Original Research

Risk Factors for In-Hospital Myocardial Infarction After Shoulder Arthroplasty

Am J Orthop. 2015 May;44(5):E142-E147

As cardiovascular complications are associated with significant morbidity and mortality in patients who have arthroplasty, it is important to analyze risk factors for perioperative cardiac morbidity after shoulder arthroplasty.

Using the Nationwide Inpatient Sample, we stratified patients who underwent shoulder arthroplasty into those who had an acute myocardial infarction after arthroplasty and a larger cohort of patients who did not. The top 4 predictors for acute myocardial infarction after shoulder arthroplasty were congestive heart failure, angina pectoris, complicated diabetes mellitus, and male sex. Other pertinent factors were older age, Caucasian ethnicity, and primary diagnosis of proximal humerus fracture.

It is prudent for surgeons and patients to understand the degree to which perioperative cardiac morbidity affects surgical recovery.

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References

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The incidence of shoulder arthroplasty in the United States is increasing annually,^1-3 and the majority of these operations occur in older patients.^4-6 Elderly patients with cardiovascular, pulmonary, cerebral, renal, and hepatic disease are increasingly susceptible to numerous surgical complications.⁴ Myocardial infarction (MI) is a complication that occurs in 0.7% of noncardiac surgeries. This figure increases to 1.1% in patients with coronary artery disease.^7-11 Perioperative MI increases morbidity and mortality,⁸ and perioperative cardiac morbidity is the leading cause of death after anesthesia and surgery.¹² The financial effects of perioperative cardiac morbidity and mortality must also be considered. A 2009 claims analysis study estimated charges associated with a perioperative MI at $15,000 and the cost of cardiac death at $21,909.¹³

Cardiovascular complications are associated with a significant degree of morbidity and mortality in patients who undergo arthroplasty.^14-16 Although studies have elucidated 30- and 90-day morbidity and mortality rates after shoulder arthroplasty, in hip and knee arthroplasty^17-19little has been done to determine predictors of perioperative MI in a representative database of patients. Given the increasing incidence of shoulder arthroplasty in the United States, the elective nature of this procedure, and the percentage of the US population with cardiovascular risk factors,²⁰ it is important to establish predictors of perioperative MI to ensure patients and physicians have the necessary resources to make informed decisions.

We conducted a study to examine the risk factors for perioperative MI in a large cohort of patients admitted for shoulder arthroplasty to US hospitals. We wanted to evaluate the association between perioperative MI and shoulder arthroplasty with respect to demographics, primary diagnosis, medical comorbidities, and perioperative complications. Specifically, we tested the null hypothesis that, among patients undergoing shoulder arthroplasty, and accounting for confounding variables, there would be no difference in risk factors for patients who have a perioperative MI.

Materials and Methods

This study was exempt from approval by our institutional review board. All data used in this project were deidentified before use.

Nationwide Inpatient Sample (NIS)

The Nationwide Inpatient Sample (NIS), an annual survey of hospitals, is conducted by the Healthcare Cost and Utilization Project (HCUP) and sponsored by the Agency for Healthcare Research and Quality (AHRQ). This database is the largest publicly available all-payer inpatient discharge database in the United States.²¹ Sampling 8 million hospital stays each year, NIS includes information from a representative batch of 20% of US hospitals. In 2011, 46 states and 1045 hospitals contributed information to the database, representing 97% of the US population.²² This large sample allows researchers to analyze a robust set of medical conditions and uncommon treatments. The survey, conducted each year since 1988, includes demographic, clinical, and resource use data.²³ Discharge weight files are provided by NIS to arrive at valid national estimates.

This database is particularly useful because it provides information on up to 25 medical diagnoses and 15 procedures, which are recorded with International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. Researchers can use this database to analyze patient and hospital characteristics as well as inpatient outcomes.^24,25 Numerous studies have used NIS to address pertinent queries across the medical landscape.^22,26

Patient Selection and Analysis

We used NIS to isolate a population of 422,371 adults (≥18 years old) who underwent total shoulder arthroplasty (TSA) or hemi–shoulder arthroplasty (HSA) between January 1, 2002 and December 31, 2011. We then placed the patients in this population into 1 of 2 cohorts. The first cohort had an acute MI during the perioperative period after TSA, and the second, larger cohort did not have an acute MI after TSA. Acute MI was identified using ICD-9-CM code 410.xx. To identify a population of shoulder arthroplasty patients, we included discharges with an ICD-9-CM procedure code of 81.80 or 81.88 (both TSA) or 81.81 (HSA) in the sample. We then considered the degree to which each of 5 variables—primary diagnosis, age, sex, race, and select medical comorbidities—was predictive of in-hospital MI after TSA.

Statistical Analysis

Given the large sample used in this study, normal distribution of data was assumed. Using bivariate analysis, Pearson χ² test for categorical data, and independent-samples t test for continuous data, we compared the nonacute MI and acute MI groups. Multivariable binary logistic regression analyses allowed us to isolate the extent that primary diagnosis, age, sex, race, and medical comorbidities were predictors of acute MI after shoulder arthroplasty. Statistical significance was set at P < .05. SPSS Version 22.0 (SPSS, Chicago, Illinois) was used for all statistical analyses and data modeling.