Prediction of Mortality in Patients with Fournier's Gangrene: Importance of Time to Surgery

Prediction of Mortality in Patients with Fournier's Gangrene: Importance of Time to Surgery | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prediction of Mortality in Patients with Fournier's Gangrene: Importance of Time to Surgery Mert Hamza Özbilen, Mahmut Can Karabacak, Eyyüp Tekin, Ulaş Can Erdoğan, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6671475/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose To evaluate the clinical and laboratory findings that predict mortality,the role of five scoring systems in mortality prediction,and the importance of the time from admission to emergency department to surgery in Fournier’s Gangrene(FG) patients. Methods A total of 354 patients who were diagnosed with FG were divided into survivors (n = 293) and non-survivors (n = 61).Multivariate logistic regression analysis was applied for variables that were statistically significant in the univariate analysis regarding factors predicting mortality in patients with FG.Fournier Gangrene Severity Index(FGSI) score,Uludağ Fournier Gangrene Severity Index(UFGSI) score,Age-adjusted Charlson Comorbidity Index(ACCI),Laboratory risk indicator for necrotizing fasciitis(LRINEC) index and The Combined Urology and Plastics Index(CUPI) were analyzed with receiver operating characteristic(ROC) curve for the predicting the mortality of FG. Results The mortality rate due to FG was found to be 17.2%.Advanced age,increased respiratory rate,high serum chloride,low serum bicarbonate,low serum albumin,and the time between hospital admission and surgery are independent predictors of FG mortality in the multivariate analysis.The area under ROC curve (AUC) values of FGSI score,UFGSI score,ACCI,LRINEC index,CUPI were found to be 0.719,0.751,0.641,0.636,0.751,respectively.Mortality was 13.3% in patients with a time of up to 12 hours until surgery,and 24.2% in patients with a time of more than 12 hours until surgery.Also,a time to surgery longer than 12 hours was associated with longer length of hospital stay (p = 0.001). Conclusions If a scoring system is to be used for FG-related mortality,the UFGSI score and CUPI should be evaluated primarily.One of the most important aspects of reducing mortality is complete debridement within 12 hours of hospital admission. Fournier’s gangrene mortality scoring systems time to surgery emergency Figures Figure 1 INTRODUCTION Necrotizing soft tissue infection (NSTI) encompasses any infection involving any layer of soft tissue, including the superficial fascia, deep fascia, or muscle. Necrotizing fasciitis is a severe form of NSTI that affects the superficial fascia and subcutaneous tissues. Fournier's gangrene (FG) is form of necrotizing fasciitis that affects the superficial and deep tissues of the genital, scrotal, perineal, and perianal regions [ 1 ]. In other words, FG is a subgroup of NSTIs. FG causes obliterative endarteritis. Necrosis occurs because of microvascular obstruction and impaired blood circulation. A hypoxic environment provides a basis for bacterial proliferation [ 2 ]. FG is associated with severe tissue damage, necrosis, and potential systemic complications following the spread of infection through soft tissues. It usually presents as signs of sepsis. It can progress to multiple organ failure and septic shock [ 3 ]. Although it can affect both sexes and various age groups, it is a rare disease that usually occurs in men aged 50–70. The incidence is estimated to be approximately 1.6 cases per 100000 men per year, representing less than 0.02% of hospitalized patients [ 4 ]. In a systematic review covering the years 1993–2018, it was emphasized that mortality due to FG was around 40%, and there was no significant decrease in the 25-year period [ 5 ]. However, another review conducted between 2000 and 2021 found that although the mortality rate due to FG was still high at 7.3%, it decreased compared to previous years owing to advances in both the recognition and treatment of the disease [ 6 ]. Considering the complex structure and severity of FG, it is important to identify prognostic factors to develop treatment strategies and predict the clinical outcomes. Various scoring systems have been developed to predict morbidity and mortality in FG patients. The Fournier Gangrene Severity Index (FGSI) [ 7 ] and Uludağ Fournier Gangrene Severity Index (UFGSI) [ 8 ] are scoring systems developed to predict the mortality probability patients with FG. The Age-adjusted Charlson Comorbidity Index (ACCI) is a scoring system used to evaluate comorbidities and predict mortality [ 9 ]. The Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) index is used to differentiate necrotizing fasciitis from other soft tissue infections based on laboratory findings [ 10 ]. The Combined Urology and Plastics Index (CUPI) is a scoring system used to predict the length of hospital stay (LOS) and morbidity in patients with FG [ 11 ]. Early diagnosis of FG may result in reduced the damage to patients' health, increasing treatment success and survival rates. Based on this idea, we aimed to evaluate the clinical and laboratory findings that predict mortality, the role of the five existing scoring systems in mortality prediction, and the importance of the time from admission to the emergency department to surgery in patients with FG. MATERIAL AND METHODS This observational study was approved by the Institutional Review Board (IRB No. 2025/01–33). Data of patients diagnosed with FG between 2007 and 2023 in one of the tertiary referral centers in our country were retrospectively examined. The diagnosis was made by physical examination, taking into account the presence of erythema, induration, tenderness, blackness, subcutaneous crepitation, necrosis, and repulsive fecaloid odor. Individuals with perianal, periurethral, or scrotal abscesses without necrosis or soft tissue extensions were excluded. As a result of the review, 354 patients aged ≥ 18 years who were diagnosed with FG and had no missing data were included in the study. A total of 354 patients who met the inclusion criteria were divided into survivors (n = 293) and non-survivors (n = 61). The following data were collected from FG patients admitted to hospital and compared between the two groups: patient demographics (age, gender, comorbidities), pulse, respiratory rate (RR), body temperature, disease extend, serum laboratory results (hematocrit, leukocyte, lymphocyte, neutrophil lymphocyte ratio (NLR), platelet, urea, blood urea nitrogen (BUN), creatinine, sodium, potassium, chloride, bicarbonate, calcium, alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), total bilirubin, total protein, albumin, international normalized ratio (INR), procalcitonin, c-reactive protein (CRP)), scoring system scores (FGSI score, UFGSI score, ACCI, LRINEC index, CUPI), microbial growth in wound culture, wound culture sterilization time, time to surgery, Vacuum-Assisted Closure (VAC) of a wound, VAC duration, definitive wound closure type, number of debridement in the operating room, need for intensive care unit (ICU), LOS, length of stay in the ICU. The time to surgery was defined as the time from the patient's arrival to the emergency department until surgical intervention. Multivariate logistic regression analysis was applied to variables that were statistically significant in the univariate analysis regarding factors predicting mortality in patients with FG. Patients who had a time to surgery of more than 12 hours or less were compared in terms of mortality, need for ICU, number of debridements performed in the operating room, LOS, and length of stay in the