Stesura Seveso Archivio Italiano di Urologia e Andrologia 2024; 96(2):12387 1 ORIGINAL PAPER Fournier’s Gangrene Severity Index (SFGSI), Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC), Neutrophil-to- lymphocyte Ratio (NLR), and Platelet-to-lymphocyte Ratio (PLR), have been formulated to estimate the mortality risk in FG patients (2-6). These predictive instruments are invaluable for healthcare professionals, especially urolo- gists and surgeons, as they enable the initiation of more aggressive interventions at an early stage. Some of these indicators, engineered for ease of use and practicality, rely solely on laboratory data (SFGSI, LRINEC, NLR, and PLR), while others are more sophisticated, amalgamating both laboratory and clinical data (FGSI and UFGSI). In the quest for an indicator that harmonizes precision and sim- plicity, a comparative evaluation of these indicators is indispensable. However, the sensitivity and specificity of these scoring systems remain undetermined. This study seeks to assess the efficacy of FGSI, UFGSI, SFGSI, LRINEC, NLR, and PLR at the point of admission in fore- casting mortality outcomes in FG patients. MATERIALS AND METHODS A retrospective cross-sectional study from January 2014 to December 2020 was conducted following approval from the Hospital Review Board (No. 0528/LOE/301.4.2/VII/ 2021). The study included all patients with FG admitted to Dr. Soetomo Hospital. Patient data was retrieved from the hospital's electronic medical records system. All partici- pants provided written informed consent for the use of their clinical information for research purposes. The study included patients diagnosed with FG by a urologist, excluding those with incomplete data. Scoring was done at admission, reflecting the emergency assessment when the patient arrived at the hospital. If a patient had test results from another healthcare institu- tion, these tests were repeated. The data examined included demographics (age, sex, eti- ology, comorbidities, and wound culture results) and parameters (FGSI, UFGSI, SFGSI, LRINEC, PLR, and NLR). Participants were segregated into two categories: those who survived and those who did not. A compara- tive analysis was conducted between these groups con- Background: Fournier's Gangrene Scoring Index (FGSI), Simplified FGSI (SFGSI), Uludag FGSI (UFGSI), Laboratory Risk Indicator for Necrotizing (LRINEC), Neutrophil-Lymphocyte ratio (NLR), and Platelet-lymphocyte ratio (PLR) have been devised to assess the risk of mortality in Fournier's Gangrene (FG) patients. However, the effectiveness of these indicators in predicting mor- tality at the time of admission remains uncertain. The aim of this study is to assess the prognostic efficacy of FG’s various indicators on in-hospital mortality. Methods: This study analyzed 123 patients from Dr. Soetomo General Hospital’s emergency department in Indonesia from 2014 to 2020. Data included demographics, wound cultures, and parameters like FGSI, UFGSI, SFGSI, NLR, PLR, and LRINEC. In-hospital mortality status was also recorded. The data was subjected to comparative, sensitivity, specificity and regression analyses. Results: In our study of 123 patients, the median age was 52, with a mortality rate of 17.9%. The majority of patients were male (91.1%) and the most common location was scrotal (54.5%). Non-survivors had a shorter median stay (6.5 days) compared to survivors (14 days). Diabetes was the most preva- lent comorbidity (61.8%). The highest sensitivity and specificity were found in FGSI and UFGSI indicators. Multivariate logistic regression identified LoS and FGSI as independent predictors of mortality. Conclusions: FGSI and UFGSI, upon admission, demonstrated the highest sensitivity and specificity, with hospital stay duration and FGSI as key mortality determinants. KEY WORDS: Fournier's gangrene; Indicator; Neutrophil/lympho- cyte ratio (NLR); Platelet to lymphocit ratio. Submitted 14 January 2024; Accepted 19 February 2024 INTRODUCTION Despite significant strides in technological advancement, Fournier’s Gangrene (FG) continues to pose a formidable challenge with mortality rates oscillating between 5% and 65% (1). An array of prognostic indicators, encompassing