DOI: 10.60118/001c.68116 ISSN:

Risk Factors for Unexpected Hospital Admission Following Achilles Tendon Repair: A National Database Study

John M. Tarazi, Matthew J. Partan, Areil Aminov, Alain E. Sherman, Adam D. Bitterman, Randy M. Cohn


Achilles tendon rupture (ATR) repair is one of the most common orthopaedic surgeries performed in the United States, however there is a paucity of literature on predisposing risk factors for hospital readmissions. The purpose of this study is to identify risk factors for 30-day readmission in patients undergoing ATR repair with emphasis on procedures performed in the outpatient setting. Specifically, we examine: 1) 30-day post-operative hospital readmission rates; 2) the medical comorbidities and patient characteristics that predisposed this cohort to post-operative complications; and 3) the complications leading to readmission. 


The ACS-NSQIP was queried for patients who underwent ATR from 2015 to 2019 using CPT code 27650 in all fields yielding a sample size of 3,887 cases. The following demographic, lifestyle, and comorbidity variables were recorded: age, sex, race, BMI, morbid obesity (BMI ≥ 40.00 kg/m2), bleeding disorders, chronic obstructive pulmonary disease (COPD), diabetes mellitus, hypertension, tobacco use, and chronic steroid use. The primary outcome of 30-day readmission was defined as unplanned hospital readmission likely related to the principal procedure. Independent samples Student’s t-tests, chi-squared, and, where appropriate, Fisher’s exact tests were used in univariate analyses to identify demographic, lifestyle, and peri-operative variables related to 30-day readmission following ATR. Multivariate logistic regression modeling was subsequently performed. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated and reported.


Of the 3,887 patients included in our sample, 28 were readmitted within the 30-day post-operative period, corresponding to a readmission rate of 0.73%. Significant relationships with univariate analyses between readmission status and the following patient variables included: mean patient age (p = 0.02); hypertension (p < 0.001); BMI (p = 0.01); morbid obesity (p = 0.002); ASA Classification (p = 0.006); and bleeding disorders (p = 0.03). Multivariate logistic regression modeling confirmed that the following patient variables were associated with statistically significantly increased odds of readmission: age, p = 0.02), OR = 1.03, 95% CI [1.01, 1.06]; hypertension, p < 0.001, OR = 3.82, 95% CI [1.81, 8.06]; BMI, p = 0.01, OR = 1.06, 95% CI [1.01, 1.11]; morbid obesity, p = 0.004, OR = 3.53, 95% CI [1.49, 8.36].


Our study indicated that only 0.73% of patients were readmitted after their outpatient procedure. Patients who: 1) have BMIs greater than 40; 2) are older in age 3) have hypertension; and 4) a higher ASA Classification were at increased risk for readmission.

More from our Archive