ICU. The FGSI score, UFGSI score, ACCI, LRINEC index, and CUPI were analyzed using receiver operating characteristic (ROC) curves to predict the severity of FG. After the vital signs of all patients stabilized, the patient was evaluated by the infectious disease clinic, and empirical antibiotics were started in the emergency room. Antibiotic treatment was changed if deemed necessary by the Infectious Disease Department based on the patient's wound culture results and clinical and laboratory findings. Surgical intervention was performed by debridement of the infected and necrotic tissues until healthy tissues were obtained. Depending on the progression of the infection, debridement was repeated in the operating room when the surgeon deemed it necessary. All patients who did not receive VAC treatment were followed up using conventional wound dressings. In patients receiving VAC treatment, the dressing was changed every 72 hours. The conventional wound dressing was changed daily with appropriate saline soaked gauze by the surgeon and nurse. The FGSI score is a numerical value created by combining the clinical and laboratory values. It is based on body temperature, pulse, RR, serum sodium, potassium, creatinine, hematocrit, leukocyte, and bicarbonate values. A score between 0 and 4 was assigned to each parameter. The overall score is calculated by summing the points assigned to each parameter. It has been reported that it is strongly associated with mortality rates [ 7 ]. The UFGSI score is another scoring system created by adding the disease extent and patient age to the FGSI score [ 8 ]. ACCI is a widely used comorbidity scoring system. It has 20 parameters. It is used to evaluate mortality risk based on the severity and number of diseases that the patient has [ 9 ]. The LRINEC index is a laboratory-based scoring system that can be used to detect early clinical cases of necrotizing fasciitis. It was created based on serum CRP, leukocyte, hemoglobin, sodium, creatinine, and glucose levels. A maximum of 13 points was obtained by assigning points to each parameter [ 10 ]. The CUPI is a scoring system used for the LOS of patients with FG. In addition to age, serum hematocrit, calcium, ALP, albumin, INR, bicarbonate, total bilirubin, and BUN values were considered. A total score of up to 15 was obtained for these parameters [ 11 ]. Statistical Analysis: The one-sample Kolmogorov Smirnov test was used to determine whether the data showed a normal distribution for numerical variables. The mean ± standard deviation was found in the data with normal distribution, and median (interquartile range (IQR)) values ​​were recorded in the data without normal distribution. Numerical variables were compared using the Student's t-test when parametric test criteria were found. In the absence of these criteria, the Mann-Whitney U test was used. In addition, the Mann-Whitney U test was used to compare ordinal categorical variables. Pearson’s chi-squared test was used to determine whether there was a difference between the percentages of categorical variables. Binary logistic regression analysis was used to identify the independent risk factors for mortality in patients with FG. Multivariate logistic regression analysis was performed for variables that were statistically significant in univariate analysis. A ROC curve was generated by plotting the sensitivity as a function of (1-specificity) to investigate the predictive values of the scoring systems predicting the severity of FG. For all the tests, the probability of the first type of error was α = 0.05. Statistical analysis was performed using IBM SPSS 22.0 package program. RESULTS Considering the inclusion and exclusion criteria, 354 patients followed up due to FG were included in the study. Of these, 293 patients were defined as survivors and 61 as non-survivors. The demographic, clinical, and laboratory findings of the two groups are compared in Table 1 . The mortality rate of FG was 17.2%. The mean age was 55.3 in survivors and 65.6 in non-survivors, and a statistically significant difference was found (p < 0.001). While the mean RR was 19.5 in survivors, it was 22.5 in non-survivors, and a statistically significant difference was observed (p < 0.001). Female sex, comorbidities, increased pulse rate, and advanced disease extension were more common in the deceased patients. When laboratory findings were evaluated, serum NLR (p = 0.046), chloride (p = 0.025), creatinine (p < 0.001), INR (p = 0.001), total bilirubin (p = 0.001), BUN (p < 0.001) and procalcitonin (p < 0.001) were found to be high, while hematocrit (p = 0.004), bicarbonate (p < 0.001), albumin (p < 0.001) and calcium (p = 0.003) were found to be low in non-survivors. No significant differences were found between the two groups in terms of serum leukocyte (p = 0.951), sodium (p = 0.934), potassium (p = 0.544), CRP (p = 0.309), and ALP (p = 0.505) levels. Table 1: Grouping of demographic, clinical and laboratory data according to mortality (SD: standard deviation, n: number, min: minute, BUN: blood urea nitrogen, ALT: alanine aminotransferase, AST: aspartate aminotransferase, ALP: alkaline phospatase, INR: international normalized ratio, CRP: C-reactive protein, FGSI: Fournier Gangrene Severity Index, UFGSI: Uludağ Fournier Gangrene Severity Index, ACCI: Age-adjusted Charlson Comorbidity Index, LRINEC: Laboratory risk indicator for necrotizing fasciitis, CUPI: the Combined Urology and Plastics Index , VAC: vacuum assisted closure, ICU: intensive care unit, T :Student T test, M :Mann-Whitney U test, P :Pearson’s Chi-square test) Survivors (n=293) Non-survivors (n=61) P value Age, years, mean±SD 55.3±13.5 65.6±13.5 <0.001 T Gender, n (%) Female Male 82 (28) 211 (72) 27 (44.3) 34 (55.7) 0.012 P Presence of risk factors, n (%) 247 (84.3) 56 (91.8) 0.129 P Pulse (beats per min) ,mean±SD 92.3±15.9 100.4±17.5 <0.001 T Respiratory rate ( breaths per min) , mean±SD 19.5±4.9 22.6±5.3 <0.001 T Body temperature (°C), median (min-max) 36.6 (36.0-39.6) 37 (36.4-41.0) <0.001 M Comorbidities, n (%) No Diabetes Mellitus Cancer Immunosuppression Obesity Trauma/Surgery Cardiovascular Chronic Kidney Disease 46 (15.7) 81 (27.6) 21 (7.2) 5 (1.7) 24 (8.2) 45 (15.4) 60 (20.5) 11 (3.8) 5 (8.2) 8 (13.1) 3 (4.9) 3 (4.9) 1 (1.6) 13 (21.3) 24 (39.3) 4 (6.6) 0.003 P Disease extend, n (%) Urogenital Anorectal Extending into the pelvis Extending outside the pelvis Anogenital 82 (28) 108 (36.9) 26 (8.9) 48 (16.4) 29 (9.9) 13 (21.3) 13 (21.3) 7 (11.5) 22 (36.1) 6 (9.8) 0.005 P Hematocrit (%), mean±SD 34.2±7.0 31.5±5.3 0.004 T Leukocyte (10 3 /μL), mean±SD 16.9±7.9 16.8±8.5 0.951 T Lymphocyte (10 3 /μL), median (min-max) 1.3 (0.2-9.8) 1 (0.1-8.3) 0.005 M Neutrophil lymphocyte ratio, median (min-max) 12.1 (0.8-119.5) 16.8 (1.3-133) 0.046 M Platelet (10 3 /μL), mean±SD 323.7±144.2 287.3±181.1 0.088 T Urea (mg/dL), median (min-max) 43 (13-324) 78 (7-447) <0.001 M BUN (mg/dL), median (min-max) 20.1 (6.1-151.4) 36.4 (3.3-208.9) <0.001 M Creatinine (mg/dL), median (min-max) 1.1 (0.4-10.6) 1.5 (0.4-7.4) <0.001 M Sodium (mmol/L), median (min-max) 134 (115-148) 134 (117-176) 0.934 M Potassium (mmol/L), mean±SD 4.3±0.7 4.3±0.9 0.544 T Chloride (mmol/L), median (min-max) 99 (79-112) 101 (78-144) 0.025 M Bicarbonate (venous) (mmol/L), mean±SD 22.9±2.8 19.1±4.2 <0.001 T Calcium (mg/dL), mean±SD 8.6±0.7 8.3±0.7 0.003 T ALT (U/L), median (min-max) 19 (3-358) 22 (4-346) 0.692 M AST (U/L), median (min-max) 23 (7-493) 37 (5-470) <0.001 M ALP (U/L), median (min-max) 97 (46-520) 100 (43-555) 0.505 M Total bilirubin (mg/dL), median (min-max) 0.6 (0.01-3.7) 0.8 (0.05-5.78) 0.001 M Total protein (g/dL), mean±SD 5.7±1.0 5.1±0.9 <0.001 T Albumin (g/dL), mean±SD 