Aaron C Hamilton, MD, MBA

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), is associated with a wide range of illness severity and community prevalence, with an estimated 20% to 30% of patients requiring hospitalization.^1,2 Outcome studies of hospitalized patients to date have focused on epicenter healthcare systems operating at surge-level bed capacity in resource-limited settings with mortality exceeding 20% among patients with a discharge disposition^3,4 and have had a publication bias toward those suffering critical illness.^5-7 Generalizability of these results to nonepicenter hospital systems is unclear given potential differences in triage practices and resource availability according to disease prevalence, with nonepicenter systems that are operating below capacity potentially able to accommodate the needs of most, if not all patients, requiring inpatient level care. Clinical outcomes associated with non–critically ill patients in nonepicenter regions remain poorly characterized yet highly relevant because these will ultimately apply to most US and global healthcare environments.

Nonepicenter healthcare systems must anticipate disease requirements for noncritically ill patients hospitalized with COVID-19 in order to appropriately allocate resources, including monitoring services like continuous pulse oximetry and cardiac telemetry. Data regarding the incidence of in-hospital respiratory and cardiovascular complications, including arrhythmias, among non–intensive care unit (non-ICU) hospitalized patients with COVID-19 are limited, with little granularity in terms of associated variables.^7-11 Further data are needed to guide prioritization of valuable non-ICU continuous monitoring resources to the highest-risk patients in order to minimize consumption of personal protective equipment, reduce healthcare worker exposure, and ensure adequate availability for the expansion of prepandemic services.

Projections indicate that COVID-19 incidence may persist in the coming months.^11-13 As nonessential hospital operations simultaneously resume, planning for resource allocation for patients with COVID-19 must be incorporated into broader systems of care. Further data are needed to help hospitals anticipate resource needs during this transition, especially by most systems that are caring for COVID-19 patients in nonepicenter environments. Therefore, we conducted a retrospective study of a large, multihospital, nonepicenter health system equipped with centralized continuous monitoring services in order to describe the detailed clinical course, resource utilization, and risk factors for adverse events in patients with COVID-19 initially admitted to the non-ICU setting.

Central Monitoring Unit

The central monitoring unit (CMU) provides standardized and continuous off-site secondary monitoring of cardiac telemetry and pulse oximetry for non-ICU patients within Cleveland Clinic hospitals (Ohio, Florida), with direct communication to bedside nursing and inpatient emergency response teams for clinically significant cardiac arrhythmias, respiratory events, and vital sign changes according to standardized indications, as previously reported.¹⁴ Clinical variables of interest, including electrocardiographic and vital sign data, are collected and periodically analyzed within a central registry for quality assurance, risk stratification, and resource allocation. The data registry carries Institutional Review Board approval for retrospective analysis and deidentified outcomes reporting with consent form waiver.

Study Design and Data Collection

All patients positive for SARS-CoV-2 infection by nasopharyngeal polymerase chain reaction assay (Applied Biosystems) admitted from the emergency department to a non-ICU bed at a CMU hospital on or after March 13, 2020, and subsequently discharged on or before May 1, 2020, were identified. Retrospective review of the electronic medical record was performed, with follow-up continued through hospital discharge. Data were collected on patient demographics, clinical characteristics including admission laboratories and chest x-ray findings (abnormal defined as presence of an infiltrate/opacity consistent with airspace disease), continuous monitoring utilization, respiratory support, medication treatment, ICU transfer, and final hospital disposition. In addition, prospective recordings of cardiac arrhythmias that prompted CMU notification of bedside nursing were reviewed.

The primary outcome was a composite of death, ICU transfer, or increased oxygen requirement defined as escalation from simple nasal cannula to either high-flow nasal cannula (HFNC), noninvasive ventilation (NIV) consisting of continuous positive airway pressure (CPAP) or bilevel positive airway pressure (BiPAP), or mechanical ventilation. In accordance with published guidelines, patients were treated with supplemental oxygen to maintain peripheral oxygen saturation between 92% and 96%.¹⁵

Of note, based on the validated performance of high sensitivity troponin primarily for the diagnosis of acute myocardial infarction in patients presenting to the emergency department with chest pain, our system reserves its use for this context and prefers conventional (fourth generation) troponin T testing for inpatients. Therefore, conventional troponin T values are reported in this study.

Statistical Analyses

Continuous variables are expressed as mean ± standard deviation or median (interquartile range), and categorical variables are expressed as absolute numbers with percentages. Independent samples t and Mann-Whitney U tests were used to compare continuous variables, as appropriate, and chi-square testing was used to compare categorical variables. Clinical variables satisfying an a priori two-tailed threshold of P < .05 were retained for multivariable logistic regression analysis. Variables retaining P < .05 in multivariable modeling were considered statistically significant. Analyses were performed using SPSS software, Version 23 (SPSS Inc).

Baseline Characteristics

Between March 13, 2020, and May 1, 2020, a total of 350 patients admitted from the emergency department to a non-ICU inpatient bed had a final hospital disposition. Baseline characteristics, medication treatments, and continuous monitoring utilization are shown in Table 1 and Table 2. The average age was 64 ± 16 years, more than half of patients were male (n = 194; 55%), and most patients had at least one underlying comorbidity (n = 297; 85%), the most common being hypertension (n = 230; 66%), diabetes mellitus (n = 113; 32%), and current or prior tobacco use (n = 99; 28%). The presenting syndrome most frequently included subjective fever (n = 191; 55%), cough (n = 191; 55%), or dyspnea (n = 180; 51%).

Continuous Monitoring Use

Continuous monitoring was used in most patients (n = 289; 83%), including telemetry with intermittent pulse oximetry (n = 197; 56%), telemetry with continuous pulse oximetry (n = 81; 23%), or continuous pulse oximetry alone (n = 11; 3%). Among telemetry-monitored patients (n = 278; 79%), the most frequent indication was for a noncardiac disease state (n = 187; 67%), while indications for known cardiac arrhythmia (n = 74; 27%), heart failure (n = 10; 4%), or coronary artery disease (n = 7; 2%) were less common.

Oxygen Requirements and Cardiac Arrhythmias

The maximum level of respiratory support required by each patient is shown in Appendix Figure 1A. A total of 256 patients (73%) required 3 L/min or less of supplemental oxygen by nasal cannula, 45 (13%) required more than 3 L/min of supplemental oxygen by nasal cannula, 19 (5%) required HFNC, 8 (2%) required NIV, and 22 patients (6%) required mechanical ventilation. Among patients requiring HFNC or NIV, there were 13 (48%) who remained in a non-ICU bed, while the remaining 14 patients (52%) were transferred to the ICU.

Cardiac arrhythmias were detected in 39 (14%) of the 278 telemetry-monitored patients (Appendix Figure 1B). Clinical arrhythmias consisted of supraventricular tachycardia (SVT) in 17 patients (6%), nonsustained monomorphic ventricular tachycardia (VT) in 15 patients (5%), and a prolonged pause or severe bradyarrhythmia in 12 patients (4%). There were no cases of sustained monomorphic VT, polymorphic VT (including torsades de pointes), or ventricular fibrillation. All supraventricular tachycardias, nonsustained monomorphic VTs, and bradyarrhythmias/pauses were managed medically in the non-ICU setting, with the exception of one patient who was transferred to the ICU for a primary indication of atrial fibrillation with rapid ventricular response, which was treated with amiodarone. No patient with supraventricular tachycardia required emergent cardioversion, and no patient with a bradyarrhythmia or pause required temporary or permanent pacemaker implantation.

The detection of any arrhythmia was more common in patients with a history of cardiac arrhythmia (n = 18/41 vs 21/237; 44% vs 9%; P < .001), congestive heart failure (n = 11/36 vs 28/242; 31% vs 12%; P = .002), coronary artery disease (n = 12/49 vs 27/229; 24% vs 12%; P = .02), hypertension (n = 33/190 vs 6/88; 17% vs 7%; P = .02), and an abnormal admission troponin level (n = 13/40 vs 19/142; 33% vs 13%; P = .005). Notably, of the 39 patients with cardiac arrhythmias, 35 (90%) had either an abnormal admission troponin level or a history of cardiac arrhythmia, congestive heart failure, coronary artery disease, or hypertension. Of the 17 patients with SVT episodes, 13 (76%) had a known history of atrial fibrillation. Among patients who had a cardiac arrhythmia vs those who did not, there were no differences in levels of C-reactive protein (CRP; 7.3 ± 6.2 mg/dL vs. 7.8 ± 6.8 mg/dL, P = .63) or lactate dehydrogenase (LDH; 281 ± 89 U/L vs. 318 ± 142 U/L; P = .17). Approximately half of patients were treated with hydroxychloroquine (n = 185; 53%) or azithromycin (n = 182; 52%); 41% were treated with both (n = 142), with no observed association between any arrhythmia type and treatment with one or both medications (P > .05 for all comparisons).

Discharge Disposition and Adverse Outcomes

After an average length of stay of 6.1 ± 5.9 days, final hospital disposition included discharge to home (n = 278; 79%), discharge to subacute facility (n = 40; 11%), discharge to hospice (n = 8; 2%), death (n = 22, 6%), or release against medical advice (n = 2; 1%) (Figure). The primary composite outcome occurred in 62 patients (18%), including 22 deaths (6%), 48 ICU transfers (14%), and 49 patients with increased oxygen requirements (14%). Only two deaths occurred in the absence of an increased oxygen requirement or ICU transfer.

Increased oxygen requirement was the indication for ICU transfer in 37 of 48 patients (77%), with 22 patients (46%) requiring mechanical ventilation. Of the 48 patients requiring ICU transfer, 14 (29%) died, including 10 of the 22 patients (45%) treated with mechanical ventilation. Of the 302 patients who remained in the non-ICU setting, 8 (3%) died and 8 (3%) were discharged to hospice.

In univariable analyses, the primary composite outcome was more common among older patients (event vs event free, 72 ± 13 years vs 63 ± 16 years; P < .001); it was also more common in patients with congestive heart failure (n = 14/62 vs 28/288; 23% vs 10%; P = .005), chronic obstructive pulmonary disease (n = 9/62 vs 19/288; 15% vs 7%; P = .04), lower body mass index (29 ± 5 kg/m² vs 31 ± 7 kg/m²; P = .006), lower peripheral oxygen saturation on room air (93% ± 5% vs 95% ± 3%; P = .005), higher CRP level (12.0 ± 7.8 mg/dL vs 6.9 ± 6.1 mg/dL; P < .001), higher LDH level (358 ± 140 U/L vs 302 ± 133 U/L; P = .009), higher troponin level (0.05 ± 0.13 ng/dL vs 0.02 ± 0.06 ng/dL; P = .01), abnormal D-dimer level (n = 39/42 vs 102/145; 93% vs 70%; P = .003), and abnormal chest x-ray findings (n = 48/62 vs 166/285; 77% vs 58%; P = .005) (Table 1 and Table 2). After multivariable adjustment, CRP level (odds ratio [OR], 1.09 per 1 mg/dL increase; 95% CI, 1.01-1.18; P = .04) and LDH level (OR, 1.006 per 1 U/L increase; 95% CI, 1.001-1.012; P = .03) remained significantly associated with the composite adverse outcome (Table 3). The rate of death, ICU transfer, or increased oxygen requirement was sixfold higher in patients with a CRP level in the fourth quartile (≥11.0 mg/dL) than it was among those in the first quartile (≤ 2.6 mg/dL) (P < .001 for trend), and it was fivefold higher in patients with an LDH level in the fourth quartile (≥ 354 U/L) than it was among those in the first quartile (≤ 232 U/L) (P = .001 for trend) (Appendix Figure 2). No patient with a CRP level in the reference range (≤ 0.9 mg/dL) experienced the composite adverse event, compared to three patients (n = 3/49, 6.1%) within the reference range for LDH level (≤ 225 U/L), all of whom had an elevated CRP.

