Şimşek Index (Kocaeli Fournier’s Gangrene Severity Index, KFGSI): Development and Prognostic Performance of an Admission-Based Mortality Prediction Model for Fournier’s Gangrene

backgroundFournier's gangrene (FG) is an aggressive form of necrotizing fasciitis associated with high mortality despite advances in critical care and surgical management. Early identification of high-risk patients is essential to enable timely intervention. This study aimed to evaluate established prognostic indices and to develop a novel model for mortality prediction.

methodsWe retrospectively reviewed the medical records of 69 patients diagnosed with FG and treated at the General Surgery Clinic of Kocaeli University Hospital between January 2017 and January 2022. Demographic, clinical, laboratory, radiological, and treatment-related data were collected. Disease severity was assessed using the Fournier's Gangrene Severity Index (FGSI), Uludağ FGSI (UFGSI), and the American Society of Anesthesiologists (ASA) score. The UFGSI was calculated by combining the FGSI physiological score with additional age and dissemination scores derived from radiological extent grading. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to identify independent predictors of mortality and to develop the Kocaeli Fournier Gangrene Severity Index (KFGSI).

resultsThe mean age was 58.6±13.5 years (range: 36-89), with 52 (75.4%) males and 17 (24.6%) females. The overall in-hospital mortality rate was 40.6% (n=28). On univariate analysis, admission parameters significantly associated with mortality included pulse rate, respiratory rate, body mass index (BMI), serum lactate level, radiological extent grade, body temperature, and FGSI score (all p<0.05). Intensive care unit (ICU) length of stay was also associated with mortality in exploratory analyses, reflecting the downstream clinical course. ROC analysis demonstrated strong prognostic performance for pulse rate (area under the curve [AUC] 0.935; 95% confidence interval [CI] 0.848-0.980) and radiological extent grade (AUC 0.898; 95% CI 0.797-0.966), as illustrated in Figure 1. The UFGSI also showed good discrimination (AUC 0.858; 95% CI 0.748-0.967), with 96.4% sensitivity and 73.2% specificity at the Youdenderived cut-off (≥10). The newly developed admission-based KFGSI, incorporating five admission parameters (pulse rate, respiratory rate, body mass index, serum lactate level, and radiological extent grade), demonstrated superior discrimination compared with FGSI in this derivation cohort (AUC 0.943; 95% CI 0.860-0.985; sensitivity 92.9%; specificity 85.4% vs. FGSI AUC 0.860; 95% CI 0.755- 0.932). ICU length of stay was not included in the admission-based KFGSI model.

conclusionThe KFGSI demonstrated excellent prognostic accuracy for mortality prediction in FG and outperformed FGSI in this derivation cohort. However, external validation in multicenter populations is required. Early application of the KFGSI may enhance clinical risk stratification and support timely decision-making regarding triage and management. Prospective multicenter studies are needed to confirm its validity and establish its clinical utility.