Risk Model for VTE

Venous thromboembolism (VTE) is a major source of morbidity and mortality for hospitalized patients. Among medical patients at the highest risk, as many as 15% can be expected to develop a VTE during their hospital stay1, 2; however, among general medical patients, the incidence of symptomatic VTE is less than 1%,1 and potentially as low as 0.3%.3 Thromboprophylaxis with subcutaneous heparin reduces the risk of VTE by approximately 50%,4 and is therefore recommended for medical patients at high risk. However, heparin also increases the risk of bleeding and thrombocytopenia and thus should be avoided for patients at low risk of VTE. Consequently, the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) recommends that all hospitalized medical patients receive a risk assessment for VTE.5

Certain disease states, including stroke, acute myocardial infarction, heart failure, respiratory disease, sepsis, and cancer, have been associated with increased risk for VTE, and, based on the inclusion criteria of several randomized trials, current American College of Chest Physicians (ACCP) guidelines recommend thromboprophylaxis for patients hospitalized with these diagnoses.2 However, evidence that these factors actually increase a patient's risk for VTE comes from studies of ambulatory patients and is often weak or conflicting. Existing risk‐stratification tools,6, 7 as well as the ACCP guidelines, have not been validated, and accordingly JCAHO does not specify how risk assessment should be conducted. In order to help clinicians better estimate the risk of VTE in medical patients and therefore to provide more targeted thromboprophylaxis, we examined a large cohort of patients with high‐risk diagnoses and created a risk stratification model.

Methods

Results

Our sample contained 242,738 patients, 194,198 (80%) assigned to the derivation set and 48,540 (20%) to the validation set. Patient characteristics were similar in both sets (Supporting Information Appendix Table 1). Most patients were over age 65, 59% were female, and 64% were white (Table 1). The most common primary diagnoses were pneumonia (33%) and congestive heart failure (19%). The most common comorbidities were hypertension (50%), diabetes (31%), chronic pulmonary disease (30%), and anemia (20%). Most patients were cared for by internists (54%) or family practitioners (21%), and 30% received some form of anticoagulant VTE prophylaxis (Table 2). Of patients with an ICD‐9 code for VTE during hospitalization, just over half lacked either diagnostic testing, treatment, or both, leaving 612 (0.25%) patients who fulfilled our criteria for VTE; an additional 440 (0.18%) were readmitted for VTE, for an overall incidence of 0.43%. Patients with a length of stay 6 days had an incidence of 0.79% vs 0.19% for patients with shorter stays.

Risk factors for VTE

A large number of patient and hospital factors were associated with the development of VTE (Table 1). Due to the large sample size, even weak associations appear highly statistically significant. Compared to patients without VTE, those with VTE were more likely to have received VTE prophylaxis (37% vs 30%, P < 0.001). However, models of patients receiving prophylaxis and of patients not receiving prophylaxis produced similar odds ratios for the various risk factors (Supporting Information Appendix Table 2); therefore, the final model includes both patients who did, and did not, receive VTE prophylaxis. In the multivariable model (Supporting Information Appendix Table 3), age, length of stay, gender, primary diagnosis, cancer, inflammatory bowel disease, obesity, central venous catheter, inherited thrombophilia, steroid use, mechanical ventilation, active chemotherapy, and urinary catheters were all associated with VTE (Table 3). The strongest risk factors were length of stay 6 days (OR 3.22, 95% CI 2.73, 3.79), central venous catheter (OR 1.87, 95% CI 1.52, 2.29), inflammatory bowel disease (OR 3.11, 95% CI 1.59, 6.08), and inherited thrombophilia (OR 4.00, 95% CI 0.98, 16.40). In addition, there were important interactions between age and cancer; cancer was a strong risk factor among younger patients, but is not as strong a risk factor among older patients (OR compared to young patients without cancer was 4.62 (95% CI 2.72, 7.87) for those age 1849 years, and 3.64 (95% CI 2.52, 5.25) for those aged 5064 years).

Table 3.Factors Associated Venous Thromboembolism (VTE) in Multivariable Model

Risk Factor	OR	95% CI
* For patients without cancer. Comparison group is patients aged 18‐49 years without cancer.
Any prophylaxis	0.98	(0.84, 1.14)
Female	0.85	(0.74, 0.98)
Length of stay 6 days	3.22	(2.73, 3.79)
Age*
18‐49 years	1	Referent
50‐64 years	1.15	(0.86, 1.56)
>65 years	1.51	(1.17, 1.96)
Primary diagnosis
Pneumonia	1	Referent
Chronic obstructive pulmonary disease	0.57	(0.44, 0.75)
Stroke	0.84	(0.66, 1.08)
Congestive heart failure	0.86	(0.70, 1.06)
Urinary tract infection	1.19	(0.95, 1.50)
Respiratory failure	1.15	(0.85, 1.55)
Septicemia	1.11	(0.82, 1.50)
Comorbidities
Inflammatory bowel disease	3.11	(1.59, 6.08)
Obesity	1.28	(0.99, 1.66)
Inherited thrombophilia	4.00	(0.98, 16.40)
Cancer
18‐49 years	4.62	(2.72, 7.87)
50‐64 years	3.64	(2.52, 5.25)
>65 years	2.17	(1.61, 2.92)
Treatments
Central venous catheter	1.87	(1.52, 2.29)
Mechanical ventilation	1.61	(1.27, 2.05)
Urinary catheter	1.17	(0.99, 1.38)
Chemotherapy	1.71	(1.03, 2.83)
Steroids	1.22	(1.04, 1.43)