DISCUSSION

In this study of 350 patients initially admitted to a non-ICU hospital bed within a large, nonepicenter healthcare system, the primary outcome of death, ICU transfer, or increased oxygen requirement occurred in 18% of patients and was independently associated with higher admission CRP and LDH levels on multivariable analysis. Most patients (73%) required 3 L/min or less of supplemental oxygen, while 14% of patients required escalation to HFNC, NIV, or mechanical ventilation. Despite frequent telemetry use (79%), cardiac arrhythmias were uncommon (14%), including no life-threatening ventricular arrhythmias. Clinical deterioration requiring ICU transfer occurred in 14% of patients, most often for an indication of increased oxygen requirement (77%). In-hospital mortality was 6% for the entire cohort, 29% for patients requiring ICU transfer, and 3% for patients who remained in the non-ICU setting.

Nonepicenter, Non-ICU Mortality

This study offers an assessment of clinical outcomes in patients with COVID-19 hospitalized in a non-ICU, nonepicenter healthcare system operating below capacity. Although such systems account for most institutions caring for patients with COVID-19, this population has been underrepresented in the literature, which has focused on epicenter hospitals and critically ill patients.^3-7 Existing epicenter estimates of in-hospital mortality for patients not requiring ICU-level care range from 6% in Northern California² to at least 10% in New York, New York,³ and 11% in Wuhan, China.⁴ The corresponding non-ICU in-hospital mortality in our study was only 3%, supporting the vital role of social distancing in reducing COVID-19 mortality by facilitating care delivery in a non–resource limited hospital setting.

Oxygen Requirements and Cardiac Arrhythmias in Non-ICU Patients

Beyond nonepicenter mortality estimates, this study is the first to provide a detailed characterization of the clinical course and resource usage among patients with COVID-19 admitted to the non-ICU setting. Given the predicted persistence of SARS-CoV-2 spread,^11-13 this information is crucial to healthcare systems that must anticipate resource requirements, such as respiratory support and continuous monitoring equipment, for the care of hospitalized patients with COVID-19. Such informed planning takes on even greater importance as prepandemic hospital services resume.

While most patients (73%) with COVID-19 admitted to a non-ICU bed required peak supplemental oxygen of 3 L/min or less, a relevant proportion (14%) developed a need for HFNC, NIV, or mechanical ventilation. Furthermore, among telemetry-monitored patients (79%), cardiac arrhythmias were uncommon (14%), and nearly all (90%) occurred in patients with either a positive troponin or known history of cardiac disease. There were no life-threatening ventricular arrhythmias associated with frequent use of hydroxychloroquine (53%) and azithromycin (52%).

These telemetry findings expand upon a smaller study of non-ICU patients receiving either hydroxychloroquine or azithromycin, in which no life-threatening ventricular tachyarrhythmias were detected.⁸ A separate study reported a 5.9% incidence of malignant ventricular tachyarrhythmias in hospitalized patients with COVID-19,¹⁰ but this study did not stratify arrhythmias by illness severity, and a high frequency of critical illness is suggested by the mechanical ventilation rate of 24%, thereby limiting comparison with our non-ICU telemetry findings.

CRP and LDH Levels as Predictors of Adverse Outcomes

This study supports the utility of obtaining CRP and LDH levels for risk stratification at the time of non-ICU hospital admission. In multivariable analysis, higher CRP and LDH levels were significantly associated with the composite adverse outcome. The adverse event rates was increased sixfold between patients with a CRP in the fourth quartile (≥ 11.0 mg/dL, 36%) and those in the first quartile (≤ 2.6 mg/dL, 5.3%), and it was fivefold higher in patients with an LDH level in the fourth quartile (≥ 354 U/L, 34%) compared with those in the first quartile (≤ 232 U/L, 7%).

These findings are consistent with prior studies that have associated elevated inflammatory markers with poor prognosis and death.^7,9,16 In some cases, COVID-19 may manifest similar to a cytokine storm syndrome, which highlights the importance of inflammation-associated tissue injury and leads to widespread interest in the use of immunosuppressive medications.^17,18 Several studies also have demonstrated an association between LDH level and severe illness,^4,7,19 although this is the first to specifically demonstrate its association with clinical decompensation in the non-ICU hospitalized population. Given that SARS-CoV-2 can infect multiple organs,^20,21 there is biological plausibility for the use of LDH levels as a nonspecific marker of tissue injury for early identification of more severe infection.

Notably, while elevated troponin levels have been strongly associated with the need for mechanical ventilation and with death, this has primarily been established using either high-sensitivity troponin assays at the time of admission²² or using peak conventional troponin levels during hospitalization.¹⁰ In this study, while abnormal conventional troponin levels at the time of non-ICU admission were not significantly associated with the primary outcome in multivariable analysis, absolute troponin values were significantly higher in univariable analysis. Incomplete troponin sampling and the lack of routine high-sensitivity troponin assay use may explain the lack of more robust troponin significance in this study.

Implications for Non-ICU Continuous Monitoring Resource Allocation

Prioritization of non-ICU continuous monitoring resources among patients with COVID-19 has numerous benefits, including reduced consumption of personal protective equipment, fewer healthcare worker exposures, and adequate availability of continuous monitoring for the expansion of prepandemic hospital services. While individualized clinical discretion is still required, the results of this study can be used as a guide for the allocation of continuous pulse oximetry and cardiac telemetry. Patients with a normal presenting CRP level and/or LDH level had a low incidence of clinical decompensation, which suggests that such patients could be monitored with intermittent rather than continuous pulse oximetry. Furthermore, cardiac telemetry could be reserved for patients with a history of cardiac comorbidities or abnormal troponin levels because such patients accounted for 90% of cardiac arrhythmias in this study.

Limitations

This study was limited to a single health system, and it lacks a direct comparison to nonhospitalized patients and those directly admitted to the ICU. Triage practices and thresholds for hospitalization may differ across institutions and regions, thereby limiting the generalizability of our study. Additional limitations include the lack of selected admission laboratories for all patients, as well as the lack of telemetry monitoring in all patients. However, any resulting selection bias may be more likely to attenuate the magnitude of observed effects given that additional testing and increased telemetry use may be expected in patients who are felt to be higher risk by routine clinical assessment.

In this study of non–critically ill patients hospitalized within a nonepicenter health system, the development of more severe illness or death was significantly associated with higher levels of CRP and LDH on admission. Clinical decompensation was driven largely by respiratory complications, while cardiac arrhythmias were rare. Overall, the non-ICU mortality rate was at least half of that reported in epicenter regions. Altogether, these findings provide valuable information for resource allocation planning while nonepicenter health systems continue caring for patients with COVID-19 as they also resume prepandemic operations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), is associated with a wide range of illness severity and community prevalence, with an estimated 20% to 30% of patients requiring hospitalization.^1,2 Outcome studies of hospitalized patients to date have focused on epicenter healthcare systems operating at surge-level bed capacity in resource-limited settings with mortality exceeding 20% among patients with a discharge disposition^3,4 and have had a publication bias toward those suffering critical illness.^5-7 Generalizability of these results to nonepicenter hospital systems is unclear given potential differences in triage practices and resource availability according to disease prevalence, with nonepicenter systems that are operating below capacity potentially able to accommodate the needs of most, if not all patients, requiring inpatient level care. Clinical outcomes associated with non–critically ill patients in nonepicenter regions remain poorly characterized yet highly relevant because these will ultimately apply to most US and global healthcare environments.

Nonepicenter healthcare systems must anticipate disease requirements for noncritically ill patients hospitalized with COVID-19 in order to appropriately allocate resources, including monitoring services like continuous pulse oximetry and cardiac telemetry. Data regarding the incidence of in-hospital respiratory and cardiovascular complications, including arrhythmias, among non–intensive care unit (non-ICU) hospitalized patients with COVID-19 are limited, with little granularity in terms of associated variables.^7-11 Further data are needed to guide prioritization of valuable non-ICU continuous monitoring resources to the highest-risk patients in order to minimize consumption of personal protective equipment, reduce healthcare worker exposure, and ensure adequate availability for the expansion of prepandemic services.

Projections indicate that COVID-19 incidence may persist in the coming months.^11-13 As nonessential hospital operations simultaneously resume, planning for resource allocation for patients with COVID-19 must be incorporated into broader systems of care. Further data are needed to help hospitals anticipate resource needs during this transition, especially by most systems that are caring for COVID-19 patients in nonepicenter environments. Therefore, we conducted a retrospective study of a large, multihospital, nonepicenter health system equipped with centralized continuous monitoring services in order to describe the detailed clinical course, resource utilization, and risk factors for adverse events in patients with COVID-19 initially admitted to the non-ICU setting.

Central Monitoring Unit

The central monitoring unit (CMU) provides standardized and continuous off-site secondary monitoring of cardiac telemetry and pulse oximetry for non-ICU patients within Cleveland Clinic hospitals (Ohio, Florida), with direct communication to bedside nursing and inpatient emergency response teams for clinically significant cardiac arrhythmias, respiratory events, and vital sign changes according to standardized indications, as previously reported.¹⁴ Clinical variables of interest, including electrocardiographic and vital sign data, are collected and periodically analyzed within a central registry for quality assurance, risk stratification, and resource allocation. The data registry carries Institutional Review Board approval for retrospective analysis and deidentified outcomes reporting with consent form waiver.

Study Design and Data Collection

All patients positive for SARS-CoV-2 infection by nasopharyngeal polymerase chain reaction assay (Applied Biosystems) admitted from the emergency department to a non-ICU bed at a CMU hospital on or after March 13, 2020, and subsequently discharged on or before May 1, 2020, were identified. Retrospective review of the electronic medical record was performed, with follow-up continued through hospital discharge. Data were collected on patient demographics, clinical characteristics including admission laboratories and chest x-ray findings (abnormal defined as presence of an infiltrate/opacity consistent with airspace disease), continuous monitoring utilization, respiratory support, medication treatment, ICU transfer, and final hospital disposition. In addition, prospective recordings of cardiac arrhythmias that prompted CMU notification of bedside nursing were reviewed.

The primary outcome was a composite of death, ICU transfer, or increased oxygen requirement defined as escalation from simple nasal cannula to either high-flow nasal cannula (HFNC), noninvasive ventilation (NIV) consisting of continuous positive airway pressure (CPAP) or bilevel positive airway pressure (BiPAP), or mechanical ventilation. In accordance with published guidelines, patients were treated with supplemental oxygen to maintain peripheral oxygen saturation between 92% and 96%.¹⁵

Of note, based on the validated performance of high sensitivity troponin primarily for the diagnosis of acute myocardial infarction in patients presenting to the emergency department with chest pain, our system reserves its use for this context and prefers conventional (fourth generation) troponin T testing for inpatients. Therefore, conventional troponin T values are reported in this study.

Statistical Analyses

Continuous variables are expressed as mean ± standard deviation or median (interquartile range), and categorical variables are expressed as absolute numbers with percentages. Independent samples t and Mann-Whitney U tests were used to compare continuous variables, as appropriate, and chi-square testing was used to compare categorical variables. Clinical variables satisfying an a priori two-tailed threshold of P < .05 were retained for multivariable logistic regression analysis. Variables retaining P < .05 in multivariable modeling were considered statistically significant. Analyses were performed using SPSS software, Version 23 (SPSS Inc).

Baseline Characteristics

Between March 13, 2020, and May 1, 2020, a total of 350 patients admitted from the emergency department to a non-ICU inpatient bed had a final hospital disposition. Baseline characteristics, medication treatments, and continuous monitoring utilization are shown in Table 1 and Table 2. The average age was 64 ± 16 years, more than half of patients were male (n = 194; 55%), and most patients had at least one underlying comorbidity (n = 297; 85%), the most common being hypertension (n = 230; 66%), diabetes mellitus (n = 113; 32%), and current or prior tobacco use (n = 99; 28%). The presenting syndrome most frequently included subjective fever (n = 191; 55%), cough (n = 191; 55%), or dyspnea (n = 180; 51%).