2.9±0.7 2.2±0.7 <0.001 T INR, median (min-max) 1.1 (0.1-2.2) 1.2 (0.12-52) 0.001 M Procalcitonin (μg/L), median (min-max) 0.4 (0-75) 1.1 (0.03-63) <0.001 M CRP (mg/dL), mean±SD 165.5±136.7 185.0±130.9 0.309 T FGSI score, mean±SD 3.5±3.7 6.9±4.8 <0.001 T UFGSI score, mean±SD 5.7±4.3 10.5±5.7 <0.001 T ACCI, mean±SD 1.8±1.6 2.9±2.3 <0.001 T LRINEC index, mean±SD 5.5±3.4 7.1±3.4 <0.001 T CUPI, mean±SD 4.3±1.8 5.9±1.7 <0.001 T Microbial growth in wound culture, n (%) 163 (60.8) 34 (59.6) 0.869 P Wound culture sterilization time (days) 17.6±18.4 Time to surgery (hours), median (min-max) 8 (0.5-168) 12.5 (1-480) 0.016 M Surgery after 24 hours, n (%) 50 (17.1) 15 (24.6) 0.167 P Surgery after 12 hours, n (%) 97 (33.1) 31 (50.8) 0.009 P Surgery after 6 hours, n (%) 176 (60.1) 40 (65.6) 0.422 P Surgery after 3 hours, n (%) 241 (82.3) 52 (85.2) 0.573 P Surgery after 1 hour, n (%) 274 (93.5) 58 (95.1) 0.645 P VAC of a wound, n (%) 83 (28.3) 16 (26.2) 0.740 P VAC duration, median (min-max) 15 (3-60) 13.5 (1-85) 0.875 M Definitive wound closure type, n (%) Primary Secondary Graft-Flap Exitus 121 (41.3) 111 (37.9) 61 (20.8) - 2 (3.3) 2 (3.3) - 57 (93.4) <0.001 P Number of debridement in the operating room, median (min-max) 1 (1-13) 1 (1-20) 0.966 M Need for ICU, n (%) 109 (37.2) 56 (91.8) <0.001 P Length of hospital stay, days, median (min-max) 15 (1-93) 14 (1-120) 0.374 M Length of stay in the ICU, days, median (min-max) 3 (1-35) 6 (1-90) 0.001 M The mean FGSI, UFGSI, ACCI, LRINEC, and CUPI scores were 3.5, 5.7, 1.8, 5.5, 4.3 in survivors, and 6.9, 10.5, 2.9, 7.1, 5.9 in non-survivors, respectively. All of these scores were statistically higher in deceased patients (p < 0.001 for all). In the comparison of both groups, the median time to surgery was 8 hours in the surviving patients and 12.5 hours in those who died (p = 0.016). Time to surgery longer than 12 hours was associated with increased mortality (p = 0.009). The results of the multivariate logistic regression analysis of the factors predicting mortality in patients with FG are shown in Table 2 . Multivariate analysis showed that advanced age (p = 0.001), increased RR (p = 0.003), high serum chloride level (p = 0.027), low serum bicarbonate level (p < 0.001), low serum albumin level (p < 0.001), and prolonged time to surgery (p = 0.005) were independent predictors of mortality in FG. Table 2 Multivariate logistic regression analysis of factors predicting mortality in patients with Fournier gangrene (n: number, BUN: blood urea nitrogen, ALT: alanine aminotransferase, AST: aspartate aminotransferase, ALP: alkaline phospatase, INR: international normalized ratio, CRP: C-reactive protein, OR: odds ratio, FGSI: Fournier Gangrene Severity Index, UFGSI: Uludağ Fournier Gangrene Severity Index, ACCI: Age-adjusted Charlson Comorbidity Index, LRINEC: Laboratory risk indicator for necrotizing fasciitis, CUPI: the Combined Urology and Plastics Index , VAC: vacuum assisted closure, ICU: intensive care unit) Binary Logistic Regression (n = 354) Univariate Model Multivariate Model OR 95% CI P value OR 95% CI P value Age 1.065 1.039 - 1.092 <0.001 1.055 1.022 - 1.090 0.001 Gender (reference: female) 0.489 0.278 - 0.862 0.013 Presence of risk factors 2.086 0.793 - 5.488 0.136 Pulse 1.029 1.012 - 1.046 0.001 Respiratory rate 1.113 1.055 - 1.173 < 0.001 1.107 1.035 - 1.185 0.003 Body temperature (°C) 2.235 1.569 - 3.185 < 0.001 Disease extend (reference: urogenital) 1.302 1.063 - 1.594 0.011 Hematocrit 0.945 0.907 - 0.984 0.006 Leukocyte 0.999 0.965 - 1.034 0.951 Lymphocyte 0.905 0.681 - 1.204 0.494 Neutrophil lymphocyte ratio 1.023 1.006 - 1.040 0.008 Platelet 0.998 0.996 - 1.000 0.089 Urea 1.014 1.009 - 1.019 < 0.001 BUN 1.031 1.020 - 1.042 < 0.001 Creatinine 1.328 1.093 - 1.614 0.004 Sodium 1.016 0.970 - 1.063 0.509 Potassium 1.123 0.772 - 1.634 0.543 Chloride 1.060 1.012 - 1.110 0.014 1.075 1.008 - 1.146 0.027 Bicarbonate 0.731 0.668 - 0.801 < 0.001 0.776 0.700 - 0.860 < 0.001 Calcium 0.557 0.378 - 0.821 0.003 ALT 1.004 0.996 - 1.011 0.323 AST 1.008 1.002 - 1.015 0.016 ALP 1.003 0.999 - 1.008 0.135 Total bilirubin 1.945 1.271 - 2.977 0.002 Total protein 0.523 0.394 - 0.695 < 0.001 Albumin 0.186 0.109 - 0.317 < 0.001 0.245 0.125 - 0.478 < 0.001 INR 6.274 1.184 - 20.888 0.003 Procalcitonin 1.027 1.000 - 1.055 0.047 CRP 1.001 0.999 - 1.003 0.308 FGSI score 1.193 1.119 - 1.271 < 0.001 UFGSI score 1.201 1.135 - 1.271 < 0.001 ACCI 1.331 1.156 - 1.531 < 0.001 LRINEC Index 1.151 1.056 - 1.255 0.001 CUPI 1.775 1.460 - 2.158 < 0.001 Time to surgery (hours) 1.012 1.006 - 1.019 12 2.088 1.195 - 3.647 0.010 Number of debridement 1.069 0.980 - 1.167 0.131 VAC 0.900 0.482 - 1.680 0.740 VAC duration 1.026 0.995 - 1.058 0.097 When the survivors and the deceased were compared (Table 1 ), it was determined that the time to surgery exceeding 12 hours was significantly different between the two groups. For this reason, patients whose time to surgery exceeded 12 hours and those who did not exceed 12 hours were evaluated separately (Table 3 ). In Table 3 , patients with a time to surgery of up to 12 hours (n = 226) and those with a time to surgery of more than 12 hours (n = 128) were compared with each other. Accordingly, mortality was 13.3% in patients with a time of up to 12 hours until surgery and 24.2% in patients with a time of more than 12 hours until surgery (p = 0.009). In addition, a time to surgery longer than 12 hours was associated with longer LOS (p = 0.001) and longer length of stay in the ICU (p = 0.044). No significant difference was found in the need for ICU admission (p = 0.459) and the number of debridements in the operating room (p = 0.774). Table 3 Effect of time to surgery longer than 12 hours on mortality and length of hospital stay (n: number, ICU: intensive care unit, M : Mann-Whitney U test, P : Pearson’s Chi-square test) Δ-hours ≤ 12 (n = 226) Δ-hours > 12 (n = 128) P value Mortality, n (%) 30 (13.3) 31 (24.2) 0.009 P Need for ICU, n (%) 102 (45.1) 63 (49.2) 0.459 P Number of debridement in the operating room, median (min-max) 1 (1–20) 1 (1–18) 0.774 M Length of hospital stay, days, median (min-max) 14 (1-103) 19 (1-120) 0.001 M Length of stay in the ICU, days, median (min-max) 3 (1–64) 6 (1–90) 0.044 M Details of the ROC analysis of the scoring systems predicting FG severity were shown in Fig. 1 . The area under ROC curve (AUC) values of FGSI, UFGSI, ACCI, LRINEC and CUPI score were 0.719, 0.751, 0.641, 0.636, and 0.751, respectively. DISCUSSION In a disease with high mortality rates, such as FG, determining the factors that affect the course of the disease is one of the most important elements. By determining these factors, it is possible to prevent the morbidity and mortality associated with FG [ 12 ]. Advancing age causes a decrease in physiological functions and a weakening of the immune system. This can lead to an increased risk of infection and a reduced ability to fight infection. At the same time, comorbidities that may occur due to advanced age can cause a more dramatic FG course [ 13 ]. While age was not included in the FSGI and LRINEC indices, it was one of the parameters in the UFGSI and CUPI scores. Although there are studies claiming the contrary, [ 14 , 15 ] many have stated that advanced age is associated with mortality due to FG [ 4 , 13 ]. In a regression analysis of mortality due to FG in the study by Sugihara et al., advanced age was found to be an independent risk factor, similar to our study [ 16 ]. RR is one of the parameters of the two most commonly used scoring systems for FG (FGSI and UFGSI). Some studies have shown that RR is higher in patients who died, and [ 15 ] as well as there are some studies have shown that there is no