In the derivation set, the multivariable model produced deciles of mean predicted risk from 0.11% to 1.45%, while mean observed risk over the same deciles ranged from 0.12% to 1.42% (Figure 1). Within the validation cohort, the observed rate of VTE was 0.46% (223 cases among 48,543 subjects). The expected rate according to the model was 0.43% (expected/observed ratio: 0.93 [95% CI 0.82, 1.06]). Model discrimination measured by the c‐statistic in the validation set was 0.75 (95% CI 0.71, 0.78). The model produced deciles of mean predicted risk from 0.11% to 1.46%, with mean observed risk over the same deciles from 0.17% to 1.81%. Risk gradient was relatively flat across the first 6 deciles, began to rise at the seventh decile, and rose sharply in the highest one. Using a risk threshold of 1%, the model had a sensitivity of 28% and a specificity of 93%. In the validation set, this translated into a positive predictive value of 2.2% and a negative predictive value of 99.7%. Assuming that VTE prophylaxis has an efficacy of 50%, the number‐needed‐to‐treat to prevent one VTE among high‐risk patients (predicted risk >1%) would be 91. In contrast, providing prophylaxis to the entire validation sample would result in a number‐needed‐to‐treat of 435. Using a lower treatment threshold of 0.4% produced a positive predictive value of 1% and a negative predictive value of 99.8%. At this threshold, the model would detect 73% of patients with VTE and the number‐needed‐to‐treat to prevent one VTE would be 200.

Figure 1

Discussion

In a representative sample of 243,000 hospitalized medical patients with at least one major risk factor for VTE, we found that symptomatic VTE was an uncommon event, occurring in approximately 1 in 231 patients. We identified a number of factors that were associated with an increased risk of VTE, but many previously cited risk factors did not show an association in multivariable models. In particular, patients with a primary diagnosis of COPD appeared not to share the same high risk of VTE as patients with the other diagnoses we examined, a finding reported by others.11 The risk model we developed accurately stratifies patients across a wide range of VTE probabilities, but even among those with the highest predicted rates, symptomatic VTE occurred in less than 2%.

VTE is often described as a frequent complication of hospitalization for medical illness and one of the most common potentially preventable causes of death. Indeed, rates of asymptomatic VTE have been demonstrated to be 3.7% to 26%.12 Although some of these might have fatal consequences, most are distal vein thromboses and their significance is unknown. In contrast, symptomatic events are uncommon, with previous estimates among general medical patients in observational studies in the range of 0.3%3 to 0.8%,12 similar to the rate observed in our study. Symptomatic event rates among control patients in landmark randomized trials have ranged from 0.86%13 to 2.3%,14 but these studies enrolled only very high‐risk patients with more extended hospitalizations, and may involve follow‐up periods of a month or more.

Because it is unlikely that our diagnostic algorithm was 100% sensitive, and because 30% of our patients received chemoprophylaxis, it is probable that we have underestimated the true rate of VTE in our sample. Among the patients who received prophylaxis, the observed rate of VTE was 0.54%. If we assume that prophylaxis is 50% effective, then had these patients not received prophylaxis, their rate of VTE would have been 1.08% (vs 0.39% among those patients who received no prophylaxis) and the overall rate of VTE for the sample would have been 0.60% (1.08 0.30 + 0.39 0.70). If we further assume that our algorithm was only 80% sensitive and 100% specific, the true underlying rate of symptomatic VTE could have been as high as 0.75%, still less than half that seen in randomized trials.

Prophylaxis with heparin has been shown to decrease the rate of both asymptomatic and symptomatic events, but because of the low prevalence, the number‐needed‐to‐treat to prevent one symptomatic pulmonary embolism has been estimated at 345, and prophylaxis has not been shown to affect all‐cause mortality.4, 15 At the same time, prophylaxis costs money, is uncomfortable, and carries a small risk of bleeding and heparin‐induced thrombocytopenia. Given the generally low incidence of symptomatic VTE, it therefore makes sense to reserve prophylaxis for patients at higher risk of thromboembolism.

To decide whether prophylaxis is appropriate for a given patient, it is necessary to quantify the patient's risk and then apply an appropriate threshold for treatment. The National Quality Forum (NQF) recommends,16 and JCAHO has adopted, that a clinician must evaluate each patient upon admission, and regularly thereafter, for the risk of developing DVT [deep vein thrombosis]/VTE. Until now, however, there has been no widely accepted, validated method to risk stratify medical patients. The ACCP recommendations cite just three studies of VTE risk factors in hospitalized medical patients.11, 17, 18 Together they examined 477 cases and 1197 controls, identifying congestive heart failure, pneumonia, cancer, and previous VTE as risk factors. Predictive models based on these factors17, 1921 have not been subjected to validation or have performed poorly.18 Acknowledging this lack of standardized risk assessment, JCAHO leaves the means of assessment to individual hospitals. A quality improvement guide published by the Agency for Healthcare Research and Quality goes one step further, stating that In a typical hospital, it is estimated that fewer than 5% of medical patients could be considered at low risk by most VTE risk stratification methods.22 The guide recommends near universal VTE prophylaxis.