Continuous Monitoring Use

Continuous monitoring was used in most patients (n = 289; 83%), including telemetry with intermittent pulse oximetry (n = 197; 56%), telemetry with continuous pulse oximetry (n = 81; 23%), or continuous pulse oximetry alone (n = 11; 3%). Among telemetry-monitored patients (n = 278; 79%), the most frequent indication was for a noncardiac disease state (n = 187; 67%), while indications for known cardiac arrhythmia (n = 74; 27%), heart failure (n = 10; 4%), or coronary artery disease (n = 7; 2%) were less common.

Oxygen Requirements and Cardiac Arrhythmias

The maximum level of respiratory support required by each patient is shown in Appendix Figure 1A. A total of 256 patients (73%) required 3 L/min or less of supplemental oxygen by nasal cannula, 45 (13%) required more than 3 L/min of supplemental oxygen by nasal cannula, 19 (5%) required HFNC, 8 (2%) required NIV, and 22 patients (6%) required mechanical ventilation. Among patients requiring HFNC or NIV, there were 13 (48%) who remained in a non-ICU bed, while the remaining 14 patients (52%) were transferred to the ICU.

Cardiac arrhythmias were detected in 39 (14%) of the 278 telemetry-monitored patients (Appendix Figure 1B). Clinical arrhythmias consisted of supraventricular tachycardia (SVT) in 17 patients (6%), nonsustained monomorphic ventricular tachycardia (VT) in 15 patients (5%), and a prolonged pause or severe bradyarrhythmia in 12 patients (4%). There were no cases of sustained monomorphic VT, polymorphic VT (including torsades de pointes), or ventricular fibrillation. All supraventricular tachycardias, nonsustained monomorphic VTs, and bradyarrhythmias/pauses were managed medically in the non-ICU setting, with the exception of one patient who was transferred to the ICU for a primary indication of atrial fibrillation with rapid ventricular response, which was treated with amiodarone. No patient with supraventricular tachycardia required emergent cardioversion, and no patient with a bradyarrhythmia or pause required temporary or permanent pacemaker implantation.

The detection of any arrhythmia was more common in patients with a history of cardiac arrhythmia (n = 18/41 vs 21/237; 44% vs 9%; P < .001), congestive heart failure (n = 11/36 vs 28/242; 31% vs 12%; P = .002), coronary artery disease (n = 12/49 vs 27/229; 24% vs 12%; P = .02), hypertension (n = 33/190 vs 6/88; 17% vs 7%; P = .02), and an abnormal admission troponin level (n = 13/40 vs 19/142; 33% vs 13%; P = .005). Notably, of the 39 patients with cardiac arrhythmias, 35 (90%) had either an abnormal admission troponin level or a history of cardiac arrhythmia, congestive heart failure, coronary artery disease, or hypertension. Of the 17 patients with SVT episodes, 13 (76%) had a known history of atrial fibrillation. Among patients who had a cardiac arrhythmia vs those who did not, there were no differences in levels of C-reactive protein (CRP; 7.3 ± 6.2 mg/dL vs. 7.8 ± 6.8 mg/dL, P = .63) or lactate dehydrogenase (LDH; 281 ± 89 U/L vs. 318 ± 142 U/L; P = .17). Approximately half of patients were treated with hydroxychloroquine (n = 185; 53%) or azithromycin (n = 182; 52%); 41% were treated with both (n = 142), with no observed association between any arrhythmia type and treatment with one or both medications (P > .05 for all comparisons).

Discharge Disposition and Adverse Outcomes

After an average length of stay of 6.1 ± 5.9 days, final hospital disposition included discharge to home (n = 278; 79%), discharge to subacute facility (n = 40; 11%), discharge to hospice (n = 8; 2%), death (n = 22, 6%), or release against medical advice (n = 2; 1%) (Figure). The primary composite outcome occurred in 62 patients (18%), including 22 deaths (6%), 48 ICU transfers (14%), and 49 patients with increased oxygen requirements (14%). Only two deaths occurred in the absence of an increased oxygen requirement or ICU transfer.

Increased oxygen requirement was the indication for ICU transfer in 37 of 48 patients (77%), with 22 patients (46%) requiring mechanical ventilation. Of the 48 patients requiring ICU transfer, 14 (29%) died, including 10 of the 22 patients (45%) treated with mechanical ventilation. Of the 302 patients who remained in the non-ICU setting, 8 (3%) died and 8 (3%) were discharged to hospice.

In univariable analyses, the primary composite outcome was more common among older patients (event vs event free, 72 ± 13 years vs 63 ± 16 years; P < .001); it was also more common in patients with congestive heart failure (n = 14/62 vs 28/288; 23% vs 10%; P = .005), chronic obstructive pulmonary disease (n = 9/62 vs 19/288; 15% vs 7%; P = .04), lower body mass index (29 ± 5 kg/m² vs 31 ± 7 kg/m²; P = .006), lower peripheral oxygen saturation on room air (93% ± 5% vs 95% ± 3%; P = .005), higher CRP level (12.0 ± 7.8 mg/dL vs 6.9 ± 6.1 mg/dL; P < .001), higher LDH level (358 ± 140 U/L vs 302 ± 133 U/L; P = .009), higher troponin level (0.05 ± 0.13 ng/dL vs 0.02 ± 0.06 ng/dL; P = .01), abnormal D-dimer level (n = 39/42 vs 102/145; 93% vs 70%; P = .003), and abnormal chest x-ray findings (n = 48/62 vs 166/285; 77% vs 58%; P = .005) (Table 1 and Table 2). After multivariable adjustment, CRP level (odds ratio [OR], 1.09 per 1 mg/dL increase; 95% CI, 1.01-1.18; P = .04) and LDH level (OR, 1.006 per 1 U/L increase; 95% CI, 1.001-1.012; P = .03) remained significantly associated with the composite adverse outcome (Table 3). The rate of death, ICU transfer, or increased oxygen requirement was sixfold higher in patients with a CRP level in the fourth quartile (≥11.0 mg/dL) than it was among those in the first quartile (≤ 2.6 mg/dL) (P < .001 for trend), and it was fivefold higher in patients with an LDH level in the fourth quartile (≥ 354 U/L) than it was among those in the first quartile (≤ 232 U/L) (P = .001 for trend) (Appendix Figure 2). No patient with a CRP level in the reference range (≤ 0.9 mg/dL) experienced the composite adverse event, compared to three patients (n = 3/49, 6.1%) within the reference range for LDH level (≤ 225 U/L), all of whom had an elevated CRP.

DISCUSSION

In this study of 350 patients initially admitted to a non-ICU hospital bed within a large, nonepicenter healthcare system, the primary outcome of death, ICU transfer, or increased oxygen requirement occurred in 18% of patients and was independently associated with higher admission CRP and LDH levels on multivariable analysis. Most patients (73%) required 3 L/min or less of supplemental oxygen, while 14% of patients required escalation to HFNC, NIV, or mechanical ventilation. Despite frequent telemetry use (79%), cardiac arrhythmias were uncommon (14%), including no life-threatening ventricular arrhythmias. Clinical deterioration requiring ICU transfer occurred in 14% of patients, most often for an indication of increased oxygen requirement (77%). In-hospital mortality was 6% for the entire cohort, 29% for patients requiring ICU transfer, and 3% for patients who remained in the non-ICU setting.

Nonepicenter, Non-ICU Mortality

This study offers an assessment of clinical outcomes in patients with COVID-19 hospitalized in a non-ICU, nonepicenter healthcare system operating below capacity. Although such systems account for most institutions caring for patients with COVID-19, this population has been underrepresented in the literature, which has focused on epicenter hospitals and critically ill patients.^3-7 Existing epicenter estimates of in-hospital mortality for patients not requiring ICU-level care range from 6% in Northern California² to at least 10% in New York, New York,³ and 11% in Wuhan, China.⁴ The corresponding non-ICU in-hospital mortality in our study was only 3%, supporting the vital role of social distancing in reducing COVID-19 mortality by facilitating care delivery in a non–resource limited hospital setting.

Oxygen Requirements and Cardiac Arrhythmias in Non-ICU Patients

Beyond nonepicenter mortality estimates, this study is the first to provide a detailed characterization of the clinical course and resource usage among patients with COVID-19 admitted to the non-ICU setting. Given the predicted persistence of SARS-CoV-2 spread,^11-13 this information is crucial to healthcare systems that must anticipate resource requirements, such as respiratory support and continuous monitoring equipment, for the care of hospitalized patients with COVID-19. Such informed planning takes on even greater importance as prepandemic hospital services resume.

While most patients (73%) with COVID-19 admitted to a non-ICU bed required peak supplemental oxygen of 3 L/min or less, a relevant proportion (14%) developed a need for HFNC, NIV, or mechanical ventilation. Furthermore, among telemetry-monitored patients (79%), cardiac arrhythmias were uncommon (14%), and nearly all (90%) occurred in patients with either a positive troponin or known history of cardiac disease. There were no life-threatening ventricular arrhythmias associated with frequent use of hydroxychloroquine (53%) and azithromycin (52%).

These telemetry findings expand upon a smaller study of non-ICU patients receiving either hydroxychloroquine or azithromycin, in which no life-threatening ventricular tachyarrhythmias were detected.⁸ A separate study reported a 5.9% incidence of malignant ventricular tachyarrhythmias in hospitalized patients with COVID-19,¹⁰ but this study did not stratify arrhythmias by illness severity, and a high frequency of critical illness is suggested by the mechanical ventilation rate of 24%, thereby limiting comparison with our non-ICU telemetry findings.

CRP and LDH Levels as Predictors of Adverse Outcomes

This study supports the utility of obtaining CRP and LDH levels for risk stratification at the time of non-ICU hospital admission. In multivariable analysis, higher CRP and LDH levels were significantly associated with the composite adverse outcome. The adverse event rates was increased sixfold between patients with a CRP in the fourth quartile (≥ 11.0 mg/dL, 36%) and those in the first quartile (≤ 2.6 mg/dL, 5.3%), and it was fivefold higher in patients with an LDH level in the fourth quartile (≥ 354 U/L, 34%) compared with those in the first quartile (≤ 232 U/L, 7%).

These findings are consistent with prior studies that have associated elevated inflammatory markers with poor prognosis and death.^7,9,16 In some cases, COVID-19 may manifest similar to a cytokine storm syndrome, which highlights the importance of inflammation-associated tissue injury and leads to widespread interest in the use of immunosuppressive medications.^17,18 Several studies also have demonstrated an association between LDH level and severe illness,^4,7,19 although this is the first to specifically demonstrate its association with clinical decompensation in the non-ICU hospitalized population. Given that SARS-CoV-2 can infect multiple organs,^20,21 there is biological plausibility for the use of LDH levels as a nonspecific marker of tissue injury for early identification of more severe infection.

Notably, while elevated troponin levels have been strongly associated with the need for mechanical ventilation and with death, this has primarily been established using either high-sensitivity troponin assays at the time of admission²² or using peak conventional troponin levels during hospitalization.¹⁰ In this study, while abnormal conventional troponin levels at the time of non-ICU admission were not significantly associated with the primary outcome in multivariable analysis, absolute troponin values were significantly higher in univariable analysis. Incomplete troponin sampling and the lack of routine high-sensitivity troponin assay use may explain the lack of more robust troponin significance in this study.