Fournier’s Gangrene Severity Index (FGSI), Uludag Fournier’s Gangrene Severity Index (UFGSI), Simplified Evaluating prognostic indicators for in-Hospital mortality in Fournier's gangrene: A 7-year study in a tertiary Hospital Soetojo Wirjopranoto 1, 2*, Mohammad Reza Affandi 1*, Faisal Yusuf Ashari 3, 4, Yufi Aulia Azmi 2, 5, Kevin Muliawan Soetanto 6 1 Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia; 2 Department of Urology, Faculty of Medicine, Universitas Airlangga- Dr. Soetomo General Academic Hospital, Surabaya, Indonesia; 3 Department of Biomedical Sciences, Faculty of Medicine Universitas Airlangga, Surabaya, Indonesia; 4 Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom; 5 Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, Netherlands; 6 Department of Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand. * These authors equally contributed as first co-authors. DOI: 10.4081/aiua.2024.12387 Summary Archivio Italiano di Urologia e Andrologia 2024; 96(2):12387 S. Wirjopranoto, M. Reza Affandi, F. Yusuf Ashari, Y. Aulia Azmi, K. Muliawan Soetanto 2 cerning demographic informa- tion and scoring. The FGSI, UFGSI, SFGSI, LRINEC, NLR, and PLR were calculated using various parameters (5, 7, 8). Statistical analysis Group comparisons were per- formed using chi-square and Mann Whitney U test as appro- priate. The area under the receiver operating characteristic (ROC) curve was used to assess sensitivity and specificity, and the Youden index was used to determine the optimal cutoff value. Multivariable logistic regression models were con- structed using the stepwise backward LR method. A signif- icance level of p < 0.05 was considered statistically signifi- cant. Data analyses were per- formed using IBM SPSS Statistics for Windows version 24.0 (IBM Corp., Armonk, NY, USA). RESULTS Throughout the period under investigation, spanning from January 2014 to December 2020, the emergency department received a total of 135 patients with FG. However, the analysis only incorporated 123 patients (Figure 1). The patients had a median age of 52 (44-61), and the mortality rate was recorded at 17.9%. The study population was predominantly male (91.1%), and the most common location was scrotal (54.5%). Non-sur- vivors had a shorter median duration of stay compared to survivors, with lengths of 6.5 (3-14) days and 14 (7-21) days, respectively (Table 1). Diabetes was identified as the most prevalent comorbidity, present in 61.8% of patients. Table 1. Prognostic correlation with demographic and clinical features. Variable Total Survivor Non-survivor p value 101 (82.1%) 22 (17.9%) Age 52 (44-61) 52 (44-60) 55.5 (44-63) 0.328 Sex Male 112 (91.1%) 93 (92.1%) 19 (86.4%) 0.413 Female 11 (8.9%) 8 (7.9%) 3 (13.6%) Etiology Penoscrotal 18 (14.6%) 16 (15.8%) 2 (9.1%) 0.714 Perineum 38 (30.9%) 31 (30.7%) 7 (31.8%) Scrotum 67 (54.5%) 54 (53.5%) 13 (59.1%) LoS 12 (5-20) 14 (7-21) 6.5 (3-14) 0.009 Comorbidities Diabetes mellitus 76 (61.8%) 65 (64.4%) 11 (50.0%) 0.23 Hypertension 31 (25.2%) 29 (28.7%) 2 (9.1%) 0.06 Chronic kidney disease 11 (8.9%) 8 (7.9%) 3 (13.6%) 0.41 *LoS = Length of stay. Figure 1. Algorithm for the Inclusion and exclusion of patients. Figure 2. The ROC curve for FGSI, SFGSI, NLR, PLR, and LRINEC. The microorganisms most frequently encountered in our study population were Pseudomonas spp., Klebsiella pneu- monia, E. coli, and Acinetobacter spp. (Table 2). As illustrated in Figure 2, the ROC analysis unveiled cut- off values (sensitivity, specificity) for FGSI, SFGSI, UFGSI, NLR, PLR, and LRINEC predicting mortality as follows: 9 (100%, 83.2%), 2.5 (50%, 74.3%), 10.5 (100%, 83.2%), 7.5 (95.5%, 47.5%), 264.69 (68.2%, 57.4%), and 3.5 (50%, 56.4%), respectively. To identify independent pre- dictors of mortality, a multivariate logistic regression analy- Archivio Italiano di Urologia e Andrologia 2024; 96(2):12387 3 Prognostic indicators of Fournier's gangrene sis was conducted, including variables that were signifi- cantly associated with mortality in the univariate analysis (p < 0.05) (Table 3). Among these variables, only length of stay (LoS) and FGSI remained significant predictors of mor- tality in the multivariate analysis (Table 4). DISCUSSION During the study