In light of the JCAHO requirements, our model should be welcomed by hospitalists. Rather than assuming that all patients over 40 years of age are at high risk, our model will enable clinicians to risk stratify patients from a low of 0.1% to >1.4% (>10‐fold increase in risk). Moreover, the model was derived from more than 800 episodes of symptomatic VTE among almost 190,000 general medical patients and validated on almost 50,000 more. The observed patients were cared for in clinical practice at a nationally representative group of US hospitals, not in a highly selected clinical trial, increasing the generalizability of our findings. Finally, the model includes ten common risk factors that can easily be entered into decision support software or extracted automatically from the electronic medical record. Electronic reminder systems have already been shown to increase use of VTE prophylaxis, and prevent VTE, especially among cancer patients.23

A more challenging task is defining the appropriate risk threshold to initiate VTE prophylaxis. The Thromboembolic Risk Factors (THRIFT) Consensus Group classified patients according to risk of proximal DVT as low (<1%), moderate (1%‐10%), and high (>10%).21 They recommended heparin prophylaxis for all patients at moderate risk or higher. Although the patients included in our study all had a diagnosis that warranted prophylaxis according to the ACCP guidelines, using the THRIFT threshold for moderate‐to‐high risk, only 7% of our patients should have received prophylaxis. The recommendation not to offer heparin prophylaxis to patients with less than 1% chance of developing symptomatic VTE seems reasonable, given the large number‐needed‐to‐treat, but formal decision analyses should be conducted to better define this threshold. Many hospitalists, however, may feel uncomfortable using the 1% threshold, because our model failed to identify almost three out of four patients who ultimately experienced symptomatic VTE. At that threshold, it would seem that hospital‐acquired VTE is not a preventable complication in most medical patients, as others have pointed out.3, 24 Alternatively, if the threshold were lowered to 0.4%, our model could reduce the use of prophylaxis by 60%, while still identifying three‐fourths of all VTE cases. Further research is needed to know whether such a threshold is reasonable.

Our study has a number of important limitations. First, we relied on claims data, not chart review. We do not know for certain which patients experienced VTE, although our definition of VTE required diagnosis codes plus charges for both diagnosis and treatment. Moreover, our rates are similar to those observed in other trials where symptomatic events were confirmed. Second, about 30% of our patients received at least some VTE prophylaxis, and this may have prevented as many as half of the VTEs in that group. Without prophylaxis, rates might have been 20%30% higher. Similarly, we could not detect patients who were diagnosed after discharge but not admitted to hospital. While we believe this number to be small, it would again increase the rate slightly. Third, we could not assess certain clinical circumstances that are not associated with hospital charges or diagnosis codes, especially prolonged bed rest. Other risk factors, such as the urinary catheter, were probably surrogate markers for immobilization rather than true risk factors. Fourth, we included length of stay in our prediction model. We did this because most randomized trials of VTE prophylaxis included only patients with an expected length of stay 6 days. Physicians' estimates about probable length of stay may be less accurate than actual length of stay as a predictor of VTE. Moreover, the relationship may have been confounded if hospital‐acquired VTE led to longer lengths of stay. We think this unlikely since many of the events were discovered on readmission. Fifth, we studied only patients carrying high‐risk diagnoses, and therefore do not know the baseline risk for patients with less risky conditions, although it should be lower than what we observed. It seems probable that COPD, rather than being protective, as it appears in our model, actually represents the baseline risk for low‐risk diagnoses. It should be noted that we did include a number of other high‐risk diagnoses, such as cancer and inflammatory bowel disease, as secondary diagnoses. A larger, more inclusive study should be conducted to validate our model in other populations. Finally, we cannot know who died of undiagnosed VTE, either in the hospital or after discharge. Such an outcome would be important, but those events are likely to be rare, and VTE prophylaxis has not been shown to affect mortality.

VTE remains a daunting problem in hospitalized medical patients. Although VTE is responsible for a large number of hospital deaths each year, identifying patients at high risk for clinically important VTE is challenging, and may contribute to the persistently low rates of VTE prophylaxis seen in hospitals.25 Current efforts to treat nearly all patients are likely to lead to unnecessary cost, discomfort, and side effects. We present a simple logistic regression model that can easily identify patients at moderate‐to‐high risk (>1%) of developing symptomatic VTE. Future studies should focus on prospectively validating the model in a wider spectrum of medical illness, and better defining the appropriate risk cutoff for general prophylaxis.

Venous thromboembolism (VTE) is a major source of morbidity and mortality for hospitalized patients. Among medical patients at the highest risk, as many as 15% can be expected to develop a VTE during their hospital stay1, 2; however, among general medical patients, the incidence of symptomatic VTE is less than 1%,1 and potentially as low as 0.3%.3 Thromboprophylaxis with subcutaneous heparin reduces the risk of VTE by approximately 50%,4 and is therefore recommended for medical patients at high risk. However, heparin also increases the risk of bleeding and thrombocytopenia and thus should be avoided for patients at low risk of VTE. Consequently, the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) recommends that all hospitalized medical patients receive a risk assessment for VTE.5

Certain disease states, including stroke, acute myocardial infarction, heart failure, respiratory disease, sepsis, and cancer, have been associated with increased risk for VTE, and, based on the inclusion criteria of several randomized trials, current American College of Chest Physicians (ACCP) guidelines recommend thromboprophylaxis for patients hospitalized with these diagnoses.2 However, evidence that these factors actually increase a patient's risk for VTE comes from studies of ambulatory patients and is often weak or conflicting. Existing risk‐stratification tools,6, 7 as well as the ACCP guidelines, have not been validated, and accordingly JCAHO does not specify how risk assessment should be conducted. In order to help clinicians better estimate the risk of VTE in medical patients and therefore to provide more targeted thromboprophylaxis, we examined a large cohort of patients with high‐risk diagnoses and created a risk stratification model.

