Comparative Study
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Predictors of readmission after laparoscopic gastric bypass and sleeve gastrectomy: a comparative analysis of ACS-NSQIP database.

BACKGROUND: Readmission rate is an indicator of quality in surgical practice. We aimed to determine the predictors of unplanned early readmissions following stapling bariatric surgeries.

METHODS: From the American College of Surgeons National Surgical Quality Improvement Program database, we identified morbidly obese patients, who underwent either laparoscopic sleeve gastrectomy (LSG) or laparoscopic Roux-en-Y gastric bypass (LRYGB) in 2012 and 2013. Demographic, comorbidities, operative and postoperative parameters of the readmitted (within 30 days) and non-readmitted patients were evaluated using a multivariate logistic regression analysis.

RESULTS: A total of 35,655 patients (17,101 LSG and 18,554 LRYGB) were analyzed. Of those, 1758 patients (4.9 %) were readmitted within 30 days of surgery. Multivariate analysis showed the following significant predictors for readmission: Non-Hispanic black ethnicity (OR: 1.56, 95 % CI:1.34-1.81), Hispanic ethnicity (OR: 1.29, 95 % CI:1.05-1.58), totally or partially dependent functional status (OR: 1.94, 95 % CI:1.06-3.55), higher preoperative creatinine (OR: 1.13, 95 % CI:1.04-1.22), lower serum albumin (OR: 0.78, 95 % CI:0.68-0.90), diabetes mellitus on insulin (OR: 1.28, 95 % CI:1.09-1.51), steroid or immunosuppressant use for a chronic condition (OR: 1.61, 95 % CI:1.11-2.33), history of cardiac disease with intervention (OR: 2.05, 95 % CI:1.10-3.83), bleeding disorders (OR: 1.71, 95 % CI:1.15-2.54), LRYGB versus LSG (OR: 1.63, 95 % CI:1.44-1.85), longer operative time (OR: 1.13, 95 % CI:1.07-1.20), concurrent splenectomy (OR: 4.10, 95 % CI:1.05-16.01), and occurrence of any postoperative complication during index admission (OR: 2.61, 95 % CI:1.99-3.42).

CONCLUSIONS: Ethnicity, baseline functional status, comorbidities, type and duration of surgical procedure, and postoperative complications occurred in the index admission can predict risk of early readmission following LRYGB and LSG.

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