Is there a need for the Fournier's gangrene severity index? Comparison of scoring systems for outcome prediction in patients with Fournier's gangrene

BJU Int. 2012 Nov;110(9):1359-65. doi: 10.1111/j.1464-410X.2012.11082.x. Epub 2012 Apr 11.

Abstract

Study Type - Prognosis (prospective cohort) Level of Evidence 2a. What's known on the subject? and What does the study add? Fournier's gangrene (FG) is a rare but life-threatening disease challenging the treating medical staff. Despite the fact that antibiotic therapy combined with surgery and intensive care surveillance are performed as standard treatment, mortality rates remain high. There have been efforts to develop a reliable tool to predict severity of the disease, not only to identify patients at highest risk of major complications or death but also to provide a target for medical teams and researchers aiming to improve outcome and to gather information for counselling patients. Laor et al. published the FG severity index (FGSI) in 1995 presenting a complex prediction score solely for patients with FG. Fifteen years later, Yilmazlar et al. suggested a new and supposedly more powerful scoring system, the Uludag FGSI (UFGSI), adding an age score and an extent of disease score to the FGSI. In the present study population we applied two scoring systems for outcome prediction that are solitarily applicable in patients with FG (FGSI, UFGSI), as well as two general scoring systems such as the established age-adjusted Charlson Comorbidity Index (ACCI) and the recently introduced surgical Apgar Score (sAPGAR) to compare them and to test whether one system might be superior to the other. In addition, we identified potential prognostic factors in the study population. By contrast to many earlier studies, we performed a combined prospective and retrospective analysis and provided a 30-day follow up. In the cohort of the present study, older patients with comorbidities as well as a need for mechanical ventilation and blood transfusion are at higher risk of lethal outcome. All scores are useful to predict mortality. Despite including more variables, the UFGSI does not seem to be more powerful than the FGSI. In daily routine we suggest applying ACCI and sAPGAR, as they are more easily calculated, generally applicable and well validated.

Objective: • To compare four published scoring systems for outcome prediction (Fournier's gangrene severity index [FGSI], Uludag FGSI [UFGSI], age-adjusted Charlson Comorbidity Index [ACCI] and surgical Apgar Score [sAPGAR]) and evaluate risk factors in patients with Fournier's gangrene (FG).

Patients and methods: • In all, 44 patients were analysed. The scores were applied. • A Mann-Whitney U-test, Fisher's exact test, receiver operator characteristic (ROC) analysis and Pearson correlation analysis were performed.

Results: • The results of the present study show a significant association among FGSI (P= 0.002), UFGSI (P= 0.002), ACCI (P= 0.004), sAPGAR (P= 0.018) and death. • The differences between the area under the receiver operating characteristic curve of the scores were not significant. • Non-survivors were older (P= 0.046), had a greater incidence of acute renal failure (P < 0.001) and coagulopathy (P= 0.041), were treated more often with mechanical ventilation (P= 0.001) and received more packed red blood cells (RBCs; P= 0.001).

Conclusion: • Older patients with comorbidities and need for mechanical ventilation and RBCs are at higher risk for death. • In the present cohort, scores calculated easily at the bedside, such as ACCI and sAPGAR, seemed to be as good at predicting outcome in patients with FG as FGSI and UFGSI.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Fournier Gangrene / complications
  • Fournier Gangrene / mortality*
  • Fournier Gangrene / surgery
  • Genital Diseases, Male / complications
  • Genital Diseases, Male / mortality*
  • Genital Diseases, Male / surgery
  • Humans
  • Male
  • Middle Aged
  • Prospective Studies
  • ROC Curve
  • Retrospective Studies
  • Severity of Illness Index*