significant difference between survivors and non-survivors [ 17 ]. In our study, multivariate regression analysis showed that an increased RR was an independent predictor of mortality (p = 0.003). Chloride is an electrolyte that is often overlooked, but has important effects on the patient, which can lead to many disorders, including disorders of hemostasis, acid-base balance, and immunomodulation [ 18 ]. Increased serum chloride levels can lead to metabolic acidosis, renal failure, and hemodynamic instability [ 19 ]. Although literature indicates that mortality rates increase in patients with hyperchloremia, it is not yet clear whether the effect of chloride levels on mortality is direct or indirect [ 20 ]. In our study, high serum chloride level was found to be an independent predictor of FG-related mortality. Based on this result, our study is the first and only study in the literature to show the existence of a relationship between serum chloride levels and FG-related mortality. Low serum bicarbonate level is an indicator of metabolic acidosis. In metabolic acidosis, interleukin production is stimulated by macrophages and lymphocyte function is suppressed. This leads to increased inflammation and an impaired immune response [ 21 ]. Studies have generally reported that serum bicarbonate levels were significantly lower in patients who died of FG [ 17 ]. In our study, a low serum bicarbonate level was found to be an independent predictor of FG-related mortality (p < 0.001). Serum albumin is known as a negative acute phase reactant. Hypoalbuminemia can be observed in patients with metabolic stress. Serum albumin levels may reflect the patient's nutritional status and immune function [ 22 ]. Low serum albumin levels may play a role in disease progression, and advanced disease may cause a decrease in serum albumin levels. Low serum albumin level was found to be an independent risk factor for mortality related to FG in the multivariate regression analysis in the study by Shin et al. and in the study by Çomçalı et al, as in our study [ 23 , 24 ]. More than 10 scoring systems, both specific and non-specific to FG, have been investigated to predict mortality in FG [ 15 ]. Scoring systems should be easy to calculate, relatively less time consuming, and have high sensitivity and specificity. There is no clear consensus in the literature on whether scoring systems are useful in FG, and if so, which system should be used first [ 25 ]. The FGSI is the first and most commonly used FG-specific scoring method; however, it is time consuming to calculate. The threshold value for the FGSI was found to be 9. If the score was higher than 9, the mortality rate would be 75%, and if it was lower than 9, the mortality rate would drop to 22% [ 7 ]. Sparenborg et al. emphasized the necessity of adding diabetes to FGSI score [ 17 ]. The threshold value for the UFGSI score was 9, which is similar to the FGSI score. The authors stated that the predictive power was higher and emphasized that if the score was higher than 9, the mortality rate would be 94%, whereas when it was 9 or less, this rate would drop to 18% [ 8 ]. This calculation is time consuming. Although the ACCI is not a scoring system specific to FG, it is used to evaluate the mortality risk based on the severity and number of diseases the patient has. It is easy to calculate and has validation for a large number of diseases. In a study by Sugihara et al., increased ACCI was found to be an independent risk factor for FG-related mortality in multivariate regression analysis [ 16 ]. LRINEC index is an easy-to-calculate scoring system. It is not specific to FG, and was developed for diagnostic purposes. In the LRINEC index, patients were divided into three risk categories for NSTIs: low (LRINEC index ≤ 5), intermediate (LRINEC index 6–7) and high (LRINEC index ≥ 8). A LRINEC index of 6 and above increases the suspicion of necrotizing fasciitis, and a score of 8 or above is a strong predictor of this disease [ 10 ]. The CUPI is specific for FG and is the first scoring system that prioritizes morbidity and LOS in patients with FG. The threshold value for the CUPI was 5. For values 5 and​​ below, the mean LOS was 25 days, whereas for values ​​above 5, the mean LOS was 71 days [ 11 ]. CUPI is a scoring system that has not been extensively studied. If we evaluate the studies comparing the scoring systems predicting FG-related mortality, in the meta-analysis conducted by Tufano et al. investigating the predictive values ​​of FGSI and UFGSI scores for mortality in patients with FG, they stated that mortality increased as scores increased in both scoring systems, but the accuracy rate of UFGSI was higher [ 25 ]. Atilla et al. stated that both FGSI and UFGSI scores have a strong predictive value for mortality, whereas LRINEC is weak [ 14 ]. Among the studies comparing FGSI, UFGSI, and ACCI, Although Çomçalı et al. found that UFGSI has a higher prediction than FGSI and ACCI [ 24 ], Roghmann et al. stated that all three scoring systems can be used to predict mortality; however, if possible, ACCI, which is easier to calculate and generally accepted, should be preferred [ 26 ]. In a study by Azmi et al. comparing FGSI, UFGSI, ACCI, and LRINEC scores, all scoring systems were found to be significantly higher in non-survivors, but among these, FSGI was found to be superior to the other three scoring systems [ 15 ]. In our study, although all five scoring systems were found to be statistically higher in the non-survivors (p < 0.001), the UFSGI score and CUPI were found to be superior to the others in the ROC analysis. The general consensus among surgeons is that the earlier the necrotic tissue is debrided, the better is the outcome. However, how early is early enough is not well defined. Studies on this subject have mainly covered NSTIs, which are a more general definition. In a meta-analysis by Nawijn et al., the time from the onset of NSTI symptoms to hospital admission or surgery did not affect the mortality. Surgical treatment within 12 hours of hospital admission is necessary to reduce the mortality rate, but surgical treatment within 6 hours may further improve outcomes [ 27 ]. In a study by Gelbard et al., in patients with NSTI, including the pediatric age group, mortality was found to be 14% and 25.8% in patients with a time to surgery of less than and more than 12 hours, respectively [ 28 ]. In a systematic review evaluating patients with necrotizing fasciitis, the survival rate decreased from 93.2–75.2% when the time from admission to surgery increased from 24 to 48 hours [ 29 ]. Lin et al. found that the only significant factor in comparing surviving and deceased patients with FG was time to surgery. This period was found to be an average of 12.2 hours in survivors and 28.8 hours in non-survivors (p = 0.039). It has been stated that the appropriate time for surgical debridement of FG is the first 14 hours, and any delay is associated with increased mortality [ 30 ]. In their study evaluating 379 patients with FG, Sugihara et al. reported that 1, 2, 3, 4, and 5 days between admission and surgery resulted in 16%, 16.9%, 19%, 26.7%, and 25% mortality, respectively. Accordingly, in the multivariate regression analysis, it was stated that a time to surgery shorter than 48 hours significantly reduced mortality compared to surgery within 3–5 days (p = 0.031) [ 16 ]. In our study, in the multivariate regression analysis investigating the factors affecting mortality in patients with FG, time to surgery was found to be an independent predictor (p = 0.005). When the time to surgery was compared between survivors and non-survivors, the median time to surgery was 8 hours in survivors