Patient and operative characteristics of readmission and poly-readmission following metabolic surgery: an MBSAQIP analysis (2015-2021).

Background: Recently, same-day Metabolic Surgery (MS) has gained traction, especially to reduce costs and hospital resource utilization. While shorter hospital stays are desirable, accelerated discharge could increase postoperative burden for those patients at risk. This study evaluated whether specific patient characteristics are associated with increased 30-day readmission rates and number of readmissions as a potentially identifying those less suited for same-day discharge.

Methods: Using the MBSAQIP (2015-2021), 960,757 cases of primary minimally invasive sleeve gastrectomy (SG), Roux-en-Y gastric bypass (RYGB), and duodenal switch (DS) were included. Readmission characteristics were extracted from ancillary Participant Use Files (PUF) and linked to the main MBSAQIP data. Zero-inflated Poisson (ZIP) models assessed associations between preoperative patient characteristics and readmission risk. The two-stage models analyzed odds of any 30-day readmission and calculated the relative risk (RR) of multiple readmissions.

Results: Several key predictors of single as well as multiple readmissions in the first 30 days following intervention were noted. Black or Hispanic race, BMI, diabetes, COPD, GERD, and therapeutic anticoagulation were associated with increased odds of readmission likelihood after MS. Black race and GERD predicted increased readmission frequency (multiple readmissions) among all readmission cases, while those aged ≥ 40 years and Hispanic race were less likely to require multiple readmissions.

Conclusion: This large-scale MS analysis highlights patient characteristics that should be carefully considered by MS providers during patient counseling and consideration of same-day discharge. Readmission poses significant financial, physiological, and psychological burdens emphasizing the need for careful patient evaluation and counseling, particularly for those at higher risk, to optimize patient outcomes in the context of accelerated discharge protocols.