Variables that predict hospital stay and the outcome of Fournier gangrene at King Abdulaziz University Hospital: a retrospective study

Abstract

Background The aggressive nature of Fournier gangrene and the associated health issues can result in a more complex clinical course and potentially a longer hospital stay. This study aimed to assess factors that affect the length of hospital stay (LHS) and its relation to the outcome of Fournier gangrene patients. Methods A retrospective study was performed at King Abdulaziz University Hospital (KAUH), Saudi Arabia, on patients diagnosed with Fournier gangrene between 2017 and 2023. Data about length of hospital stay (LHS), age, BMI, clinical and surgical data and outcome was obtained. Results The mean age of the studied patients was 59.23 ± 11.19 years, the mean body mass index (BMI) was 26.69 ± 7.99 kg/m2, and the mean duration of symptoms was 10.27 ± 9.16 days. The most common presenting symptoms were swelling or induration (64%), 88% had comorbidities with diabetes mellitus (DM) (84%), and 76% had uncontrolled DM. of patients, 24% had a poly-microbial infection, with E. coli being the most common (52%). The mean length of hospital stay (LHS) was 54.56 ± 54.57 days, and 24% of patients had an LHS of more than 50 days. Longer LHS (> 50 days) was associated with patients who did not receive a compatible initial antibiotic, whereas shorter LHS was associated with patients who received Impenem or a combination of vancomycin and meropenem as alternative antibiotics following incompatibility. Reconstruction patients had significantly longer LHS and a higher mean temperature. However, none of the studied variables were found to be predictors of long LHS in the multivariate regression analysis. Conclusion Knowledge of the values that predict LHS allows for patient-centered treatment and may be useful in predicting more radical treatments or the need for additional treatment in high-risk patients. Future multicenter prospective studies with larger sample sizes are needed to assess the needed variables and predictors of long LHS.