Methods

Results

Our sample contained 242,738 patients, 194,198 (80%) assigned to the derivation set and 48,540 (20%) to the validation set. Patient characteristics were similar in both sets (Supporting Information Appendix Table 1). Most patients were over age 65, 59% were female, and 64% were white (Table 1). The most common primary diagnoses were pneumonia (33%) and congestive heart failure (19%). The most common comorbidities were hypertension (50%), diabetes (31%), chronic pulmonary disease (30%), and anemia (20%). Most patients were cared for by internists (54%) or family practitioners (21%), and 30% received some form of anticoagulant VTE prophylaxis (Table 2). Of patients with an ICD‐9 code for VTE during hospitalization, just over half lacked either diagnostic testing, treatment, or both, leaving 612 (0.25%) patients who fulfilled our criteria for VTE; an additional 440 (0.18%) were readmitted for VTE, for an overall incidence of 0.43%. Patients with a length of stay 6 days had an incidence of 0.79% vs 0.19% for patients with shorter stays.

Risk factors for VTE

A large number of patient and hospital factors were associated with the development of VTE (Table 1). Due to the large sample size, even weak associations appear highly statistically significant. Compared to patients without VTE, those with VTE were more likely to have received VTE prophylaxis (37% vs 30%, P < 0.001). However, models of patients receiving prophylaxis and of patients not receiving prophylaxis produced similar odds ratios for the various risk factors (Supporting Information Appendix Table 2); therefore, the final model includes both patients who did, and did not, receive VTE prophylaxis. In the multivariable model (Supporting Information Appendix Table 3), age, length of stay, gender, primary diagnosis, cancer, inflammatory bowel disease, obesity, central venous catheter, inherited thrombophilia, steroid use, mechanical ventilation, active chemotherapy, and urinary catheters were all associated with VTE (Table 3). The strongest risk factors were length of stay 6 days (OR 3.22, 95% CI 2.73, 3.79), central venous catheter (OR 1.87, 95% CI 1.52, 2.29), inflammatory bowel disease (OR 3.11, 95% CI 1.59, 6.08), and inherited thrombophilia (OR 4.00, 95% CI 0.98, 16.40). In addition, there were important interactions between age and cancer; cancer was a strong risk factor among younger patients, but is not as strong a risk factor among older patients (OR compared to young patients without cancer was 4.62 (95% CI 2.72, 7.87) for those age 1849 years, and 3.64 (95% CI 2.52, 5.25) for those aged 5064 years).

Table 3.Factors Associated Venous Thromboembolism (VTE) in Multivariable Model

Risk Factor	OR	95% CI
* For patients without cancer. Comparison group is patients aged 18‐49 years without cancer.
Any prophylaxis	0.98	(0.84, 1.14)
Female	0.85	(0.74, 0.98)
Length of stay 6 days	3.22	(2.73, 3.79)
Age*
18‐49 years	1	Referent
50‐64 years	1.15	(0.86, 1.56)
>65 years	1.51	(1.17, 1.96)
Primary diagnosis
Pneumonia	1	Referent
Chronic obstructive pulmonary disease	0.57	(0.44, 0.75)
Stroke	0.84	(0.66, 1.08)
Congestive heart failure	0.86	(0.70, 1.06)
Urinary tract infection	1.19	(0.95, 1.50)
Respiratory failure	1.15	(0.85, 1.55)
Septicemia	1.11	(0.82, 1.50)
Comorbidities
Inflammatory bowel disease	3.11	(1.59, 6.08)
Obesity	1.28	(0.99, 1.66)
Inherited thrombophilia	4.00	(0.98, 16.40)
Cancer
18‐49 years	4.62	(2.72, 7.87)
50‐64 years	3.64	(2.52, 5.25)
>65 years	2.17	(1.61, 2.92)
Treatments
Central venous catheter	1.87	(1.52, 2.29)
Mechanical ventilation	1.61	(1.27, 2.05)
Urinary catheter	1.17	(0.99, 1.38)
Chemotherapy	1.71	(1.03, 2.83)
Steroids	1.22	(1.04, 1.43)

In the derivation set, the multivariable model produced deciles of mean predicted risk from 0.11% to 1.45%, while mean observed risk over the same deciles ranged from 0.12% to 1.42% (Figure 1). Within the validation cohort, the observed rate of VTE was 0.46% (223 cases among 48,543 subjects). The expected rate according to the model was 0.43% (expected/observed ratio: 0.93 [95% CI 0.82, 1.06]). Model discrimination measured by the c‐statistic in the validation set was 0.75 (95% CI 0.71, 0.78). The model produced deciles of mean predicted risk from 0.11% to 1.46%, with mean observed risk over the same deciles from 0.17% to 1.81%. Risk gradient was relatively flat across the first 6 deciles, began to rise at the seventh decile, and rose sharply in the highest one. Using a risk threshold of 1%, the model had a sensitivity of 28% and a specificity of 93%. In the validation set, this translated into a positive predictive value of 2.2% and a negative predictive value of 99.7%. Assuming that VTE prophylaxis has an efficacy of 50%, the number‐needed‐to‐treat to prevent one VTE among high‐risk patients (predicted risk >1%) would be 91. In contrast, providing prophylaxis to the entire validation sample would result in a number‐needed‐to‐treat of 435. Using a lower treatment threshold of 0.4% produced a positive predictive value of 1% and a negative predictive value of 99.8%. At this threshold, the model would detect 73% of patients with VTE and the number‐needed‐to‐treat to prevent one VTE would be 200.

Figure 1

Discussion

In a representative sample of 243,000 hospitalized medical patients with at least one major risk factor for VTE, we found that symptomatic VTE was an uncommon event, occurring in approximately 1 in 231 patients. We identified a number of factors that were associated with an increased risk of VTE, but many previously cited risk factors did not show an association in multivariable models. In particular, patients with a primary diagnosis of COPD appeared not to share the same high risk of VTE as patients with the other diagnoses we examined, a finding reported by others.11 The risk model we developed accurately stratifies patients across a wide range of VTE probabilities, but even among those with the highest predicted rates, symptomatic VTE occurred in less than 2%.