and 12.5 hours in non-survivors (p = 0.016). In our study, mortality was 13.3% in patients with a time of up to 12 hours until surgery and 24.2% in patients with a time of more than 12 hours until surgery (p = 0.009). Although our study included a certain population, it included a larger number of patients than similar studies. One of the limitations of this study was that not all scoring systems were used. In addition, the lack of detailed information on the type of microorganism isolated in the wound culture, antibiotic therapy administered, and antibiotic resistance pattern of patients with FG are among the limitations of this study. The retrospective single-center nature is a potential source of bias and another limitation that prevents the generalization of the study results. A multicenter prospective study with a larger sample size is required for further confirmation. CONCLUSION There are various clinical and laboratory findings and scoring systems that help predict the relationship between FG and mortality. According to our study, advanced age, increased RR, high serum chloride level, low serum bicarbonate level, low serum albümin level, and the time between hospital admission and surgery were independent predictors of FG mortality. Our study is the first and only study in the literature to show that high serum chloride increases mortality due to FG. If a scoring system is to be used for FG-related mortality, the UFGSI and CUPI scores should be evaluated primarily. Complete debridement is the basis for patient survival. Complete debridement within 12 hours of hospital admission is one of the most important factors in reducing mortality. Abbreviations FG Fournier’s gangrene BUN blood urea nitrogen ALT alanine aminotransferase AST aspartate aminotransferase ALP alkaline phospatase INR international normalized ratio CRP C-reactive protein FGSI Fournier Gangrene Severity Index UFGSI Uludağ Fournier Gangrene Severity Index ACCI Age-adjusted Charlson Comorbidity Index LRINEC Laboratory risk indicator for necrotizing fasciitis CUPI the Combined Urology and Plastics Index LOS length of hospital stay VAC vacuum assisted closure NSTI necrotizing soft tissue infections ICU intensive care unit ROC receiver operating characteristic AUC area under curves IRB institutional review board IQR interquartile range Declarations Authors’ Contributions: MH Ozbilen: Protocol/project development, Manuscript writing/editing MC Karabacak: Data analysis E Tekin: Data analysis UC Erdogan: Data analysis MÇ Çakıcı: Manuscript writing/editing M Yoldas: Data collection or management A Altunkol: Data collection or management E Alma: Protocol/project development H Ercil: Protocol/project development MZ Keskin: Protocol/project development Disclosure of potential conflicts of interest : The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article. Research involving Human Participants and/or Animals and Ethical approval: The study protocol was approved by Institutional Review Board (IRB No. 2025/01-33). The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments. Informed consent: Informed consent form was obtained from all patients. Acknowledgements: None References Eke N (2000) Fournier’s gangrene: a review of 1726 cases. Br J Surg 87(6):718–728. 10.1046/j.1365-2168.2000.01497.x Chennamsetty A, Khourdaji I, Burks F, Killinger KA (2015) Contemporary diagnosis and management of Fournier’s gangrene. Ther Adv Urol 7(4):203–215. 10.1177/1756287215584740 Ioannidis O, Kitsikosta L, Tatsis D et al (2017) Fournier’s Gangrene: Lessons Learned from Multimodal and Multidisciplinary Management of Perineal Necrotizing Fasciitis. Front Surg 4. 10.3389/fsurg.2017.00036 Sorensen MD, Krieger JN, Rivara FP (2009) Fournier’s Gangrene: population based epidemiology and outcomes. J Urol 181(5):2120–2126. 10.1016/j.juro.2009.01.034 Radcliffe RS, Khan MA (2020) Mortality associated with Fournier’s gangrene remains unchanged over 25 years. BJU Int 125(4):610–616. 10.1111/bju.14998 Bowen D, Juliebø-Jones P, Somani BK (2022) Global outcomes and lessons learned in the management of Fournier’s gangrene from high-volume centres: findings from a literature review over the last two decades. World J Urol 40(10):2399–2410. 10.1007/s00345-022-04139-4 Laor E, Palmer LS, Tolia BM, Reid RE, Winter HI (1995) Outcome Prediction in Patients with Fournier’s Gangrene. J Urol 154(1):89–92 Yilmazlar T, Ozturk E, Ozguc H, Ercan I, Vuruskan H, Oktay B (2010) Fournier’s gangrene: an analysis of 80 patients and a novel scoring system. Tech Coloproctol 14(3):217–223. 10.1007/s10151-010-0592-1 Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40(5):373–383. 10.1016/0021-9681(87)90171-8 Wong CH, Khin LW, Heng KS, Tan KC, Low CO (2004) The LRINEC (Laboratory Risk Indicator for Necrotizing Fasciitis) score: a tool for distinguishing necrotizing fasciitis from other soft tissue infections. Crit Care Med 32(7):1535–1541. 10.1097/01.ccm.0000129486.35458.7d Ghodoussipour SB, Gould D, Lifton J et al (2018) Surviving Fournier’s gangrene: Multivariable analysis and a novel scoring system to predict length of stay. J Plast Reconstr Aesthet Surg 71(5):712–718. 10.1016/j.bjps.2017.12.005 Alhubaishy B, Bahassan OM, Alsabban AE et al (2024) Variables that predict hospital stay and the outcome of Fournier gangrene at King Abdulaziz University Hospital: a retrospective study. BMC Urol 24(1). 10.1186/s12894-024-01496-7 You Q, Guan J, Wu B et al (2024) Fournier’s Gangrene: clinical case review and analysis of risk factors for mortality. BMC Surg 24(1):1–8. 10.1186/s12893-024-02547-4 Atilla A, Temocin F, Kuruoglu T, Kamali-Polat A (2023) Fournier’s Gangrene: Microbiological Profile and Risk Factors for Mortality: Review of 97 Cases. Infect Dis Clin Microbiol 5(1):13–22. 10.36519/idcm.2023.177 Azmi YA, Alkaff FF, Renaldo J et al (2023) Comparison of different scoring systems for predicting in-hospital mortality for patients with Fournier gangrene. World J Urol 41(10):2751–2757. 10.1007/s00345-023-04552-3 Sugihara T, Yasunaga H, Horiguchi H et al (2012) Impact of surgical intervention timing on the case fatality rate for Fournier’s gangrene: an analysis of 379 cases. BJU Int 110(11 Pt C). 10.1111/j.1464-410X.2012.11291.x Sparenborg JD, Brems JA, Wood AM, Hwang JJ, Venkatesan K (2019) Fournier’s gangrene: a modern analysis of predictors of outcomes. Transl Androl Urol 8(4):37478–37378. 10.21037/tau.2019.03.09 Berend K, Van Hulsteijn LH, Gans ROB (2012) Chloride: the queen of electrolytes? Eur J Intern Med 23(3):203–211. 10.1016/j.ejim.2011.11.013 Yaanallah S, Qahtani A (2023) Impact of hyperchloremia on inflammatory markers, serum creatinine, hemoglobin, and outcome in critically ill patients with COVID-19 infection LDH-Lactate Dehydrogenase, RRT-Renal Replacement Therapy. J Med Life 16. 10.25122/jml-2023-0013 Pfortmueller CA, Uehlinger D, von Haehling S, Schefold JC (2018) Serum chloride levels in critical illness—the hidden story. Intensive Care Med Exp 6(1):10. 10.1186/s40635-018-0174-5 Kellum JA, Song M, Li J (2004) Science review: Extracellular acidosis and the immune response: clinical and physiologic implications. Crit Care 8(5):331. 10.1186/cc2900 Moon JJ, Kim Y, Kim DK, Joo KW, Kim YS, Han SS (2020) Association of hypoalbuminemia with short-term and long-term mortality in patients undergoing continuous renal replacement therapy. Kidney Res Clin Pract 39(1):47–53. 10.23876/j.krcp.19.088 Shin IS, Gong SC, An S, Kim K (2023) Biomarkers to predict mortality in patients with Fournier’s gangrene admitted to the intensive care unit after surgery in South Korea. Acute Crit care 38(4):452–459. 