Implications for Non-ICU Continuous Monitoring Resource Allocation

Prioritization of non-ICU continuous monitoring resources among patients with COVID-19 has numerous benefits, including reduced consumption of personal protective equipment, fewer healthcare worker exposures, and adequate availability of continuous monitoring for the expansion of prepandemic hospital services. While individualized clinical discretion is still required, the results of this study can be used as a guide for the allocation of continuous pulse oximetry and cardiac telemetry. Patients with a normal presenting CRP level and/or LDH level had a low incidence of clinical decompensation, which suggests that such patients could be monitored with intermittent rather than continuous pulse oximetry. Furthermore, cardiac telemetry could be reserved for patients with a history of cardiac comorbidities or abnormal troponin levels because such patients accounted for 90% of cardiac arrhythmias in this study.

Limitations

This study was limited to a single health system, and it lacks a direct comparison to nonhospitalized patients and those directly admitted to the ICU. Triage practices and thresholds for hospitalization may differ across institutions and regions, thereby limiting the generalizability of our study. Additional limitations include the lack of selected admission laboratories for all patients, as well as the lack of telemetry monitoring in all patients. However, any resulting selection bias may be more likely to attenuate the magnitude of observed effects given that additional testing and increased telemetry use may be expected in patients who are felt to be higher risk by routine clinical assessment.

In this study of non–critically ill patients hospitalized within a nonepicenter health system, the development of more severe illness or death was significantly associated with higher levels of CRP and LDH on admission. Clinical decompensation was driven largely by respiratory complications, while cardiac arrhythmias were rare. Overall, the non-ICU mortality rate was at least half of that reported in epicenter regions. Altogether, these findings provide valuable information for resource allocation planning while nonepicenter health systems continue caring for patients with COVID-19 as they also resume prepandemic operations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), is associated with a wide range of illness severity and community prevalence, with an estimated 20% to 30% of patients requiring hospitalization.^1,2 Outcome studies of hospitalized patients to date have focused on epicenter healthcare systems operating at surge-level bed capacity in resource-limited settings with mortality exceeding 20% among patients with a discharge disposition^3,4 and have had a publication bias toward those suffering critical illness.^5-7 Generalizability of these results to nonepicenter hospital systems is unclear given potential differences in triage practices and resource availability according to disease prevalence, with nonepicenter systems that are operating below capacity potentially able to accommodate the needs of most, if not all patients, requiring inpatient level care. Clinical outcomes associated with non–critically ill patients in nonepicenter regions remain poorly characterized yet highly relevant because these will ultimately apply to most US and global healthcare environments.

Nonepicenter healthcare systems must anticipate disease requirements for noncritically ill patients hospitalized with COVID-19 in order to appropriately allocate resources, including monitoring services like continuous pulse oximetry and cardiac telemetry. Data regarding the incidence of in-hospital respiratory and cardiovascular complications, including arrhythmias, among non–intensive care unit (non-ICU) hospitalized patients with COVID-19 are limited, with little granularity in terms of associated variables.^7-11 Further data are needed to guide prioritization of valuable non-ICU continuous monitoring resources to the highest-risk patients in order to minimize consumption of personal protective equipment, reduce healthcare worker exposure, and ensure adequate availability for the expansion of prepandemic services.

Projections indicate that COVID-19 incidence may persist in the coming months.^11-13 As nonessential hospital operations simultaneously resume, planning for resource allocation for patients with COVID-19 must be incorporated into broader systems of care. Further data are needed to help hospitals anticipate resource needs during this transition, especially by most systems that are caring for COVID-19 patients in nonepicenter environments. Therefore, we conducted a retrospective study of a large, multihospital, nonepicenter health system equipped with centralized continuous monitoring services in order to describe the detailed clinical course, resource utilization, and risk factors for adverse events in patients with COVID-19 initially admitted to the non-ICU setting.

Central Monitoring Unit

The central monitoring unit (CMU) provides standardized and continuous off-site secondary monitoring of cardiac telemetry and pulse oximetry for non-ICU patients within Cleveland Clinic hospitals (Ohio, Florida), with direct communication to bedside nursing and inpatient emergency response teams for clinically significant cardiac arrhythmias, respiratory events, and vital sign changes according to standardized indications, as previously reported.¹⁴ Clinical variables of interest, including electrocardiographic and vital sign data, are collected and periodically analyzed within a central registry for quality assurance, risk stratification, and resource allocation. The data registry carries Institutional Review Board approval for retrospective analysis and deidentified outcomes reporting with consent form waiver.

Study Design and Data Collection

All patients positive for SARS-CoV-2 infection by nasopharyngeal polymerase chain reaction assay (Applied Biosystems) admitted from the emergency department to a non-ICU bed at a CMU hospital on or after March 13, 2020, and subsequently discharged on or before May 1, 2020, were identified. Retrospective review of the electronic medical record was performed, with follow-up continued through hospital discharge. Data were collected on patient demographics, clinical characteristics including admission laboratories and chest x-ray findings (abnormal defined as presence of an infiltrate/opacity consistent with airspace disease), continuous monitoring utilization, respiratory support, medication treatment, ICU transfer, and final hospital disposition. In addition, prospective recordings of cardiac arrhythmias that prompted CMU notification of bedside nursing were reviewed.

The primary outcome was a composite of death, ICU transfer, or increased oxygen requirement defined as escalation from simple nasal cannula to either high-flow nasal cannula (HFNC), noninvasive ventilation (NIV) consisting of continuous positive airway pressure (CPAP) or bilevel positive airway pressure (BiPAP), or mechanical ventilation. In accordance with published guidelines, patients were treated with supplemental oxygen to maintain peripheral oxygen saturation between 92% and 96%.¹⁵

Of note, based on the validated performance of high sensitivity troponin primarily for the diagnosis of acute myocardial infarction in patients presenting to the emergency department with chest pain, our system reserves its use for this context and prefers conventional (fourth generation) troponin T testing for inpatients. Therefore, conventional troponin T values are reported in this study.

Statistical Analyses

Continuous variables are expressed as mean ± standard deviation or median (interquartile range), and categorical variables are expressed as absolute numbers with percentages. Independent samples t and Mann-Whitney U tests were used to compare continuous variables, as appropriate, and chi-square testing was used to compare categorical variables. Clinical variables satisfying an a priori two-tailed threshold of P < .05 were retained for multivariable logistic regression analysis. Variables retaining P < .05 in multivariable modeling were considered statistically significant. Analyses were performed using SPSS software, Version 23 (SPSS Inc).

Baseline Characteristics

Between March 13, 2020, and May 1, 2020, a total of 350 patients admitted from the emergency department to a non-ICU inpatient bed had a final hospital disposition. Baseline characteristics, medication treatments, and continuous monitoring utilization are shown in Table 1 and Table 2. The average age was 64 ± 16 years, more than half of patients were male (n = 194; 55%), and most patients had at least one underlying comorbidity (n = 297; 85%), the most common being hypertension (n = 230; 66%), diabetes mellitus (n = 113; 32%), and current or prior tobacco use (n = 99; 28%). The presenting syndrome most frequently included subjective fever (n = 191; 55%), cough (n = 191; 55%), or dyspnea (n = 180; 51%).

Continuous Monitoring Use

Continuous monitoring was used in most patients (n = 289; 83%), including telemetry with intermittent pulse oximetry (n = 197; 56%), telemetry with continuous pulse oximetry (n = 81; 23%), or continuous pulse oximetry alone (n = 11; 3%). Among telemetry-monitored patients (n = 278; 79%), the most frequent indication was for a noncardiac disease state (n = 187; 67%), while indications for known cardiac arrhythmia (n = 74; 27%), heart failure (n = 10; 4%), or coronary artery disease (n = 7; 2%) were less common.

Oxygen Requirements and Cardiac Arrhythmias

The maximum level of respiratory support required by each patient is shown in Appendix Figure 1A. A total of 256 patients (73%) required 3 L/min or less of supplemental oxygen by nasal cannula, 45 (13%) required more than 3 L/min of supplemental oxygen by nasal cannula, 19 (5%) required HFNC, 8 (2%) required NIV, and 22 patients (6%) required mechanical ventilation. Among patients requiring HFNC or NIV, there were 13 (48%) who remained in a non-ICU bed, while the remaining 14 patients (52%) were transferred to the ICU.

Cardiac arrhythmias were detected in 39 (14%) of the 278 telemetry-monitored patients (Appendix Figure 1B). Clinical arrhythmias consisted of supraventricular tachycardia (SVT) in 17 patients (6%), nonsustained monomorphic ventricular tachycardia (VT) in 15 patients (5%), and a prolonged pause or severe bradyarrhythmia in 12 patients (4%). There were no cases of sustained monomorphic VT, polymorphic VT (including torsades de pointes), or ventricular fibrillation. All supraventricular tachycardias, nonsustained monomorphic VTs, and bradyarrhythmias/pauses were managed medically in the non-ICU setting, with the exception of one patient who was transferred to the ICU for a primary indication of atrial fibrillation with rapid ventricular response, which was treated with amiodarone. No patient with supraventricular tachycardia required emergent cardioversion, and no patient with a bradyarrhythmia or pause required temporary or permanent pacemaker implantation.

The detection of any arrhythmia was more common in patients with a history of cardiac arrhythmia (n = 18/41 vs 21/237; 44% vs 9%; P < .001), congestive heart failure (n = 11/36 vs 28/242; 31% vs 12%; P = .002), coronary artery disease (n = 12/49 vs 27/229; 24% vs 12%; P = .02), hypertension (n = 33/190 vs 6/88; 17% vs 7%; P = .02), and an abnormal admission troponin level (n = 13/40 vs 19/142; 33% vs 13%; P = .005). Notably, of the 39 patients with cardiac arrhythmias, 35 (90%) had either an abnormal admission troponin level or a history of cardiac arrhythmia, congestive heart failure, coronary artery disease, or hypertension. Of the 17 patients with SVT episodes, 13 (76%) had a known history of atrial fibrillation. Among patients who had a cardiac arrhythmia vs those who did not, there were no differences in levels of C-reactive protein (CRP; 7.3 ± 6.2 mg/dL vs. 7.8 ± 6.8 mg/dL, P = .63) or lactate dehydrogenase (LDH; 281 ± 89 U/L vs. 318 ± 142 U/L; P = .17). Approximately half of patients were treated with hydroxychloroquine (n = 185; 53%) or azithromycin (n = 182; 52%); 41% were treated with both (n = 142), with no observed association between any arrhythmia type and treatment with one or both medications (P > .05 for all comparisons).

Discharge Disposition and Adverse Outcomes

After an average length of stay of 6.1 ± 5.9 days, final hospital disposition included discharge to home (n = 278; 79%), discharge to subacute facility (n = 40; 11%), discharge to hospice (n = 8; 2%), death (n = 22, 6%), or release against medical advice (n = 2; 1%) (Figure). The primary composite outcome occurred in 62 patients (18%), including 22 deaths (6%), 48 ICU transfers (14%), and 49 patients with increased oxygen requirements (14%). Only two deaths occurred in the absence of an increased oxygen requirement or ICU transfer.

Increased oxygen requirement was the indication for ICU transfer in 37 of 48 patients (77%), with 22 patients (46%) requiring mechanical ventilation. Of the 48 patients requiring ICU transfer, 14 (29%) died, including 10 of the 22 patients (45%) treated with mechanical ventilation. Of the 302 patients who remained in the non-ICU setting, 8 (3%) died and 8 (3%) were discharged to hospice.