VTE is often described as a frequent complication of hospitalization for medical illness and one of the most common potentially preventable causes of death. Indeed, rates of asymptomatic VTE have been demonstrated to be 3.7% to 26%.12 Although some of these might have fatal consequences, most are distal vein thromboses and their significance is unknown. In contrast, symptomatic events are uncommon, with previous estimates among general medical patients in observational studies in the range of 0.3%3 to 0.8%,12 similar to the rate observed in our study. Symptomatic event rates among control patients in landmark randomized trials have ranged from 0.86%13 to 2.3%,14 but these studies enrolled only very high‐risk patients with more extended hospitalizations, and may involve follow‐up periods of a month or more.

Because it is unlikely that our diagnostic algorithm was 100% sensitive, and because 30% of our patients received chemoprophylaxis, it is probable that we have underestimated the true rate of VTE in our sample. Among the patients who received prophylaxis, the observed rate of VTE was 0.54%. If we assume that prophylaxis is 50% effective, then had these patients not received prophylaxis, their rate of VTE would have been 1.08% (vs 0.39% among those patients who received no prophylaxis) and the overall rate of VTE for the sample would have been 0.60% (1.08 0.30 + 0.39 0.70). If we further assume that our algorithm was only 80% sensitive and 100% specific, the true underlying rate of symptomatic VTE could have been as high as 0.75%, still less than half that seen in randomized trials.

Prophylaxis with heparin has been shown to decrease the rate of both asymptomatic and symptomatic events, but because of the low prevalence, the number‐needed‐to‐treat to prevent one symptomatic pulmonary embolism has been estimated at 345, and prophylaxis has not been shown to affect all‐cause mortality.4, 15 At the same time, prophylaxis costs money, is uncomfortable, and carries a small risk of bleeding and heparin‐induced thrombocytopenia. Given the generally low incidence of symptomatic VTE, it therefore makes sense to reserve prophylaxis for patients at higher risk of thromboembolism.

To decide whether prophylaxis is appropriate for a given patient, it is necessary to quantify the patient's risk and then apply an appropriate threshold for treatment. The National Quality Forum (NQF) recommends,16 and JCAHO has adopted, that a clinician must evaluate each patient upon admission, and regularly thereafter, for the risk of developing DVT [deep vein thrombosis]/VTE. Until now, however, there has been no widely accepted, validated method to risk stratify medical patients. The ACCP recommendations cite just three studies of VTE risk factors in hospitalized medical patients.11, 17, 18 Together they examined 477 cases and 1197 controls, identifying congestive heart failure, pneumonia, cancer, and previous VTE as risk factors. Predictive models based on these factors17, 1921 have not been subjected to validation or have performed poorly.18 Acknowledging this lack of standardized risk assessment, JCAHO leaves the means of assessment to individual hospitals. A quality improvement guide published by the Agency for Healthcare Research and Quality goes one step further, stating that In a typical hospital, it is estimated that fewer than 5% of medical patients could be considered at low risk by most VTE risk stratification methods.22 The guide recommends near universal VTE prophylaxis.

In light of the JCAHO requirements, our model should be welcomed by hospitalists. Rather than assuming that all patients over 40 years of age are at high risk, our model will enable clinicians to risk stratify patients from a low of 0.1% to >1.4% (>10‐fold increase in risk). Moreover, the model was derived from more than 800 episodes of symptomatic VTE among almost 190,000 general medical patients and validated on almost 50,000 more. The observed patients were cared for in clinical practice at a nationally representative group of US hospitals, not in a highly selected clinical trial, increasing the generalizability of our findings. Finally, the model includes ten common risk factors that can easily be entered into decision support software or extracted automatically from the electronic medical record. Electronic reminder systems have already been shown to increase use of VTE prophylaxis, and prevent VTE, especially among cancer patients.23

A more challenging task is defining the appropriate risk threshold to initiate VTE prophylaxis. The Thromboembolic Risk Factors (THRIFT) Consensus Group classified patients according to risk of proximal DVT as low (<1%), moderate (1%‐10%), and high (>10%).21 They recommended heparin prophylaxis for all patients at moderate risk or higher. Although the patients included in our study all had a diagnosis that warranted prophylaxis according to the ACCP guidelines, using the THRIFT threshold for moderate‐to‐high risk, only 7% of our patients should have received prophylaxis. The recommendation not to offer heparin prophylaxis to patients with less than 1% chance of developing symptomatic VTE seems reasonable, given the large number‐needed‐to‐treat, but formal decision analyses should be conducted to better define this threshold. Many hospitalists, however, may feel uncomfortable using the 1% threshold, because our model failed to identify almost three out of four patients who ultimately experienced symptomatic VTE. At that threshold, it would seem that hospital‐acquired VTE is not a preventable complication in most medical patients, as others have pointed out.3, 24 Alternatively, if the threshold were lowered to 0.4%, our model could reduce the use of prophylaxis by 60%, while still identifying three‐fourths of all VTE cases. Further research is needed to know whether such a threshold is reasonable.