10.4266/acc.2023.00766 Çomçalı B, Ceylan C, Özdemir BA, Ağaçkıran İ, Akıncı F (2022) Comparison of the newly developed Fournier’s gangrene mortality prediction model with existing models. Turkish J Trauma Emerg Surg 28(4):490. 10.14744/tjtes.2020.68137 Tufano A, Dipinto P, Passaro F et al (2023) The Value of Fournier’s Gangrene Scoring Systems on Admission to Predict Mortality: A Systematic Review and Meta-Analysis. J Pers Med 13(9). 10.3390/jpm13091283 Roghmann F, Von Bodman C, Löppenberg B, Hinkel A, Palisaar J, Noldus J (2012) 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 110(9):1359–1365. 10.1111/j.1464-410X.2012.11082.x Nawijn F, Smeeing DPJ, Houwert RM, Leenen LPH, Hietbrink F (2020) Time is of the essence when treating necrotizing soft tissue infections: a systematic review and meta-analysis. World J Emerg Surg 15(1). 10.1186/s13017-019-0286-6 Gelbard RB, Ferrada P, Dante Yeh D et al (2018) Optimal timing of initial debridement for necrotizing soft tissue infection: A Practice Management Guideline from the Eastern Association for the Surgery of Trauma. J Trauma Acute Care Surg 85(1):208–214. 10.1097/TA.0000000000001857 Goh T, Goh LG, Ang CH, Wong CH (2013) Early diagnosis of necrotizing fasciitis. Br J Surg 101(1):e119–e125. 10.1002/bjs.9371 Lin TY, Cheng IH, Ou CH et al (2019) Incorporating Simplified Fournier’s Gangrene Severity Index with early surgical intervention can maximize survival in high-risk Fournier’s gangrene patients. Int J Urol 26(7):737–743. 10.1111/iju.13989 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6671475","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":462657508,"identity":"3a3b7465-2866-4b70-804f-173db395f622","order_by":0,"name":"Mert Hamza 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10:09:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6671475/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6671475/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83681775,"identity":"e2b70ba9-1230-4f58-b77c-5d082e349069","added_by":"auto","created_at":"2025-05-30 16:22:01","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":126930,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"Figure1WJU.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6671475/v1/abdc252fe9a81f62aca81abf.jpeg"},{"id":99502727,"identity":"5a6c07e3-fbcc-4fad-b2f6-cc9e60c3d2a0","added_by":"auto","created_at":"2026-01-05 07:56:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1147261,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6671475/v1/3f5beb7a-8011-4000-8f8b-a6f38bfd0de6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prediction of Mortality in Patients with Fournier's Gangrene: Importance of Time to Surgery","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eNecrotizing soft tissue infection (NSTI) encompasses any infection involving any layer of soft tissue, including the superficial fascia, deep fascia, or muscle. Necrotizing fasciitis is a severe form of NSTI that affects the superficial fascia and subcutaneous tissues. Fournier's gangrene (FG) is form of necrotizing fasciitis that affects the superficial and deep tissues of the genital, scrotal, perineal, and perianal regions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In other words, FG is a subgroup of NSTIs. FG causes obliterative endarteritis. Necrosis occurs because of microvascular obstruction and impaired blood circulation. A hypoxic environment provides a basis for bacterial proliferation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. FG is associated with severe tissue damage, necrosis, and potential systemic complications following the spread of infection through soft tissues. It usually presents as signs of sepsis. It can progress to multiple organ failure and septic shock [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough it can affect both sexes and various age groups, it is a rare disease that usually occurs in men aged 50\u0026ndash;70. The incidence is estimated to be approximately 1.6 cases per 100000 men per year, representing less than 0.02% of hospitalized patients [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In a systematic review covering the years 1993\u0026ndash;2018, it was emphasized that mortality due to FG was around 40%, and there was no significant decrease in the 25-year period [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, another review conducted between 2000 and 2021 found that although the mortality rate due to FG was still high at 7.3%, it decreased compared to previous years owing to advances in both the recognition and treatment of the disease [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsidering the complex structure and severity of FG, it is important to identify prognostic factors to develop treatment strategies and predict the clinical outcomes. Various scoring systems have been developed to predict morbidity and mortality in FG patients. The Fournier Gangrene Severity Index (FGSI) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and Uludağ Fournier Gangrene Severity Index (UFGSI) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] are scoring systems developed to predict the mortality probability patients with FG. The Age-adjusted Charlson Comorbidity Index (ACCI) is a scoring system used to evaluate comorbidities and predict mortality [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) index is used to differentiate necrotizing fasciitis from other soft tissue infections based on laboratory findings [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The Combined Urology and Plastics Index (CUPI) is a scoring system used to predict the length of hospital stay (LOS) and morbidity in patients with FG [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEarly diagnosis of FG may result in reduced the damage to patients' health, increasing treatment success and survival rates. Based on this idea, we aimed to evaluate the clinical and laboratory findings that predict mortality, the role of the five existing scoring systems in mortality prediction, and the importance of the time from admission to the emergency department to surgery in patients with FG.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cp\u003eThis observational study was approved by the Institutional Review Board (IRB No. 2025/01\u0026ndash;33). Data of patients diagnosed with FG between 2007 and 2023 in one of the tertiary referral centers in our country were retrospectively examined. The diagnosis was made by physical examination, taking into account the presence of erythema, induration, tenderness, blackness, subcutaneous crepitation, necrosis, and repulsive fecaloid odor. Individuals with perianal, periurethral, or scrotal abscesses without necrosis or soft tissue extensions were excluded. As a result of the review, 354 patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years who were diagnosed with FG and had no missing data were included in the study.\u003c/p\u003e \u003cp\u003eA total of 354 patients who met the inclusion criteria were divided into survivors (n\u0026thinsp;=\u0026thinsp;293) and non-survivors (n\u0026thinsp;=\u0026thinsp;61). The following data were collected from FG patients admitted to hospital and compared between the two groups: patient demographics (age, gender, comorbidities), pulse, respiratory rate (RR), body temperature, disease extend, serum laboratory results (hematocrit, leukocyte, lymphocyte, neutrophil lymphocyte ratio (NLR), platelet, urea, blood urea nitrogen (BUN), creatinine, sodium, potassium, chloride, bicarbonate, calcium, alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), total bilirubin, total protein, albumin, international normalized ratio (INR), procalcitonin, c-reactive protein (CRP)), scoring system scores (FGSI score, UFGSI score, ACCI, LRINEC index, CUPI), microbial growth in wound culture, wound culture sterilization time, time to surgery, Vacuum-Assisted Closure (VAC) of a wound, VAC duration, definitive wound closure type, number of debridement in the operating room, need for intensive care unit (ICU), LOS, length of stay in the ICU. The time to surgery was defined as the time from the patient's arrival to the emergency department until surgical intervention.