In univariable analyses, the primary composite outcome was more common among older patients (event vs event free, 72 ± 13 years vs 63 ± 16 years; P < .001); it was also more common in patients with congestive heart failure (n = 14/62 vs 28/288; 23% vs 10%; P = .005), chronic obstructive pulmonary disease (n = 9/62 vs 19/288; 15% vs 7%; P = .04), lower body mass index (29 ± 5 kg/m² vs 31 ± 7 kg/m²; P = .006), lower peripheral oxygen saturation on room air (93% ± 5% vs 95% ± 3%; P = .005), higher CRP level (12.0 ± 7.8 mg/dL vs 6.9 ± 6.1 mg/dL; P < .001), higher LDH level (358 ± 140 U/L vs 302 ± 133 U/L; P = .009), higher troponin level (0.05 ± 0.13 ng/dL vs 0.02 ± 0.06 ng/dL; P = .01), abnormal D-dimer level (n = 39/42 vs 102/145; 93% vs 70%; P = .003), and abnormal chest x-ray findings (n = 48/62 vs 166/285; 77% vs 58%; P = .005) (Table 1 and Table 2). After multivariable adjustment, CRP level (odds ratio [OR], 1.09 per 1 mg/dL increase; 95% CI, 1.01-1.18; P = .04) and LDH level (OR, 1.006 per 1 U/L increase; 95% CI, 1.001-1.012; P = .03) remained significantly associated with the composite adverse outcome (Table 3). The rate of death, ICU transfer, or increased oxygen requirement was sixfold higher in patients with a CRP level in the fourth quartile (≥11.0 mg/dL) than it was among those in the first quartile (≤ 2.6 mg/dL) (P < .001 for trend), and it was fivefold higher in patients with an LDH level in the fourth quartile (≥ 354 U/L) than it was among those in the first quartile (≤ 232 U/L) (P = .001 for trend) (Appendix Figure 2). No patient with a CRP level in the reference range (≤ 0.9 mg/dL) experienced the composite adverse event, compared to three patients (n = 3/49, 6.1%) within the reference range for LDH level (≤ 225 U/L), all of whom had an elevated CRP.

DISCUSSION

In this study of 350 patients initially admitted to a non-ICU hospital bed within a large, nonepicenter healthcare system, the primary outcome of death, ICU transfer, or increased oxygen requirement occurred in 18% of patients and was independently associated with higher admission CRP and LDH levels on multivariable analysis. Most patients (73%) required 3 L/min or less of supplemental oxygen, while 14% of patients required escalation to HFNC, NIV, or mechanical ventilation. Despite frequent telemetry use (79%), cardiac arrhythmias were uncommon (14%), including no life-threatening ventricular arrhythmias. Clinical deterioration requiring ICU transfer occurred in 14% of patients, most often for an indication of increased oxygen requirement (77%). In-hospital mortality was 6% for the entire cohort, 29% for patients requiring ICU transfer, and 3% for patients who remained in the non-ICU setting.

Nonepicenter, Non-ICU Mortality

This study offers an assessment of clinical outcomes in patients with COVID-19 hospitalized in a non-ICU, nonepicenter healthcare system operating below capacity. Although such systems account for most institutions caring for patients with COVID-19, this population has been underrepresented in the literature, which has focused on epicenter hospitals and critically ill patients.^3-7 Existing epicenter estimates of in-hospital mortality for patients not requiring ICU-level care range from 6% in Northern California² to at least 10% in New York, New York,³ and 11% in Wuhan, China.⁴ The corresponding non-ICU in-hospital mortality in our study was only 3%, supporting the vital role of social distancing in reducing COVID-19 mortality by facilitating care delivery in a non–resource limited hospital setting.

Oxygen Requirements and Cardiac Arrhythmias in Non-ICU Patients

Beyond nonepicenter mortality estimates, this study is the first to provide a detailed characterization of the clinical course and resource usage among patients with COVID-19 admitted to the non-ICU setting. Given the predicted persistence of SARS-CoV-2 spread,^11-13 this information is crucial to healthcare systems that must anticipate resource requirements, such as respiratory support and continuous monitoring equipment, for the care of hospitalized patients with COVID-19. Such informed planning takes on even greater importance as prepandemic hospital services resume.

While most patients (73%) with COVID-19 admitted to a non-ICU bed required peak supplemental oxygen of 3 L/min or less, a relevant proportion (14%) developed a need for HFNC, NIV, or mechanical ventilation. Furthermore, among telemetry-monitored patients (79%), cardiac arrhythmias were uncommon (14%), and nearly all (90%) occurred in patients with either a positive troponin or known history of cardiac disease. There were no life-threatening ventricular arrhythmias associated with frequent use of hydroxychloroquine (53%) and azithromycin (52%).

These telemetry findings expand upon a smaller study of non-ICU patients receiving either hydroxychloroquine or azithromycin, in which no life-threatening ventricular tachyarrhythmias were detected.⁸ A separate study reported a 5.9% incidence of malignant ventricular tachyarrhythmias in hospitalized patients with COVID-19,¹⁰ but this study did not stratify arrhythmias by illness severity, and a high frequency of critical illness is suggested by the mechanical ventilation rate of 24%, thereby limiting comparison with our non-ICU telemetry findings.

CRP and LDH Levels as Predictors of Adverse Outcomes

This study supports the utility of obtaining CRP and LDH levels for risk stratification at the time of non-ICU hospital admission. In multivariable analysis, higher CRP and LDH levels were significantly associated with the composite adverse outcome. The adverse event rates was increased sixfold between patients with a CRP in the fourth quartile (≥ 11.0 mg/dL, 36%) and those in the first quartile (≤ 2.6 mg/dL, 5.3%), and it was fivefold higher in patients with an LDH level in the fourth quartile (≥ 354 U/L, 34%) compared with those in the first quartile (≤ 232 U/L, 7%).

These findings are consistent with prior studies that have associated elevated inflammatory markers with poor prognosis and death.^7,9,16 In some cases, COVID-19 may manifest similar to a cytokine storm syndrome, which highlights the importance of inflammation-associated tissue injury and leads to widespread interest in the use of immunosuppressive medications.^17,18 Several studies also have demonstrated an association between LDH level and severe illness,^4,7,19 although this is the first to specifically demonstrate its association with clinical decompensation in the non-ICU hospitalized population. Given that SARS-CoV-2 can infect multiple organs,^20,21 there is biological plausibility for the use of LDH levels as a nonspecific marker of tissue injury for early identification of more severe infection.

Notably, while elevated troponin levels have been strongly associated with the need for mechanical ventilation and with death, this has primarily been established using either high-sensitivity troponin assays at the time of admission²² or using peak conventional troponin levels during hospitalization.¹⁰ In this study, while abnormal conventional troponin levels at the time of non-ICU admission were not significantly associated with the primary outcome in multivariable analysis, absolute troponin values were significantly higher in univariable analysis. Incomplete troponin sampling and the lack of routine high-sensitivity troponin assay use may explain the lack of more robust troponin significance in this study.

Implications for Non-ICU Continuous Monitoring Resource Allocation

Prioritization of non-ICU continuous monitoring resources among patients with COVID-19 has numerous benefits, including reduced consumption of personal protective equipment, fewer healthcare worker exposures, and adequate availability of continuous monitoring for the expansion of prepandemic hospital services. While individualized clinical discretion is still required, the results of this study can be used as a guide for the allocation of continuous pulse oximetry and cardiac telemetry. Patients with a normal presenting CRP level and/or LDH level had a low incidence of clinical decompensation, which suggests that such patients could be monitored with intermittent rather than continuous pulse oximetry. Furthermore, cardiac telemetry could be reserved for patients with a history of cardiac comorbidities or abnormal troponin levels because such patients accounted for 90% of cardiac arrhythmias in this study.

Limitations

This study was limited to a single health system, and it lacks a direct comparison to nonhospitalized patients and those directly admitted to the ICU. Triage practices and thresholds for hospitalization may differ across institutions and regions, thereby limiting the generalizability of our study. Additional limitations include the lack of selected admission laboratories for all patients, as well as the lack of telemetry monitoring in all patients. However, any resulting selection bias may be more likely to attenuate the magnitude of observed effects given that additional testing and increased telemetry use may be expected in patients who are felt to be higher risk by routine clinical assessment.

In this study of non–critically ill patients hospitalized within a nonepicenter health system, the development of more severe illness or death was significantly associated with higher levels of CRP and LDH on admission. Clinical decompensation was driven largely by respiratory complications, while cardiac arrhythmias were rare. Overall, the non-ICU mortality rate was at least half of that reported in epicenter regions. Altogether, these findings provide valuable information for resource allocation planning while nonepicenter health systems continue caring for patients with COVID-19 as they also resume prepandemic operations.

Individuals aged 65 years and over represent 13% of the United States population and account for nearly 40% of hospital discharges.¹ Bedrest hastens the functional decline of older patients^2-5 and is associated with risk of serious complications, such as falls, delirium, venous thrombosis, and skin breakdown.^6,7 Ambulation is widely recognized as important for improving hospital outcomes.^8-10 Observational studies suggest that increases of 600 steps per day are associated with shortened length of hospital stay.⁹ However, randomized trials of assisted ambulation have not demonstrated consistent benefit.^11-14 As a result, usual care at most hospitals in the United States does not include assisted ambulation. Even when ambulation is ordered, execution of the orders is inconsistent.^15-17

Studies have demonstrated the benefits of various exercise protocols for older patients in rehabilitation facilities,^18,19 medical intensive care units,²⁰ and medical and surgical wards.^13,18,21 These interventions are usually nursing centered; however, assisting patients with ambulation multiple times per day may be a burdensome addition to the myriad responsibilities of nurses.^19,22,23 In fact, ambulation orders are the most frequently overlooked nursing task.²⁴

We designed a graded protocol of assisted ambulation implemented by a dedicated patient care nursing assistant (PCNA) multiple times daily to increase patient mobility. The objective of this study was to assess the feasibility and effectiveness of such an intervention for older inpatients. We hypothesized that the intervention would prove feasible and improve hospital outcomes, including less need for inpatient rehabilitation and shorter length of stay.

We conducted a single-blind randomized controlled trial of patients aged ≥60 years and admitted as medical inpatients to the Cleveland Clinic Main Campus, a tertiary care center with over 1,440 inpatient beds. The consent form and study protocol were approved by the Cleveland Clinic Institutional Review Board, and the study was registered with ClinicalTrials.gov (NCT02757131).

Patients

All patients who were admitted to study wards for a medical illness and evaluated by Physical Therapy (PT) were eligible for the study. PT evaluations were ordered by the medical team if deemed necessary on the basis of factors, such as age, estimated mobility, and concerns raised by the ancillary staff. All patients who were expected to be discharged to a skilled nursing facility placement or who required home PT received a PT evaluation. Assessment of mobility was documented via Activity Measure for Postacute Care Inpatient Basic Mobility “six-clicks” short form, hereafter abbreviated as “six-clicks.” Based on past experience, patients with scores <16 rarely go home (<20% of the time), and those with scores >20 usually go home regardless of ambulation. Therefore, only patients with scores of 16-20 were invited to participate in the study. Although patients who were not evaluated by PT might also benefit from the intervention, we required a six-clicks score to assess eligibility. The exclusion criteria included anticipated remaining length of stay less than three days, admission under observation status, admission to the intensive care unit (ICU,) patients receiving comfort care measures, and patients with medical conditions precluding ambulation, such as decompensated heart failure or unstable angina.

Randomization

Patients were randomized to “usual care” or “mobility technician” after baseline evaluation using a computerized system. A block randomization scheme with a size of four was used to ensure an approximately equal number of patients per group.

Intervention

Patients randomized to the intervention group were asked to participate in the ambulation protocol outlined by the PT three times daily under the supervision of the mobility technician. The protocol involved four exercise levels (sitting, standing, walking, and stairs), which were implemented depending on the patient’s physical capacity. The mobility technicians, who were PCNAs, were trained by the PT team. PCNAs have no specific degrees or certification. They are taught safe handling techniques during their job orientation, so they already had an understanding of how to transfer and assist a patient with ambulation. The mobility technician training consisted of one four-hour session run by the PT team in the physical therapy department and the nursing unit. The training included safe handling practices and basic mobility, such as transfers from bed to chair, bed to standing, walking with assistance, and walking independently with equipment such as cane, rolling walker, and walking belt. All instruction was demonstrated by the trainer, and the mobility technician was then able to practice. The mobility technician then shadowed the trainer and practiced the techniques under supervision. Competency was assessed by the trainer.