interval, it was observed that the major- ity of patients were male, with the scrotum being the most frequent site of origin. The length of hospital stay, prevalence of diabetes, and incidence of Pseudomonas spp. were also noteworthy among patients. An analysis of sensitivity, specificity, and independent risk factors for mortality revealed that both FGSI and UFGSI demon- strated the highest sensitivity and specificity. Furthermore, the length of hospital stay and FGSI were identified as independent prognostic value. Despite significant advancements, the mortality associat- ed with FG remains alarmingly high (9-11). Our study, conducted at a tertiary hospital in Indonesia's second- largest city, yielded a mortality rate of 17.9%, which could be attributed to the availability of advanced med- ical facilities and expertise. Notably, the demographics between groups were comparable, with the exception of LoS, which was significantly lower among non-survivors. In this study, we investigated established indicators employed at admission to predict FG mortality, including FGSI, SFGSI, NLR, PLR, and LRINEC. FGSI, recognized as the earliest and most frequently utilized indicator, is designed to assess the likelihood of mortality in FG patients (12). Our findings indicated that individuals who did not survive exhibited elevated FGSI values com- pared to those who did. The optimal cut-off for FGSI, along with its sensitivity and specificity, was identified as 9, 100%, and 83.2%, respectively. These results outper- formed those of previous studies, which reported sensi- tivity range of 69% to 100% and specificity range of 57% to 97% (4, 7, 13). The established cut-off of 9 at admis- sion aligns with the accepted threshold for mortality pre- diction. Therefore, FGSI with this recognized cut-off can be effectively utilized for early assessment and aggressive intervention. An analysis of the SFGSI, a simplified version of the FGSI that utilizes only three variables, revealed no differences between groups. The optimal cut-off, sensitivity, and specificity for SFGSI were determined to be 2.5, 50%, and 74.3%, respectively. The cut-off was similar to the consensus, which considered values above 2 as indicating a high risk of mortality (4). However, the reliability of SFGSI on admission to predict mortality in FG patients could not be confirmed. The UFGSI, a version of FGSI that includes age and dis- ease extent, was studied. UFGSI values were found to be Table 2. Findings from the wound culture analysis. Variable Total Survivor Non-survivor p value Acinetobacter 18 (14.6%) 13 (12.9%) 5 (22.7%) 0.31 Candida 6 (4.9%) 3 (3.0%) 3 (13.6%) 0.07 E.coli 18 (14.6%) 15 (14.9%) 3 (13.6%) 1.00 Pseudomonas 23 (18.7%) 19 (18.8%) 4 (18.2%) 1.00 Clostridium 5 (4.1%) 4 (4.0%) 1 (4.5%) 1.00 Streptococcus 4 (3.3%) 4 (4.0%) 0 (0.0%) 1.00 Streptococcus bovis 1 (0.8%) 1 (1.0%) 0 (0.0%) 1.00 Fusobacterium 11 (8.9%) 8 (7.9%) 3 (13.6%) 0.41 Staphylococcus 3 (2.4%) 3 (3.0%) 0 (0.0%) 1.00 Gamella 1 (0.8%) 1 (1.0%) 0 (0.0%) 1.00 Klebsiella p 20 (16.3%) 18 (17.8%) 2 (9.1%) 0.52 Sterile 13 (10.6%) 12 (11.9%) 1 (4.5%) 0.46 Table 3. Evaluation of the predictive capacity of FGSI, SFGSI, UFGSI, NLR, PLR, and LRINEC through univariate analysis. Variable Total Survivor Non-survivor p value FGSI 6 (4-10) 5 (4-8) 10.5 (10-11) 0.0001 SFGSI 1 (0-3) 1 (0-3) 2.5 (0-4) 0.085 UFGSI 8 (5-11) 7 (5-9) 12 (11-13) 0.0001 NLR 10 (4-16) 8 (4-15) 13 (10-19) 0.008 PLR 252.53 243.53 289.035 0.611 (164.62-358.97) (164.62-359.85) (165.07-358.65) LRINEC 3 (2-5) 3 (2-5) 3.5 (2-5) 0.859 Table 4. Outcomes of the multivariate logistic regression analysis. Variable β SE OR (95% CI) p value LoS -0.105 0.039 0.9 (0.83-0.97) 0.008 FGSI 0.618 0.127 1.856 (1.45-2.38) 0.0001 Supplementary Table 1. Measured parameters and cut-off score of each scoring system from the literature. Scoring system Number of parameters Parameters Cut-off score FGSI 9 Temperature, heart rate, respiratory rate, serum sodium, potassium, serum creatinine, hematocrit, leucocyte counts, and serum bicarbonate > 9 (13) UFGSI 11 Age and dissemination score in addition to the measured parameters from FGSI ≥ 9 (7) SFGSI 3 Serum creatinine, hematocrit, and serum potassium > 2 (4) NLR 1 The ratio