Our study has a number of important limitations. First, we relied on claims data, not chart review. We do not know for certain which patients experienced VTE, although our definition of VTE required diagnosis codes plus charges for both diagnosis and treatment. Moreover, our rates are similar to those observed in other trials where symptomatic events were confirmed. Second, about 30% of our patients received at least some VTE prophylaxis, and this may have prevented as many as half of the VTEs in that group. Without prophylaxis, rates might have been 20%30% higher. Similarly, we could not detect patients who were diagnosed after discharge but not admitted to hospital. While we believe this number to be small, it would again increase the rate slightly. Third, we could not assess certain clinical circumstances that are not associated with hospital charges or diagnosis codes, especially prolonged bed rest. Other risk factors, such as the urinary catheter, were probably surrogate markers for immobilization rather than true risk factors. Fourth, we included length of stay in our prediction model. We did this because most randomized trials of VTE prophylaxis included only patients with an expected length of stay 6 days. Physicians' estimates about probable length of stay may be less accurate than actual length of stay as a predictor of VTE. Moreover, the relationship may have been confounded if hospital‐acquired VTE led to longer lengths of stay. We think this unlikely since many of the events were discovered on readmission. Fifth, we studied only patients carrying high‐risk diagnoses, and therefore do not know the baseline risk for patients with less risky conditions, although it should be lower than what we observed. It seems probable that COPD, rather than being protective, as it appears in our model, actually represents the baseline risk for low‐risk diagnoses. It should be noted that we did include a number of other high‐risk diagnoses, such as cancer and inflammatory bowel disease, as secondary diagnoses. A larger, more inclusive study should be conducted to validate our model in other populations. Finally, we cannot know who died of undiagnosed VTE, either in the hospital or after discharge. Such an outcome would be important, but those events are likely to be rare, and VTE prophylaxis has not been shown to affect mortality.

VTE remains a daunting problem in hospitalized medical patients. Although VTE is responsible for a large number of hospital deaths each year, identifying patients at high risk for clinically important VTE is challenging, and may contribute to the persistently low rates of VTE prophylaxis seen in hospitals.25 Current efforts to treat nearly all patients are likely to lead to unnecessary cost, discomfort, and side effects. We present a simple logistic regression model that can easily identify patients at moderate‐to‐high risk (>1%) of developing symptomatic VTE. Future studies should focus on prospectively validating the model in a wider spectrum of medical illness, and better defining the appropriate risk cutoff for general prophylaxis.

Venous thromboembolism (VTE) is a major source of morbidity and mortality for hospitalized patients. Among medical patients at the highest risk, as many as 15% can be expected to develop a VTE during their hospital stay1, 2; however, among general medical patients, the incidence of symptomatic VTE is less than 1%,1 and potentially as low as 0.3%.3 Thromboprophylaxis with subcutaneous heparin reduces the risk of VTE by approximately 50%,4 and is therefore recommended for medical patients at high risk. However, heparin also increases the risk of bleeding and thrombocytopenia and thus should be avoided for patients at low risk of VTE. Consequently, the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) recommends that all hospitalized medical patients receive a risk assessment for VTE.5

Certain disease states, including stroke, acute myocardial infarction, heart failure, respiratory disease, sepsis, and cancer, have been associated with increased risk for VTE, and, based on the inclusion criteria of several randomized trials, current American College of Chest Physicians (ACCP) guidelines recommend thromboprophylaxis for patients hospitalized with these diagnoses.2 However, evidence that these factors actually increase a patient's risk for VTE comes from studies of ambulatory patients and is often weak or conflicting. Existing risk‐stratification tools,6, 7 as well as the ACCP guidelines, have not been validated, and accordingly JCAHO does not specify how risk assessment should be conducted. In order to help clinicians better estimate the risk of VTE in medical patients and therefore to provide more targeted thromboprophylaxis, we examined a large cohort of patients with high‐risk diagnoses and created a risk stratification model.

Methods

Results

Our sample contained 242,738 patients, 194,198 (80%) assigned to the derivation set and 48,540 (20%) to the validation set. Patient characteristics were similar in both sets (Supporting Information Appendix Table 1). Most patients were over age 65, 59% were female, and 64% were white (Table 1). The most common primary diagnoses were pneumonia (33%) and congestive heart failure (19%). The most common comorbidities were hypertension (50%), diabetes (31%), chronic pulmonary disease (30%), and anemia (20%). Most patients were cared for by internists (54%) or family practitioners (21%), and 30% received some form of anticoagulant VTE prophylaxis (Table 2). Of patients with an ICD‐9 code for VTE during hospitalization, just over half lacked either diagnostic testing, treatment, or both, leaving 612 (0.25%) patients who fulfilled our criteria for VTE; an additional 440 (0.18%) were readmitted for VTE, for an overall incidence of 0.43%. Patients with a length of stay 6 days had an incidence of 0.79% vs 0.19% for patients with shorter stays.

Risk factors for VTE

A large number of patient and hospital factors were associated with the development of VTE (Table 1). Due to the large sample size, even weak associations appear highly statistically significant. Compared to patients without VTE, those with VTE were more likely to have received VTE prophylaxis (37% vs 30%, P < 0.001). However, models of patients receiving prophylaxis and of patients not receiving prophylaxis produced similar odds ratios for the various risk factors (Supporting Information Appendix Table 2); therefore, the final model includes both patients who did, and did not, receive VTE prophylaxis. In the multivariable model (Supporting Information Appendix Table 3), age, length of stay, gender, primary diagnosis, cancer, inflammatory bowel disease, obesity, central venous catheter, inherited thrombophilia, steroid use, mechanical ventilation, active chemotherapy, and urinary catheters were all associated with VTE (Table 3). The strongest risk factors were length of stay 6 days (OR 3.22, 95% CI 2.73, 3.79), central venous catheter (OR 1.87, 95% CI 1.52, 2.29), inflammatory bowel disease (OR 3.11, 95% CI 1.59, 6.08), and inherited thrombophilia (OR 4.00, 95% CI 0.98, 16.40). In addition, there were important interactions between age and cancer; cancer was a strong risk factor among younger patients, but is not as strong a risk factor among older patients (OR compared to young patients without cancer was 4.62 (95% CI 2.72, 7.87) for those age 1849 years, and 3.64 (95% CI 2.52, 5.25) for those aged 5064 years).