The cohort of patients randomized to “usual care” was not seen by the mobility technicians but was not otherwise restricted in nursing’s baseline ability to execute recommendations placed by the PT team. Compliance with the recommendations is highly variable and dependent on patient acuity during the shift, staffing issues, and competing duties. Cleveland Clinic promotes a “culture of mobility,” and nurses are encouraged to get patients out of bed and assist with ambulation.

Study Instruments—Measures of Mobility

The six-clicks instrument is a tool for measuring basic mobility. It was adapted from the Activity Measures for Post-Acute Care (AM-PAC) instrument.²⁵ Although initially created for self-report in the post-acute care setting, six-clicks has been validated for use by PTs in the acute care setting²⁶ and is currently in use at more than 1,000 US hospitals. Cleveland Clinic PTs have used this measure for routine evaluation since 2011. The instrument has high interrater reliability and can predict discharge disposition.^27-29

Each patient was provided with a tracking device (Fitbit) attached at the wrist to record daily steps for measuring mobility. The use of Fitbit has been validated in ambulatory and inpatient settings.³⁰ The device produces step counts within 3% of the observed step count for most patients but may undercount steps in patients with very slow gait.³¹ The device was provided to each enrollee and collected at discharge.

Variables

Demographic information, comorbid diagnoses, and discharge destination were extracted from the electronic medical record. Information on prehospitalization physical activity level was obtained from the initial PT assessment. Falls were tracked through the safety event reporting system.

Outcomes

The primary outcomes were discharge disposition and hospital length of stay. The secondary outcomes included average steps per day, change in six-clicks score from admission to discharge, inpatient mortality, admission to ICU, falls, deep vein thrombosis, pulmonary embolism, or pneumonia, and readmission within 30 days.

Statistical Analysis

Patient characteristics were summarized as means and standard deviations or medians and interquartile ranges for continuous variables and as frequencies and percentages for categorical variables. The t-test or Wilcoxon rank sum test was applied to compare continuous characteristics between the intervention and control groups. Chi-squared test or Fisher’s exact test was applied to compare categorical characteristics. Given its skewed distribution, the length of stay was log-transformed and compared between the two groups using Student’s t-test. Chi-squared test was used to compare categorical outcomes. The analysis of final six-clicks scores was adjusted for baseline scores, and the least-square estimates are provided. A linear mixed effects model was used to compare the number of daily steps taken because each participant had multiple steps measured. Results were adjusted for prehospital activity. In addition to comparing the total steps taken by each group, we determined the proportion of patients who exceeded a particular threshold by taking the average number of steps per day for all subjects and relating it to home discharge using the Receiver Operating Characteristics (ROC) curve. An optimal cut-off was determined to maximize the Youden index. We also compared the proportion of patients who exceeded 900 steps because this value was previously reported as an important threshold.³² All analyses were conducted using intention-to-treat principles. We also conducted a per-protocol analysis in which we limited the intervention group to those who received at least one assisted ambulation session. A dose-response analysis was also performed, in which patients were categorized as not receiving the therapy, receiving sessions on one or two days, or receiving them on more than two days.

All analyses were conducted using R-studio (Boston, MA). Statistical significance was defined as a P-value < .05. Given that this is a pilot study, the results were not adjusted for multiple comparisons.

Characteristics of patients in the intervention and control groups are shown in Table 1. The patients were mostly white and female, with an average age in the mid-70s (range 61-98). All measures evaluated were not significantly different between the intervention and control groups. However, more patients in the intervention group had a prehospital activity level classified as independent.

Table 2 demonstrates the feasibility of the intervention. Of patients randomized to the intervention group, 74% were ambulated at least once. Once enrolled, the patients successfully participated in assisted ambulation for about two-thirds of their hospital stay. However, the intervention was delivered for only one-third of the total length of stay because most patients were not enrolled on admission. On average, the mobility technicians made 11 attempts to ambulate each patient and 56% of these attempts were successful. The proportion of unsuccessful attempts did not change over the course of the study. The reasons for unsuccessful attempts included patient refusal (n = 102) or unavailability (n = 68), mobility technicians running out of time (n = 2), and other (n = 12).

In this pilot study conducted with older medical inpatients, we found that assisted ambulation provided by a dedicated mobility technician was feasible and increased the number of steps taken by patients. Not all patients in the treatment group received the intervention partly due to the fact that the program initially did not include weekends and the mobility technicians were sometimes redirected to other nursing duties. Both issues were addressed during the course of the study. In the per protocol analysis, the intervention increased the average six-clicks score and there was a nonsignificant reduction in the percentage of patients discharged to a rehabilitation facility.

A range of hospital-based mobility interventions have been described. Several of which were complex multidisciplinary interventions that included a mobility component. The compliance rates have ranged from 82% to 93.7%,12,13 although a systematic review noted that many studies do not provide this level of information.¹¹ Interventions were carried out by nursing staff and PT with support from family members and social workers.^33-35 Ambulation-specific programs have also relied on nurses and PT13,14,36 and, occasionally, on research assistants to implement assisted ambulation protocols.^12,37 A recent study that employed research assistants to deliver inhospital ambulation reported achieving 51.3% of intended walks.³⁷

In contradistinction to previous studies, we created a new role, employing PCNAs as dedicated mobility technicians. We did this for two reasons. First, the approach is less expensive than deploying registered nurses or PTs to ambulate patients and therefore more likely to be adopted by hospitals, especially if it can decrease the cost of an episode of care by avoiding subsequent inpatient rehabilitation. Mobility technicians have no degree or certification requirements and are therefore paid less than nurses or physical therapists. Second, by having a single responsibility, mobility technicians were more likely to engage in their task than nurses, who have competing responsibilities. However, when nurse staffing was short, nurse managers were tempted to recall the PCNAs for other nursing duties. It took time before PCNAs and supervisors prioritized this new responsibility. When they did, the number of attempted walks increased substantially, but the percentage of successful attempts remained constant at 56%, highlighting the difficulty of getting hospitalized patients to walk.

On average, patients who received the intervention engaged in 72 minutes of additional physical activity and averaged 990 steps per day. Observational data suggest patients accrue about 1,100 steps in the day before discharge, with older patients accruing closer to 900.21 One study found that older patients with fewer than 900 steps per day were likely to experience a functional decline.32 We also found that patients who achieved at least 900 steps were more likely to go home. However, we found that a lower threshold, namely, 400 steps, offered better discrimination between patients who go home and those who do not. Future prospective studies are needed to establish the appropriate goal for exercise interventions. A lower step goal could dramatically enhance the efficiency of the intervention.

A Cochrane review found that pooled analysis of multidisciplinary interventions that included exercise, often in the form of walking, achieved a small but significant increase in the proportion of patients discharged to home (RR 1.08, 95%CI 1.03 to 1.14).¹¹ We found no significant change in the discharge disposition, but our study was underpowered for this endpoint. The six-clicks score showed a small but significant change in the per protocol analysis. The six-clicks score has been shown to correlate with discharge disposition,^28,29 and an improvement in the score suggests that discharge disposition may be influenced.

The intervention may also not have been implemented for long enough. On average, visits were achieved for one-third of the hospital stay partly because of the delay in PT evaluation, which we required for eligibility. In practice, PT evaluation can occur just a few days before the anticipated discharge. We observed a dose dependent response among patients in the intervention group, suggesting that earlier intervention could be more effective. Earlier intervention might be achieved if the MT performed the six-clicks on potentially eligible patients.

The effects of hospitalization on mobility may be the most pronounced in the long term; one study found that 40% of hospitalized older patients manifested new ADL or IADL disability three months after discharge compared with 31% at discharge.⁷ Hospital-based mobility interventions may continue to affect subjects’ independence for weeks or months. In one RCT, an inpatient ambulation intervention improved mobility in the community one month after discharge.³⁷ A hospital-based exercise program that included ambulation achieved better functional outcomes one month later.¹³ One RCT that combined inpatient exercise with outpatient care coordination also decreased readmission rates.³⁴ We found that the intervention did not affect readmission.

This pilot study has several limitations. The sample size was small, and the findings need to be replicated in a larger randomized controlled trial. This is particularly important because the two study arms were not balanced in terms of their prehospital activity. After adjustment for prehospital activity, the differences in the step count in the intention-to-treat analysis were no longer significant. As we adjusted the intervention to hospital workflow, the intervention changed over time. The intention-to-treat analysis may therefore underestimate the effect of the intervention. This work provides a basis for future trial. Finally, discharge disposition depends on a complex interplay of factors, including social factors and preferences, which may not be affected by a mobility intervention.

In summary, an inhospital mobility protocol of attempting ambulation delivered by dedicated mobility technicians three times daily successfully increased the daily step counts and mobility scores of the patients. Studies with a larger sample size are needed to determine whether the proposed approach can affect length of hospital stay, discharge disposition, and overall cost of an episode of care.

Disclosures

Mary Stilphen reports consulting for CreCare and Adeo, which license and distribute AM-PAC short forms, including 6 clicks. All other authors report no conflicts of interest.

Funding

This study was supported by a Research Program Committee grant from the Cleveland Clinic.

Individuals aged 65 years and over represent 13% of the United States population and account for nearly 40% of hospital discharges.¹ Bedrest hastens the functional decline of older patients^2-5 and is associated with risk of serious complications, such as falls, delirium, venous thrombosis, and skin breakdown.^6,7 Ambulation is widely recognized as important for improving hospital outcomes.^8-10 Observational studies suggest that increases of 600 steps per day are associated with shortened length of hospital stay.⁹ However, randomized trials of assisted ambulation have not demonstrated consistent benefit.^11-14 As a result, usual care at most hospitals in the United States does not include assisted ambulation. Even when ambulation is ordered, execution of the orders is inconsistent.^15-17

Studies have demonstrated the benefits of various exercise protocols for older patients in rehabilitation facilities,^18,19 medical intensive care units,²⁰ and medical and surgical wards.^13,18,21 These interventions are usually nursing centered; however, assisting patients with ambulation multiple times per day may be a burdensome addition to the myriad responsibilities of nurses.^19,22,23 In fact, ambulation orders are the most frequently overlooked nursing task.²⁴

We designed a graded protocol of assisted ambulation implemented by a dedicated patient care nursing assistant (PCNA) multiple times daily to increase patient mobility. The objective of this study was to assess the feasibility and effectiveness of such an intervention for older inpatients. We hypothesized that the intervention would prove feasible and improve hospital outcomes, including less need for inpatient rehabilitation and shorter length of stay.

We conducted a single-blind randomized controlled trial of patients aged ≥60 years and admitted as medical inpatients to the Cleveland Clinic Main Campus, a tertiary care center with over 1,440 inpatient beds. The consent form and study protocol were approved by the Cleveland Clinic Institutional Review Board, and the study was registered with ClinicalTrials.gov (NCT02757131).

Patients

All patients who were admitted to study wards for a medical illness and evaluated by Physical Therapy (PT) were eligible for the study. PT evaluations were ordered by the medical team if deemed necessary on the basis of factors, such as age, estimated mobility, and concerns raised by the ancillary staff. All patients who were expected to be discharged to a skilled nursing facility placement or who required home PT received a PT evaluation. Assessment of mobility was documented via Activity Measure for Postacute Care Inpatient Basic Mobility “six-clicks” short form, hereafter abbreviated as “six-clicks.” Based on past experience, patients with scores <16 rarely go home (<20% of the time), and those with scores >20 usually go home regardless of ambulation. Therefore, only patients with scores of 16-20 were invited to participate in the study. Although patients who were not evaluated by PT might also benefit from the intervention, we required a six-clicks score to assess eligibility. The exclusion criteria included anticipated remaining length of stay less than three days, admission under observation status, admission to the intensive care unit (ICU,) patients receiving comfort care measures, and patients with medical conditions precluding ambulation, such as decompensated heart failure or unstable angina.

