Predictors of surgical site infection after hospital discharge in patients undergoing major vascular surgery

Abstract

Objective: Surgical site infection (SSI) is one of the most common postoperative complications after vascular reconstruction, producing significant morbidity and hospital readmission. In contrast to SSI that develops while patients are still hospitalized, little is known about the cohort of patients who develop SSI after discharge. In this study, we explore the factors that lead to postdischarge SSI, investigate the differences between risk factors for in-hospital vs postdischarge SSI, and develop a scoring system to identify patients who might benefit from postdischarge monitoring of their wounds.

Methods: Patients who underwent major vascular surgery from 2005 to 2012 for aneurysm and lower extremity occlusive disease were identified from the American College of Surgeons National Surgical Quality Improvement Program Participant Use Files. Patients were categorized as having no SSI, in-hospital SSI, or SSI after hospital discharge. Predictors of postdischarge SSI were determined by multivariable logistic regression and internally validated by bootstrap resampling. Risk scores were assigned to all significant variables in the model. Summative risk scores were collapsed into quartile-based ordinal categories and defined as low, low/moderate, moderate/high, and high risk. Multivariable logistic regression was used to determine predictors of in-hospital SSI.

Results: Of the 49,817 patients who underwent major vascular surgery, 4449 (8.9%) were diagnosed with SSI (2.1% in-hospital SSI; 6.9% postdischarge SSI). By multivariable analysis, factors significantly associated with increased odds of postdischarge SSI include female gender, obesity, diabetes, smoking, hypertension, coronary artery disease, critical limb ischemia, chronic obstructive pulmonary disease, dyspnea, neurologic disease, prolonged operative time >4 hours, American Society of Anesthesiology class 4 or 5, lower extremity revascularization or aortoiliac procedure, and groin anastomosis. The model exhibited moderate discrimination (bias-corrected C statistic, 0.691) and excellent internal calibration. The postdischarge SSI rate was 2.1% for low-risk patients, 5.1% for low/moderate-risk patients, 7.8% for moderate/high-risk patients, and 14% for high-risk patients. In a comparative analysis, comorbidities were the primary driver of postdischarge SSI, whereas in-hospital factors (operative time, emergency case status) and complications predicted in-hospital SSI.

Conclusions: The majority of SSIs after major vascular surgery develop following hospital discharge. We have created a scoring system that can select a cohort of patients at high risk for SSI after discharge. These patients can be targeted for transitional care efforts focused on early detection and treatment with the goal of reducing morbidity and preventing readmission secondary to SSI.

Conflict of interest statement

Conflicts of Interest: The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1. Distribution of the number of days from major vascular surgery procedure to diagnosis of SSI for all patients diagnosed with SSI

A diagnosis occurring while in-hospital is represented in green; a diagnosis occurring after hospital discharge is represented in yellow. SSI, Surgical site infection

Figure 2

The receiver operator curve (ROC) of the final model.

Figure 3. Predicted probability of post-discharge surgical site infection by total point score

SSI, Surgical site infection