15.15 The Predictive Value of Baseline Creatinine in Abdominal Wall Reconstruction

C. Davis1, C. Boyd1, J. Wilson1, J. I. De La Torre1  1University Of Alabama at Birmingham,Plastic Surgery,Birmingham, Alabama, USA

Introduction:  Abdominal wall reconstruction (AWR) is an invasive surgical procedure that can result in lengthy hospital stay for patients with certain comorbidities. Postoperative kidney injury is a well described complication in other surgeries.  This study investigates baseline preoperative creatinine and its correlation to hospital length of stay (LOS) as well as acute kidney injury (AKI) after AWR.

Methods:  A retrospective analysis of patients who underwent AWR from a single surgeon at University of Alabama at Birmingham over January 2017-July 2018. Statistical analysis of patients’ charts was compared for baseline creatinine, AKI, LOS, and postoperative complications.  All patient who underwent component separation with acellular dermal reinforcement for ventral hernias during the study period were included.  Patients who did not require the use of biologic acellular dermal matrix were excluded.  Statistical analysis included t-tests and regression analysis.

Results: 52 patients underwent AWR during the respective time frame. Average age of patients was 56, and the majority of patients were female (73.1%).  Of these patients, 11 had a baseline creatinine of ≥1.  Individuals with baseline creatinine ≥1 had a longer length of stay (6.55 days) compared to patients with a baseline Cr < 1 (5.1 days) (p=0.25).   Including all 52 patients into the analysis, baseline creatinine was not significantly correlated to LOS.  Postoperative AKI was associated with a significantly longer LOS compared to patients who did not have a postoperative AKI (9.08 vs 4.14 days, p=0.03012).

Conclusion: Although baseline creatinine alone was not predictive of length of stay, baseline creatinine levels ≥1 correlated to longer length of stay in this patient group. Furthermore, AKI was also predictive of longer hospital courses. These factors can help forecast hospital courses in patients at risk based on their comorbidities and allow physicians to prevent and treat possible complications to reduce LOS and optimize patient health.