was calculated by dividing the number of neutrophils by the number of lymphocytes. > 8 (14) PLR 1 The ratio was calculated by dividing the number of platelets by the number of lymphocytes. > 140 (14) LRINEC 6 C-reactive protein, white blood cell counts, hemoglobin, serum sodium, serum creatinine, and blood glucose ≥ 6 (17) FGSI: Fournier’s Gangrene Severity Index; UFGSI: Uludag Fournier’s Gangrene Severity Index; SFGSI: Simplified Fournier’s Gangrene Severity Index; NLR: Neutrophil-to-lymphocyte Ratio (NLR); PLR: Platelet-to-lymphocyte Ratio (PLR); LRINEC: Laboratory Risk Indicator for Necrotizing Fasciitis. Archivio Italiano di Urologia e Andrologia 2024; 96(2):12387 S. Wirjopranoto, M. Reza Affandi, F. Yusuf Ashari, Y. Aulia Azmi, K. Muliawan Soetanto 4 higher in non-survivors. The optimal cut-off, sensitivity, and specificity for UFGSI were identified as 10.5, 100%, and 83.2%, respectively. These values were similar to those of the FGSI. While previous research suggested that UFGSI performs better than FGSI, the difference in our findings could be due to the lack of pelvic and beyond involvement in our study population (3). NLR and PLR have been used as mortality predictors in FG patients in previous studies (5, 6, 14). High NLR and PLR have been linked with mortality predictors in FG patients (5, 14). One study found NLR and PLR to be bet- ter than FGSI (14), while another found NLR to be better than PLR (6). However, our study showed significantly higher NLR levels in non-survivors compared to sur- vivors. Despite this, neither NLR nor PLR predicted in- hospital mortality in our study. NLR and PLR are known markers of inflammation and infection (15). The diver- gence in results suggests that NLR and PLR may be influ- enced by the disease phase, whether acute or chronic, a distinction challenging to ascertain in a tertiary hospital setting primarily consisting of referred patients (16). The LRINEC score, which overlaps with FGSI in some variables, is a laboratory-centric indicator employed to evaluate mortality in patients suffering from FG. While certain studies have identified a significant correlation between elevated LRINEC scores and mortality (5, 17), our research did not discern a notable difference between survivors and non-survivors, nor could it prognosticate in-hospital mortality for FG. These findings may be pro- foundly influenced by the specific laboratory equipment utilized and the disease’s stage at the time of examination. Given the inconsistent results obtained using laboratory- based indicators like SFGSI, LRINEC, NLR, and PLR, employing a scoring system (FGSI and UFGSI) at the time of admission could potentially provide a more accurate prediction of mortality for FG patients. Despite its strengths, this study has certain limitations. First, it utilized a retrospective design, which restricted to influence the laboratory blood draws. Second, the study analysed data from a single tertiary referral center, poten- tially leading to a sample population skewed towards more severe cases. Thirdly, each patient may have been in a distinct disease stage upon admission, given our hospi- tal's tertiary status and frequent intake of referred patients. Lastly, despite the confirmation of all FG cases through a thorough review of medical and surgical records, some positive cases might have been missed due to the absence of comprehensive retrospective records. Future prospective studies involving multiple centers are imperative to identify the most sensitive parameters for predicting patient mortality. CONCLUSIONS In this study, it was observed that FGSI and UFGSI showed the highest sensitivity and specificity among the current indicators upon admission. The duration of hos- pital stay and FGSI were recognized as independent determinants of mortality. These indicators could poten- tially offer a more accurate prediction of mortality. However, it is essential to exercise caution when inter- preting laboratory-only indicators in a tertiary hospital setting due to possible biases arising from disease stage. To validate these results, a multicenter prospective study is recommended. This would aid in verifying the reliabil- ity and applicability of these indicators across various set- tings and patient demographics. ACKNOWLEDGMENTS All Medical Recors Staff’s of Soetomo General Academic Hospital and Faculty of Medicine, Universitas Airlangga. REFERENCES 1. Sorensen MD, Krieger, JN, Rivara FP, et al. Fournier's Gangrene: Management and Mortality Predictors in a Population Based Study. J Urol 2009; 182:2742-2747. 