Randomization

Patients were randomized to “usual care” or “mobility technician” after baseline evaluation using a computerized system. A block randomization scheme with a size of four was used to ensure an approximately equal number of patients per group.

Intervention

Patients randomized to the intervention group were asked to participate in the ambulation protocol outlined by the PT three times daily under the supervision of the mobility technician. The protocol involved four exercise levels (sitting, standing, walking, and stairs), which were implemented depending on the patient’s physical capacity. The mobility technicians, who were PCNAs, were trained by the PT team. PCNAs have no specific degrees or certification. They are taught safe handling techniques during their job orientation, so they already had an understanding of how to transfer and assist a patient with ambulation. The mobility technician training consisted of one four-hour session run by the PT team in the physical therapy department and the nursing unit. The training included safe handling practices and basic mobility, such as transfers from bed to chair, bed to standing, walking with assistance, and walking independently with equipment such as cane, rolling walker, and walking belt. All instruction was demonstrated by the trainer, and the mobility technician was then able to practice. The mobility technician then shadowed the trainer and practiced the techniques under supervision. Competency was assessed by the trainer.

The cohort of patients randomized to “usual care” was not seen by the mobility technicians but was not otherwise restricted in nursing’s baseline ability to execute recommendations placed by the PT team. Compliance with the recommendations is highly variable and dependent on patient acuity during the shift, staffing issues, and competing duties. Cleveland Clinic promotes a “culture of mobility,” and nurses are encouraged to get patients out of bed and assist with ambulation.

Study Instruments—Measures of Mobility

The six-clicks instrument is a tool for measuring basic mobility. It was adapted from the Activity Measures for Post-Acute Care (AM-PAC) instrument.²⁵ Although initially created for self-report in the post-acute care setting, six-clicks has been validated for use by PTs in the acute care setting²⁶ and is currently in use at more than 1,000 US hospitals. Cleveland Clinic PTs have used this measure for routine evaluation since 2011. The instrument has high interrater reliability and can predict discharge disposition.^27-29

Each patient was provided with a tracking device (Fitbit) attached at the wrist to record daily steps for measuring mobility. The use of Fitbit has been validated in ambulatory and inpatient settings.³⁰ The device produces step counts within 3% of the observed step count for most patients but may undercount steps in patients with very slow gait.³¹ The device was provided to each enrollee and collected at discharge.

Variables

Demographic information, comorbid diagnoses, and discharge destination were extracted from the electronic medical record. Information on prehospitalization physical activity level was obtained from the initial PT assessment. Falls were tracked through the safety event reporting system.

Outcomes

The primary outcomes were discharge disposition and hospital length of stay. The secondary outcomes included average steps per day, change in six-clicks score from admission to discharge, inpatient mortality, admission to ICU, falls, deep vein thrombosis, pulmonary embolism, or pneumonia, and readmission within 30 days.

Statistical Analysis

Patient characteristics were summarized as means and standard deviations or medians and interquartile ranges for continuous variables and as frequencies and percentages for categorical variables. The t-test or Wilcoxon rank sum test was applied to compare continuous characteristics between the intervention and control groups. Chi-squared test or Fisher’s exact test was applied to compare categorical characteristics. Given its skewed distribution, the length of stay was log-transformed and compared between the two groups using Student’s t-test. Chi-squared test was used to compare categorical outcomes. The analysis of final six-clicks scores was adjusted for baseline scores, and the least-square estimates are provided. A linear mixed effects model was used to compare the number of daily steps taken because each participant had multiple steps measured. Results were adjusted for prehospital activity. In addition to comparing the total steps taken by each group, we determined the proportion of patients who exceeded a particular threshold by taking the average number of steps per day for all subjects and relating it to home discharge using the Receiver Operating Characteristics (ROC) curve. An optimal cut-off was determined to maximize the Youden index. We also compared the proportion of patients who exceeded 900 steps because this value was previously reported as an important threshold.³² All analyses were conducted using intention-to-treat principles. We also conducted a per-protocol analysis in which we limited the intervention group to those who received at least one assisted ambulation session. A dose-response analysis was also performed, in which patients were categorized as not receiving the therapy, receiving sessions on one or two days, or receiving them on more than two days.

All analyses were conducted using R-studio (Boston, MA). Statistical significance was defined as a P-value < .05. Given that this is a pilot study, the results were not adjusted for multiple comparisons.

Characteristics of patients in the intervention and control groups are shown in Table 1. The patients were mostly white and female, with an average age in the mid-70s (range 61-98). All measures evaluated were not significantly different between the intervention and control groups. However, more patients in the intervention group had a prehospital activity level classified as independent.

Table 2 demonstrates the feasibility of the intervention. Of patients randomized to the intervention group, 74% were ambulated at least once. Once enrolled, the patients successfully participated in assisted ambulation for about two-thirds of their hospital stay. However, the intervention was delivered for only one-third of the total length of stay because most patients were not enrolled on admission. On average, the mobility technicians made 11 attempts to ambulate each patient and 56% of these attempts were successful. The proportion of unsuccessful attempts did not change over the course of the study. The reasons for unsuccessful attempts included patient refusal (n = 102) or unavailability (n = 68), mobility technicians running out of time (n = 2), and other (n = 12).

In this pilot study conducted with older medical inpatients, we found that assisted ambulation provided by a dedicated mobility technician was feasible and increased the number of steps taken by patients. Not all patients in the treatment group received the intervention partly due to the fact that the program initially did not include weekends and the mobility technicians were sometimes redirected to other nursing duties. Both issues were addressed during the course of the study. In the per protocol analysis, the intervention increased the average six-clicks score and there was a nonsignificant reduction in the percentage of patients discharged to a rehabilitation facility.

A range of hospital-based mobility interventions have been described. Several of which were complex multidisciplinary interventions that included a mobility component. The compliance rates have ranged from 82% to 93.7%,12,13 although a systematic review noted that many studies do not provide this level of information.¹¹ Interventions were carried out by nursing staff and PT with support from family members and social workers.^33-35 Ambulation-specific programs have also relied on nurses and PT13,14,36 and, occasionally, on research assistants to implement assisted ambulation protocols.^12,37 A recent study that employed research assistants to deliver inhospital ambulation reported achieving 51.3% of intended walks.³⁷

In contradistinction to previous studies, we created a new role, employing PCNAs as dedicated mobility technicians. We did this for two reasons. First, the approach is less expensive than deploying registered nurses or PTs to ambulate patients and therefore more likely to be adopted by hospitals, especially if it can decrease the cost of an episode of care by avoiding subsequent inpatient rehabilitation. Mobility technicians have no degree or certification requirements and are therefore paid less than nurses or physical therapists. Second, by having a single responsibility, mobility technicians were more likely to engage in their task than nurses, who have competing responsibilities. However, when nurse staffing was short, nurse managers were tempted to recall the PCNAs for other nursing duties. It took time before PCNAs and supervisors prioritized this new responsibility. When they did, the number of attempted walks increased substantially, but the percentage of successful attempts remained constant at 56%, highlighting the difficulty of getting hospitalized patients to walk.

On average, patients who received the intervention engaged in 72 minutes of additional physical activity and averaged 990 steps per day. Observational data suggest patients accrue about 1,100 steps in the day before discharge, with older patients accruing closer to 900.21 One study found that older patients with fewer than 900 steps per day were likely to experience a functional decline.32 We also found that patients who achieved at least 900 steps were more likely to go home. However, we found that a lower threshold, namely, 400 steps, offered better discrimination between patients who go home and those who do not. Future prospective studies are needed to establish the appropriate goal for exercise interventions. A lower step goal could dramatically enhance the efficiency of the intervention.

A Cochrane review found that pooled analysis of multidisciplinary interventions that included exercise, often in the form of walking, achieved a small but significant increase in the proportion of patients discharged to home (RR 1.08, 95%CI 1.03 to 1.14).¹¹ We found no significant change in the discharge disposition, but our study was underpowered for this endpoint. The six-clicks score showed a small but significant change in the per protocol analysis. The six-clicks score has been shown to correlate with discharge disposition,^28,29 and an improvement in the score suggests that discharge disposition may be influenced.

The intervention may also not have been implemented for long enough. On average, visits were achieved for one-third of the hospital stay partly because of the delay in PT evaluation, which we required for eligibility. In practice, PT evaluation can occur just a few days before the anticipated discharge. We observed a dose dependent response among patients in the intervention group, suggesting that earlier intervention could be more effective. Earlier intervention might be achieved if the MT performed the six-clicks on potentially eligible patients.

The effects of hospitalization on mobility may be the most pronounced in the long term; one study found that 40% of hospitalized older patients manifested new ADL or IADL disability three months after discharge compared with 31% at discharge.⁷ Hospital-based mobility interventions may continue to affect subjects’ independence for weeks or months. In one RCT, an inpatient ambulation intervention improved mobility in the community one month after discharge.³⁷ A hospital-based exercise program that included ambulation achieved better functional outcomes one month later.¹³ One RCT that combined inpatient exercise with outpatient care coordination also decreased readmission rates.³⁴ We found that the intervention did not affect readmission.

This pilot study has several limitations. The sample size was small, and the findings need to be replicated in a larger randomized controlled trial. This is particularly important because the two study arms were not balanced in terms of their prehospital activity. After adjustment for prehospital activity, the differences in the step count in the intention-to-treat analysis were no longer significant. As we adjusted the intervention to hospital workflow, the intervention changed over time. The intention-to-treat analysis may therefore underestimate the effect of the intervention. This work provides a basis for future trial. Finally, discharge disposition depends on a complex interplay of factors, including social factors and preferences, which may not be affected by a mobility intervention.

In summary, an inhospital mobility protocol of attempting ambulation delivered by dedicated mobility technicians three times daily successfully increased the daily step counts and mobility scores of the patients. Studies with a larger sample size are needed to determine whether the proposed approach can affect length of hospital stay, discharge disposition, and overall cost of an episode of care.

Disclosures

Mary Stilphen reports consulting for CreCare and Adeo, which license and distribute AM-PAC short forms, including 6 clicks. All other authors report no conflicts of interest.

Funding

This study was supported by a Research Program Committee grant from the Cleveland Clinic.

Individuals aged 65 years and over represent 13% of the United States population and account for nearly 40% of hospital discharges.¹ Bedrest hastens the functional decline of older patients^2-5 and is associated with risk of serious complications, such as falls, delirium, venous thrombosis, and skin breakdown.^6,7 Ambulation is widely recognized as important for improving hospital outcomes.^8-10 Observational studies suggest that increases of 600 steps per day are associated with shortened length of hospital stay.⁹ However, randomized trials of assisted ambulation have not demonstrated consistent benefit.^11-14 As a result, usual care at most hospitals in the United States does not include assisted ambulation. Even when ambulation is ordered, execution of the orders is inconsistent.^15-17

Studies have demonstrated the benefits of various exercise protocols for older patients in rehabilitation facilities,^18,19 medical intensive care units,²⁰ and medical and surgical wards.^13,18,21 These interventions are usually nursing centered; however, assisting patients with ambulation multiple times per day may be a burdensome addition to the myriad responsibilities of nurses.^19,22,23 In fact, ambulation orders are the most frequently overlooked nursing task.²⁴

We designed a graded protocol of assisted ambulation implemented by a dedicated patient care nursing assistant (PCNA) multiple times daily to increase patient mobility. The objective of this study was to assess the feasibility and effectiveness of such an intervention for older inpatients. We hypothesized that the intervention would prove feasible and improve hospital outcomes, including less need for inpatient rehabilitation and shorter length of stay.

