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Impact of Disease Etiology and Indication for Colectomy on Postoperative Outcomes: NSQIP Colectomy-Targeted Database
Sourav K Podder1, Allison Doermann1, George Ibrahim1
1From the Department of Surgery, Thomas Jefferson University Hospital, Philadelphia, PA (Podder, Doermann, Ibrahim, Koeneman, Schleider, Shindle, Cowan, Yeo, Hanna).
Background:
The American College of Surgeons (ACS) NSQIP Colectomy-Targeted database provides valuable metrics on surgical outcomes by using clinical data to enhance quality improvement efforts. However, the quality measures offered in the ACS NSQIP semiannual report do not stratify for the indication of colectomy. We aim to compare postoperative outcomes in patients undergoing colectomy for colon cancer, infectious causes, and inflammatory bowel disease (IBD).
Study Design:
A retrospective review of patients undergoing colectomy was performed using the ACS NSQIP Colectomy-Targeted database from 2012 to 2022. Logistic regression models were used to compare the 30-day postoperative outcomes of patients who underwent colectomy for colon cancer, infectious causes, and IBD while adjusting for preoperative risk factors.
Results:
There were 158,560 patients who underwent colectomy for colon cancer, 90,827 patients for infectious causes, and 30,548 patients for IBD. In unadjusted analysis, patients undergoing colectomy for infectious causes had the highest rates of mortality (2.6%) and morbidity (27.6%). After adjusting for covariates, patients with IBD undergoing colectomy had significantly higher odds of morbidity compared to those undergoing colectomy for colon cancer (odds ratio 1.3, 95% CI [1.1 to 1.4]) and infectious causes (odds ratio 1.3 [1.2 to 1.4]). Patients with IBD had significantly higher odds of experiencing venous thromboembolism, surgical site infections, prolonged ileus, and readmission within 30 days compared to both colon cancer and infectious causes patients.
Conclusions:
This study demonstrates that the indication for colectomy impacts postoperative outcomes. Reporting risk-adjusted outcomes based on the underlying disease etiology could lead to identifying high-risk patients, improving benchmarking outcomes, and developing targeted quality initiatives.
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