Table 3.Factors Associated Venous Thromboembolism (VTE) in Multivariable Model

Risk Factor	OR	95% CI
* For patients without cancer. Comparison group is patients aged 18‐49 years without cancer.
Any prophylaxis	0.98	(0.84, 1.14)
Female	0.85	(0.74, 0.98)
Length of stay 6 days	3.22	(2.73, 3.79)
Age*
18‐49 years	1	Referent
50‐64 years	1.15	(0.86, 1.56)
>65 years	1.51	(1.17, 1.96)
Primary diagnosis
Pneumonia	1	Referent
Chronic obstructive pulmonary disease	0.57	(0.44, 0.75)
Stroke	0.84	(0.66, 1.08)
Congestive heart failure	0.86	(0.70, 1.06)
Urinary tract infection	1.19	(0.95, 1.50)
Respiratory failure	1.15	(0.85, 1.55)
Septicemia	1.11	(0.82, 1.50)
Comorbidities
Inflammatory bowel disease	3.11	(1.59, 6.08)
Obesity	1.28	(0.99, 1.66)
Inherited thrombophilia	4.00	(0.98, 16.40)
Cancer
18‐49 years	4.62	(2.72, 7.87)
50‐64 years	3.64	(2.52, 5.25)
>65 years	2.17	(1.61, 2.92)
Treatments
Central venous catheter	1.87	(1.52, 2.29)
Mechanical ventilation	1.61	(1.27, 2.05)
Urinary catheter	1.17	(0.99, 1.38)
Chemotherapy	1.71	(1.03, 2.83)
Steroids	1.22	(1.04, 1.43)

In the derivation set, the multivariable model produced deciles of mean predicted risk from 0.11% to 1.45%, while mean observed risk over the same deciles ranged from 0.12% to 1.42% (Figure 1). Within the validation cohort, the observed rate of VTE was 0.46% (223 cases among 48,543 subjects). The expected rate according to the model was 0.43% (expected/observed ratio: 0.93 [95% CI 0.82, 1.06]). Model discrimination measured by the c‐statistic in the validation set was 0.75 (95% CI 0.71, 0.78). The model produced deciles of mean predicted risk from 0.11% to 1.46%, with mean observed risk over the same deciles from 0.17% to 1.81%. Risk gradient was relatively flat across the first 6 deciles, began to rise at the seventh decile, and rose sharply in the highest one. Using a risk threshold of 1%, the model had a sensitivity of 28% and a specificity of 93%. In the validation set, this translated into a positive predictive value of 2.2% and a negative predictive value of 99.7%. Assuming that VTE prophylaxis has an efficacy of 50%, the number‐needed‐to‐treat to prevent one VTE among high‐risk patients (predicted risk >1%) would be 91. In contrast, providing prophylaxis to the entire validation sample would result in a number‐needed‐to‐treat of 435. Using a lower treatment threshold of 0.4% produced a positive predictive value of 1% and a negative predictive value of 99.8%. At this threshold, the model would detect 73% of patients with VTE and the number‐needed‐to‐treat to prevent one VTE would be 200.

Figure 1

Discussion

In a representative sample of 243,000 hospitalized medical patients with at least one major risk factor for VTE, we found that symptomatic VTE was an uncommon event, occurring in approximately 1 in 231 patients. We identified a number of factors that were associated with an increased risk of VTE, but many previously cited risk factors did not show an association in multivariable models. In particular, patients with a primary diagnosis of COPD appeared not to share the same high risk of VTE as patients with the other diagnoses we examined, a finding reported by others.11 The risk model we developed accurately stratifies patients across a wide range of VTE probabilities, but even among those with the highest predicted rates, symptomatic VTE occurred in less than 2%.

VTE is often described as a frequent complication of hospitalization for medical illness and one of the most common potentially preventable causes of death. Indeed, rates of asymptomatic VTE have been demonstrated to be 3.7% to 26%.12 Although some of these might have fatal consequences, most are distal vein thromboses and their significance is unknown. In contrast, symptomatic events are uncommon, with previous estimates among general medical patients in observational studies in the range of 0.3%3 to 0.8%,12 similar to the rate observed in our study. Symptomatic event rates among control patients in landmark randomized trials have ranged from 0.86%13 to 2.3%,14 but these studies enrolled only very high‐risk patients with more extended hospitalizations, and may involve follow‐up periods of a month or more.

Because it is unlikely that our diagnostic algorithm was 100% sensitive, and because 30% of our patients received chemoprophylaxis, it is probable that we have underestimated the true rate of VTE in our sample. Among the patients who received prophylaxis, the observed rate of VTE was 0.54%. If we assume that prophylaxis is 50% effective, then had these patients not received prophylaxis, their rate of VTE would have been 1.08% (vs 0.39% among those patients who received no prophylaxis) and the overall rate of VTE for the sample would have been 0.60% (1.08 0.30 + 0.39 0.70). If we further assume that our algorithm was only 80% sensitive and 100% specific, the true underlying rate of symptomatic VTE could have been as high as 0.75%, still less than half that seen in randomized trials.

Prophylaxis with heparin has been shown to decrease the rate of both asymptomatic and symptomatic events, but because of the low prevalence, the number‐needed‐to‐treat to prevent one symptomatic pulmonary embolism has been estimated at 345, and prophylaxis has not been shown to affect all‐cause mortality.4, 15 At the same time, prophylaxis costs money, is uncomfortable, and carries a small risk of bleeding and heparin‐induced thrombocytopenia. Given the generally low incidence of symptomatic VTE, it therefore makes sense to reserve prophylaxis for patients at higher risk of thromboembolism.