We conducted a single-blind randomized controlled trial of patients aged ≥60 years and admitted as medical inpatients to the Cleveland Clinic Main Campus, a tertiary care center with over 1,440 inpatient beds. The consent form and study protocol were approved by the Cleveland Clinic Institutional Review Board, and the study was registered with ClinicalTrials.gov (NCT02757131).

Patients

All patients who were admitted to study wards for a medical illness and evaluated by Physical Therapy (PT) were eligible for the study. PT evaluations were ordered by the medical team if deemed necessary on the basis of factors, such as age, estimated mobility, and concerns raised by the ancillary staff. All patients who were expected to be discharged to a skilled nursing facility placement or who required home PT received a PT evaluation. Assessment of mobility was documented via Activity Measure for Postacute Care Inpatient Basic Mobility “six-clicks” short form, hereafter abbreviated as “six-clicks.” Based on past experience, patients with scores <16 rarely go home (<20% of the time), and those with scores >20 usually go home regardless of ambulation. Therefore, only patients with scores of 16-20 were invited to participate in the study. Although patients who were not evaluated by PT might also benefit from the intervention, we required a six-clicks score to assess eligibility. The exclusion criteria included anticipated remaining length of stay less than three days, admission under observation status, admission to the intensive care unit (ICU,) patients receiving comfort care measures, and patients with medical conditions precluding ambulation, such as decompensated heart failure or unstable angina.

Randomization

Patients were randomized to “usual care” or “mobility technician” after baseline evaluation using a computerized system. A block randomization scheme with a size of four was used to ensure an approximately equal number of patients per group.

Intervention

Patients randomized to the intervention group were asked to participate in the ambulation protocol outlined by the PT three times daily under the supervision of the mobility technician. The protocol involved four exercise levels (sitting, standing, walking, and stairs), which were implemented depending on the patient’s physical capacity. The mobility technicians, who were PCNAs, were trained by the PT team. PCNAs have no specific degrees or certification. They are taught safe handling techniques during their job orientation, so they already had an understanding of how to transfer and assist a patient with ambulation. The mobility technician training consisted of one four-hour session run by the PT team in the physical therapy department and the nursing unit. The training included safe handling practices and basic mobility, such as transfers from bed to chair, bed to standing, walking with assistance, and walking independently with equipment such as cane, rolling walker, and walking belt. All instruction was demonstrated by the trainer, and the mobility technician was then able to practice. The mobility technician then shadowed the trainer and practiced the techniques under supervision. Competency was assessed by the trainer.

The cohort of patients randomized to “usual care” was not seen by the mobility technicians but was not otherwise restricted in nursing’s baseline ability to execute recommendations placed by the PT team. Compliance with the recommendations is highly variable and dependent on patient acuity during the shift, staffing issues, and competing duties. Cleveland Clinic promotes a “culture of mobility,” and nurses are encouraged to get patients out of bed and assist with ambulation.

Study Instruments—Measures of Mobility

The six-clicks instrument is a tool for measuring basic mobility. It was adapted from the Activity Measures for Post-Acute Care (AM-PAC) instrument.²⁵ Although initially created for self-report in the post-acute care setting, six-clicks has been validated for use by PTs in the acute care setting²⁶ and is currently in use at more than 1,000 US hospitals. Cleveland Clinic PTs have used this measure for routine evaluation since 2011. The instrument has high interrater reliability and can predict discharge disposition.^27-29

Each patient was provided with a tracking device (Fitbit) attached at the wrist to record daily steps for measuring mobility. The use of Fitbit has been validated in ambulatory and inpatient settings.³⁰ The device produces step counts within 3% of the observed step count for most patients but may undercount steps in patients with very slow gait.³¹ The device was provided to each enrollee and collected at discharge.

Variables

Demographic information, comorbid diagnoses, and discharge destination were extracted from the electronic medical record. Information on prehospitalization physical activity level was obtained from the initial PT assessment. Falls were tracked through the safety event reporting system.

Outcomes

The primary outcomes were discharge disposition and hospital length of stay. The secondary outcomes included average steps per day, change in six-clicks score from admission to discharge, inpatient mortality, admission to ICU, falls, deep vein thrombosis, pulmonary embolism, or pneumonia, and readmission within 30 days.

Statistical Analysis

Patient characteristics were summarized as means and standard deviations or medians and interquartile ranges for continuous variables and as frequencies and percentages for categorical variables. The t-test or Wilcoxon rank sum test was applied to compare continuous characteristics between the intervention and control groups. Chi-squared test or Fisher’s exact test was applied to compare categorical characteristics. Given its skewed distribution, the length of stay was log-transformed and compared between the two groups using Student’s t-test. Chi-squared test was used to compare categorical outcomes. The analysis of final six-clicks scores was adjusted for baseline scores, and the least-square estimates are provided. A linear mixed effects model was used to compare the number of daily steps taken because each participant had multiple steps measured. Results were adjusted for prehospital activity. In addition to comparing the total steps taken by each group, we determined the proportion of patients who exceeded a particular threshold by taking the average number of steps per day for all subjects and relating it to home discharge using the Receiver Operating Characteristics (ROC) curve. An optimal cut-off was determined to maximize the Youden index. We also compared the proportion of patients who exceeded 900 steps because this value was previously reported as an important threshold.³² All analyses were conducted using intention-to-treat principles. We also conducted a per-protocol analysis in which we limited the intervention group to those who received at least one assisted ambulation session. A dose-response analysis was also performed, in which patients were categorized as not receiving the therapy, receiving sessions on one or two days, or receiving them on more than two days.

All analyses were conducted using R-studio (Boston, MA). Statistical significance was defined as a P-value < .05. Given that this is a pilot study, the results were not adjusted for multiple comparisons.

Characteristics of patients in the intervention and control groups are shown in Table 1. The patients were mostly white and female, with an average age in the mid-70s (range 61-98). All measures evaluated were not significantly different between the intervention and control groups. However, more patients in the intervention group had a prehospital activity level classified as independent.

Table 2 demonstrates the feasibility of the intervention. Of patients randomized to the intervention group, 74% were ambulated at least once. Once enrolled, the patients successfully participated in assisted ambulation for about two-thirds of their hospital stay. However, the intervention was delivered for only one-third of the total length of stay because most patients were not enrolled on admission. On average, the mobility technicians made 11 attempts to ambulate each patient and 56% of these attempts were successful. The proportion of unsuccessful attempts did not change over the course of the study. The reasons for unsuccessful attempts included patient refusal (n = 102) or unavailability (n = 68), mobility technicians running out of time (n = 2), and other (n = 12).

In this pilot study conducted with older medical inpatients, we found that assisted ambulation provided by a dedicated mobility technician was feasible and increased the number of steps taken by patients. Not all patients in the treatment group received the intervention partly due to the fact that the program initially did not include weekends and the mobility technicians were sometimes redirected to other nursing duties. Both issues were addressed during the course of the study. In the per protocol analysis, the intervention increased the average six-clicks score and there was a nonsignificant reduction in the percentage of patients discharged to a rehabilitation facility.

A range of hospital-based mobility interventions have been described. Several of which were complex multidisciplinary interventions that included a mobility component. The compliance rates have ranged from 82% to 93.7%,12,13 although a systematic review noted that many studies do not provide this level of information.¹¹ Interventions were carried out by nursing staff and PT with support from family members and social workers.^33-35 Ambulation-specific programs have also relied on nurses and PT13,14,36 and, occasionally, on research assistants to implement assisted ambulation protocols.^12,37 A recent study that employed research assistants to deliver inhospital ambulation reported achieving 51.3% of intended walks.³⁷

In contradistinction to previous studies, we created a new role, employing PCNAs as dedicated mobility technicians. We did this for two reasons. First, the approach is less expensive than deploying registered nurses or PTs to ambulate patients and therefore more likely to be adopted by hospitals, especially if it can decrease the cost of an episode of care by avoiding subsequent inpatient rehabilitation. Mobility technicians have no degree or certification requirements and are therefore paid less than nurses or physical therapists. Second, by having a single responsibility, mobility technicians were more likely to engage in their task than nurses, who have competing responsibilities. However, when nurse staffing was short, nurse managers were tempted to recall the PCNAs for other nursing duties. It took time before PCNAs and supervisors prioritized this new responsibility. When they did, the number of attempted walks increased substantially, but the percentage of successful attempts remained constant at 56%, highlighting the difficulty of getting hospitalized patients to walk.

On average, patients who received the intervention engaged in 72 minutes of additional physical activity and averaged 990 steps per day. Observational data suggest patients accrue about 1,100 steps in the day before discharge, with older patients accruing closer to 900.21 One study found that older patients with fewer than 900 steps per day were likely to experience a functional decline.32 We also found that patients who achieved at least 900 steps were more likely to go home. However, we found that a lower threshold, namely, 400 steps, offered better discrimination between patients who go home and those who do not. Future prospective studies are needed to establish the appropriate goal for exercise interventions. A lower step goal could dramatically enhance the efficiency of the intervention.

A Cochrane review found that pooled analysis of multidisciplinary interventions that included exercise, often in the form of walking, achieved a small but significant increase in the proportion of patients discharged to home (RR 1.08, 95%CI 1.03 to 1.14).¹¹ We found no significant change in the discharge disposition, but our study was underpowered for this endpoint. The six-clicks score showed a small but significant change in the per protocol analysis. The six-clicks score has been shown to correlate with discharge disposition,^28,29 and an improvement in the score suggests that discharge disposition may be influenced.

The intervention may also not have been implemented for long enough. On average, visits were achieved for one-third of the hospital stay partly because of the delay in PT evaluation, which we required for eligibility. In practice, PT evaluation can occur just a few days before the anticipated discharge. We observed a dose dependent response among patients in the intervention group, suggesting that earlier intervention could be more effective. Earlier intervention might be achieved if the MT performed the six-clicks on potentially eligible patients.

The effects of hospitalization on mobility may be the most pronounced in the long term; one study found that 40% of hospitalized older patients manifested new ADL or IADL disability three months after discharge compared with 31% at discharge.⁷ Hospital-based mobility interventions may continue to affect subjects’ independence for weeks or months. In one RCT, an inpatient ambulation intervention improved mobility in the community one month after discharge.³⁷ A hospital-based exercise program that included ambulation achieved better functional outcomes one month later.¹³ One RCT that combined inpatient exercise with outpatient care coordination also decreased readmission rates.³⁴ We found that the intervention did not affect readmission.

This pilot study has several limitations. The sample size was small, and the findings need to be replicated in a larger randomized controlled trial. This is particularly important because the two study arms were not balanced in terms of their prehospital activity. After adjustment for prehospital activity, the differences in the step count in the intention-to-treat analysis were no longer significant. As we adjusted the intervention to hospital workflow, the intervention changed over time. The intention-to-treat analysis may therefore underestimate the effect of the intervention. This work provides a basis for future trial. Finally, discharge disposition depends on a complex interplay of factors, including social factors and preferences, which may not be affected by a mobility intervention.

In summary, an inhospital mobility protocol of attempting ambulation delivered by dedicated mobility technicians three times daily successfully increased the daily step counts and mobility scores of the patients. Studies with a larger sample size are needed to determine whether the proposed approach can affect length of hospital stay, discharge disposition, and overall cost of an episode of care.

Disclosures

Mary Stilphen reports consulting for CreCare and Adeo, which license and distribute AM-PAC short forms, including 6 clicks. All other authors report no conflicts of interest.

Funding

This study was supported by a Research Program Committee grant from the Cleveland Clinic.