2. Laor E, Palmer LS, Tolia BM, et al. Outcome Prediction in Patients with Fournier's Gangrene. J Urol 1995; 89-92. 3. Yilmazlar T, Ozturk E, Ozguc H, et al. Fournier's gangrene: an analysis of 80 patients and a novel scoring system. Tech Coloproctol 2010; 14:217-223. 4. Lin TY, Ou CH, Tzai TS, et al. Validation and simplification of Fournier's gangrene severity index. Int J Urol 2014; 21:696-701. 5. Bozkurt O, Sen V, Demir O, Esen A. Evaluation of the utility of different scoring systems (FGSI, LRINEC and NLR) in the manage- ment of Fournier’s gangrene. Int Urol and Neph 2015; 47:243-248. 6. Wirjopranoto S. Comparison between neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio as predictors of mortality on Fournier's gangrene cases. Indian J Urol 2023; 39:121-125. 7. Ureyen O, Acar A, Gokcelli U, et al. Usefulness of FGSI and UFGSI scoring systems for predicting mortality in patients with Fournier's gangrene: A multicenter study. Ulus Travma Acil Cerrahi Derg 2017; 23:389-394. 8. Tutino R, Colli F, Rizzo G, et al. Which Role for Hyperbaric Oxygen Therapy in the Treatment of Fournier's Gangrene? A Retrospective Study. Front Surg 2022; 9:850378. 9. Rieger C, Huber M, Kastner L, et al. Center-based First-line Therapy Is a Significant Predictor for Mortality of Fournier Gangrene. JU Open Plus 2023; 1. 10. Bermani BF, Rizaliyana S, Handriani I. Predisposition Factors Analysis for Fournier’s Gangrene Defects Closure Complication. J Rekon Est 2021; 5:13 11. Radcliffe RS, Khan MA. Mortality associated with Fournier's gangrene remains unchanged over 25 years. BJU Int 2020; 125:610- 616. 12. Laor E, Palmer LS, Tolia BM, et al. Outcome Prediction in Patients with Fournier's Gangrene. J Urol 1995; 154:89-92. 13. Noegroho BS, Siregar S, Mustafa A, Rivaldi MA. Validation of FGSI Scores in Predicting Fournier Gangrene in Tertiary Hospital. Res Rep Urol 2021; 13:341-346. 14. Yim SU, Kim SW, Ahn JH. et al. Neutrophil to Lymphocyte and Platelet to Lymphocyte Ratios Are More Effective than the Fournier's Gangrene Severity Index for Predicting Poor Prognosis in Fournier's Gangrene. Surg Infect 2016; 17:217-223. 15. Kosidlo JW, Wolszczak-Biedrzycka B, Matowicka-Karna J, et al. Clinical Significance and Diagnostic Utility of NLR, LMR, PLR and SII in the Course of COVID-19: A Literature Review. J Inflamm Res 2023; 16:539-562. Archivio Italiano di Urologia e Andrologia 2024; 96(2):12387 5 Prognostic indicators of Fournier's gangrene 16. Kose N, Yildirim T, Akin F, et al. Can NLR, PLR and LMR be used as prognostic indicators in patients with pulmonary embolism? Author's reply on commentary. Bosn J Basic Med Sci 2021; 21:502. 17. Kincius M, Telksnys T, Trumbeckas D, et al. Evaluation of LRINEC Scale Feasibility for Predicting Outcomes of Fournier Gangrene. Surg Infect 2016; 17:448-453. Correspondence Prof. Soetojo Wirjopranoto, MD (Corresponding Author) stjowirjopranoto@gmail.com Department of Urology, Faculty of Medicine, Universitas Airlangga - Dr. Soetomo General Academic Hospital, Surabaya, Indonesia Mohammad Reza Affandi, MD rezaaffandi@outlook.com Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia Faisal Yusuf Ashari, MD faisal.ashari@postgrad.manchester.ac.uk Department of Biomedical Sciences, Faculty of Medicine Universitas Airlangga, Surabaya, Indonesia Jl. Mayjen Prof. Dr. Moestopo No.6-8, Surabaya, East Java, Indonesia, 60286 Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK Yufi Aulia Azmi, MD yufiazmi@gmail.com; y.aulia.azmi@umcg.nl Department of Urology, Faculty of Medicine, Universitas Airlangga - Dr. Soetomo General Academic Hospital, Surabaya, Indonesia Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, Netherlands Kevin Muliawan Soetanto, MD kmskevinmuliawan@gmail.com Department of Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand Conflict of interest: The authors declare no potential conflict of interest.