\u003c/p\u003e \u003cp\u003eMultivariate logistic regression analysis was applied to variables that were statistically significant in the univariate analysis regarding factors predicting mortality in patients with FG. Patients who had a time to surgery of more than 12 hours or less were compared in terms of mortality, need for ICU, number of debridements performed in the operating room, LOS, and length of stay in the ICU. The FGSI score, UFGSI score, ACCI, LRINEC index, and CUPI were analyzed using receiver operating characteristic (ROC) curves to predict the severity of FG.\u003c/p\u003e \u003cp\u003eAfter the vital signs of all patients stabilized, the patient was evaluated by the infectious disease clinic, and empirical antibiotics were started in the emergency room. Antibiotic treatment was changed if deemed necessary by the Infectious Disease Department based on the patient's wound culture results and clinical and laboratory findings. Surgical intervention was performed by debridement of the infected and necrotic tissues until healthy tissues were obtained. Depending on the progression of the infection, debridement was repeated in the operating room when the surgeon deemed it necessary. All patients who did not receive VAC treatment were followed up using conventional wound dressings. In patients receiving VAC treatment, the dressing was changed every 72 hours. The conventional wound dressing was changed daily with appropriate saline soaked gauze by the surgeon and nurse.\u003c/p\u003e \u003cp\u003eThe FGSI score is a numerical value created by combining the clinical and laboratory values. It is based on body temperature, pulse, RR, serum sodium, potassium, creatinine, hematocrit, leukocyte, and bicarbonate values. A score between 0 and 4 was assigned to each parameter. The overall score is calculated by summing the points assigned to each parameter. It has been reported that it is strongly associated with mortality rates [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The UFGSI score is another scoring system created by adding the disease extent and patient age to the FGSI score [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. ACCI is a widely used comorbidity scoring system. It has 20 parameters. It is used to evaluate mortality risk based on the severity and number of diseases that the patient has [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The LRINEC index is a laboratory-based scoring system that can be used to detect early clinical cases of necrotizing fasciitis. It was created based on serum CRP, leukocyte, hemoglobin, sodium, creatinine, and glucose levels. A maximum of 13 points was obtained by assigning points to each parameter [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The CUPI is a scoring system used for the LOS of patients with FG. In addition to age, serum hematocrit, calcium, ALP, albumin, INR, bicarbonate, total bilirubin, and BUN values were considered. A total score of up to 15 was obtained for these parameters [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis:\u003c/h2\u003e \u003cp\u003eThe one-sample Kolmogorov Smirnov test was used to determine whether the data showed a normal distribution for numerical variables. The mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation was found in the data with normal distribution, and median (interquartile range (IQR)) values ​​were recorded in the data without normal distribution. Numerical variables were compared using the Student's t-test when parametric test criteria were found. In the absence of these criteria, the Mann-Whitney U test was used. In addition, the Mann-Whitney U test was used to compare ordinal categorical variables. Pearson\u0026rsquo;s chi-squared test was used to determine whether there was a difference between the percentages of categorical variables. Binary logistic regression analysis was used to identify the independent risk factors for mortality in patients with FG. Multivariate logistic regression analysis was performed for variables that were statistically significant in univariate analysis. A ROC curve was generated by plotting the sensitivity as a function of (1-specificity) to investigate the predictive values of the scoring systems predicting the severity of FG. For all the tests, the probability of the first type of error was α\u0026thinsp;=\u0026thinsp;0.05. Statistical analysis was performed using IBM SPSS 22.0 package program.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eConsidering the inclusion and exclusion criteria, 354 patients followed up due to FG were included in the study. Of these, 293 patients were defined as survivors and 61 as non-survivors. The demographic, clinical, and laboratory findings of the two groups are compared in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mortality rate of FG was 17.2%. The mean age was 55.3 in survivors and 65.6 in non-survivors, and a statistically significant difference was found (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). While the mean RR was 19.5 in survivors, it was 22.5 in non-survivors, and a statistically significant difference was observed (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Female sex, comorbidities, increased pulse rate, and advanced disease extension were more common in the deceased patients. When laboratory findings were evaluated, serum NLR (p\u0026thinsp;=\u0026thinsp;0.046), chloride (p\u0026thinsp;=\u0026thinsp;0.025), creatinine (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), INR (p\u0026thinsp;=\u0026thinsp;0.001), total bilirubin (p\u0026thinsp;=\u0026thinsp;0.001), BUN (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and procalcitonin (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were found to be high, while hematocrit (p\u0026thinsp;=\u0026thinsp;0.004), bicarbonate (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), albumin (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and calcium (p\u0026thinsp;=\u0026thinsp;0.003) were found to be low in non-survivors. No significant differences were found between the two groups in terms of serum leukocyte (p\u0026thinsp;=\u0026thinsp;0.951), sodium (p\u0026thinsp;=\u0026thinsp;0.934), potassium (p\u0026thinsp;=\u0026thinsp;0.544), CRP (p\u0026thinsp;=\u0026thinsp;0.309), and ALP (p\u0026thinsp;=\u0026thinsp;0.505) levels.\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e Grouping of demographic, clinical and laboratory data according to mortality (SD: standard deviation, n: number, min: minute, BUN: blood urea nitrogen, ALT: alanine aminotransferase, AST: aspartate aminotransferase, ALP: alkaline phospatase, INR: international normalized ratio, CRP: C-reactive protein, FGSI: Fournier Gangrene Severity Index, UFGSI: Uludağ Fournier Gangrene Severity Index, ACCI: Age-adjusted Charlson Comorbidity Index, LRINEC: Laboratory risk indicator for necrotizing fasciitis, CUPI: \u003cem\u003ethe Combined Urology and Plastics Index\u003c/em\u003e, VAC: vacuum assisted closure, ICU: intensive care unit, \u003csup\u003e\u0026nbsp;T\u003c/sup\u003e:Student T test, \u003csup\u003eM\u003c/sup\u003e:Mann-Whitney U test, \u003csup\u003eP\u003c/sup\u003e:Pearson\u0026rsquo;s Chi-square test)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eSurvivors\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(n=293)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eNon-survivors\u003c/p\u003e\n \u003cp\u003e(n=61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eAge, years, mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e55.3\u0026plusmn;13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e65.6\u0026plusmn;13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eGender, n (%)\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e82 (28)\u003c/p\u003e\n \u003cp\u003e211 (72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e27 (44.3)\u003c/p\u003e\n \u003cp\u003e34 (55.