To decide whether prophylaxis is appropriate for a given patient, it is necessary to quantify the patient's risk and then apply an appropriate threshold for treatment. The National Quality Forum (NQF) recommends,16 and JCAHO has adopted, that a clinician must evaluate each patient upon admission, and regularly thereafter, for the risk of developing DVT [deep vein thrombosis]/VTE. Until now, however, there has been no widely accepted, validated method to risk stratify medical patients. The ACCP recommendations cite just three studies of VTE risk factors in hospitalized medical patients.11, 17, 18 Together they examined 477 cases and 1197 controls, identifying congestive heart failure, pneumonia, cancer, and previous VTE as risk factors. Predictive models based on these factors17, 1921 have not been subjected to validation or have performed poorly.18 Acknowledging this lack of standardized risk assessment, JCAHO leaves the means of assessment to individual hospitals. A quality improvement guide published by the Agency for Healthcare Research and Quality goes one step further, stating that In a typical hospital, it is estimated that fewer than 5% of medical patients could be considered at low risk by most VTE risk stratification methods.22 The guide recommends near universal VTE prophylaxis.

In light of the JCAHO requirements, our model should be welcomed by hospitalists. Rather than assuming that all patients over 40 years of age are at high risk, our model will enable clinicians to risk stratify patients from a low of 0.1% to >1.4% (>10‐fold increase in risk). Moreover, the model was derived from more than 800 episodes of symptomatic VTE among almost 190,000 general medical patients and validated on almost 50,000 more. The observed patients were cared for in clinical practice at a nationally representative group of US hospitals, not in a highly selected clinical trial, increasing the generalizability of our findings. Finally, the model includes ten common risk factors that can easily be entered into decision support software or extracted automatically from the electronic medical record. Electronic reminder systems have already been shown to increase use of VTE prophylaxis, and prevent VTE, especially among cancer patients.23

A more challenging task is defining the appropriate risk threshold to initiate VTE prophylaxis. The Thromboembolic Risk Factors (THRIFT) Consensus Group classified patients according to risk of proximal DVT as low (<1%), moderate (1%‐10%), and high (>10%).21 They recommended heparin prophylaxis for all patients at moderate risk or higher. Although the patients included in our study all had a diagnosis that warranted prophylaxis according to the ACCP guidelines, using the THRIFT threshold for moderate‐to‐high risk, only 7% of our patients should have received prophylaxis. The recommendation not to offer heparin prophylaxis to patients with less than 1% chance of developing symptomatic VTE seems reasonable, given the large number‐needed‐to‐treat, but formal decision analyses should be conducted to better define this threshold. Many hospitalists, however, may feel uncomfortable using the 1% threshold, because our model failed to identify almost three out of four patients who ultimately experienced symptomatic VTE. At that threshold, it would seem that hospital‐acquired VTE is not a preventable complication in most medical patients, as others have pointed out.3, 24 Alternatively, if the threshold were lowered to 0.4%, our model could reduce the use of prophylaxis by 60%, while still identifying three‐fourths of all VTE cases. Further research is needed to know whether such a threshold is reasonable.

Our study has a number of important limitations. First, we relied on claims data, not chart review. We do not know for certain which patients experienced VTE, although our definition of VTE required diagnosis codes plus charges for both diagnosis and treatment. Moreover, our rates are similar to those observed in other trials where symptomatic events were confirmed. Second, about 30% of our patients received at least some VTE prophylaxis, and this may have prevented as many as half of the VTEs in that group. Without prophylaxis, rates might have been 20%30% higher. Similarly, we could not detect patients who were diagnosed after discharge but not admitted to hospital. While we believe this number to be small, it would again increase the rate slightly. Third, we could not assess certain clinical circumstances that are not associated with hospital charges or diagnosis codes, especially prolonged bed rest. Other risk factors, such as the urinary catheter, were probably surrogate markers for immobilization rather than true risk factors. Fourth, we included length of stay in our prediction model. We did this because most randomized trials of VTE prophylaxis included only patients with an expected length of stay 6 days. Physicians' estimates about probable length of stay may be less accurate than actual length of stay as a predictor of VTE. Moreover, the relationship may have been confounded if hospital‐acquired VTE led to longer lengths of stay. We think this unlikely since many of the events were discovered on readmission. Fifth, we studied only patients carrying high‐risk diagnoses, and therefore do not know the baseline risk for patients with less risky conditions, although it should be lower than what we observed. It seems probable that COPD, rather than being protective, as it appears in our model, actually represents the baseline risk for low‐risk diagnoses. It should be noted that we did include a number of other high‐risk diagnoses, such as cancer and inflammatory bowel disease, as secondary diagnoses. A larger, more inclusive study should be conducted to validate our model in other populations. Finally, we cannot know who died of undiagnosed VTE, either in the hospital or after discharge. Such an outcome would be important, but those events are likely to be rare, and VTE prophylaxis has not been shown to affect mortality.

VTE remains a daunting problem in hospitalized medical patients. Although VTE is responsible for a large number of hospital deaths each year, identifying patients at high risk for clinically important VTE is challenging, and may contribute to the persistently low rates of VTE prophylaxis seen in hospitals.25 Current efforts to treat nearly all patients are likely to lead to unnecessary cost, discomfort, and side effects. We present a simple logistic regression model that can easily identify patients at moderate‐to‐high risk (>1%) of developing symptomatic VTE. Future studies should focus on prospectively validating the model in a wider spectrum of medical illness, and better defining the appropriate risk cutoff for general prophylaxis.