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.012\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003ePresence of risk factors, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e247 (84.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e56 (91.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.129\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003ePulse (beats per min) ,mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e92.3\u0026plusmn;15.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e100.4\u0026plusmn;17.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eRespiratory rate ( breaths per min) , mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e19.5\u0026plusmn;4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e22.6\u0026plusmn;5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eBody temperature (\u0026deg;C), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e36.6 (36.0-39.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e37 (36.4-41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eComorbidities, n (%)\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n \u003cp\u003eCancer\u003c/p\u003e\n \u003cp\u003eImmunosuppression\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eObesity\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTrauma/Surgery\u003c/p\u003e\n \u003cp\u003eCardiovascular\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eChronic Kidney Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e46 (15.7)\u003c/p\u003e\n \u003cp\u003e81 (27.6)\u003c/p\u003e\n \u003cp\u003e21 (7.2)\u003c/p\u003e\n \u003cp\u003e5 (1.7)\u003c/p\u003e\n \u003cp\u003e24 (8.2)\u003c/p\u003e\n \u003cp\u003e45 (15.4)\u003c/p\u003e\n \u003cp\u003e60 (20.5)\u003c/p\u003e\n \u003cp\u003e11 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5 (8.2)\u003c/p\u003e\n \u003cp\u003e8 (13.1)\u003c/p\u003e\n \u003cp\u003e3 (4.9)\u003c/p\u003e\n \u003cp\u003e3 (4.9)\u003c/p\u003e\n \u003cp\u003e1 (1.6)\u003c/p\u003e\n \u003cp\u003e13 (21.3)\u003c/p\u003e\n \u003cp\u003e24 (39.3)\u003c/p\u003e\n \u003cp\u003e4 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.003\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eDisease extend, n (%)\u003c/p\u003e\n \u003cp\u003eUrogenital\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eAnorectal\u003c/p\u003e\n \u003cp\u003eExtending into the pelvis\u003c/p\u003e\n \u003cp\u003eExtending outside the pelvis\u003c/p\u003e\n \u003cp\u003eAnogenital\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e82 (28)\u003c/p\u003e\n \u003cp\u003e108 (36.9)\u003c/p\u003e\n \u003cp\u003e26 (8.9)\u003c/p\u003e\n \u003cp\u003e48 (16.4)\u003c/p\u003e\n \u003cp\u003e29 (9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13 (21.3)\u003c/p\u003e\n \u003cp\u003e13 (21.3)\u003c/p\u003e\n \u003cp\u003e7 (11.5)\u003c/p\u003e\n \u003cp\u003e22 (36.1)\u003c/p\u003e\n \u003cp\u003e6 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.005\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eHematocrit (%), mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e34.2\u0026plusmn;7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e31.5\u0026plusmn;5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.004\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eLeukocyte (10\u003csup\u003e3\u003c/sup\u003e/\u0026mu;L), mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e16.9\u0026plusmn;7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e16.8\u0026plusmn;8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.951\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eLymphocyte (10\u003csup\u003e3\u003c/sup\u003e/\u0026mu;L), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e1.3 (0.2-9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e1 (0.1-8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.005\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eNeutrophil lymphocyte ratio, median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e12.1 (0.8-119.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e16.8 (1.3-133)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.046\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003ePlatelet (10\u003csup\u003e3\u003c/sup\u003e/\u0026mu;L), mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e323.7\u0026plusmn;144.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e287.3\u0026plusmn;181.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.088\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eUrea (mg/dL), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e43 (13-324)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e78 (7-447)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eBUN (mg/dL), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e20.1 (6.1-151.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e36.4 (3.3-208.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eCreatinine (mg/dL), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e1.1 (0.4-10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e1.5 (0.4-7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eSodium (mmol/L), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e134 (115-148)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e134 (117-176)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.934\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003ePotassium (mmol/L), mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e4.3\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e4.3\u0026plusmn;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.544\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eChloride (mmol/L), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e99 (79-112)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e101 (78-144)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.025\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eBicarbonate (venous) (mmol/L), mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e22.9\u0026plusmn;2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e19.1\u0026plusmn;4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eCalcium (mg/dL), mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e8.6\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e8.3\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.003\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eALT (U/L), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e19 (3-358)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e22 (4-346)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.692\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eAST (U/L), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e23 (7-493)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e37 (5-470)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eALP (U/L), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e97 (46-520)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e100 (43-555)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.505\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eTotal bilirubin (mg/dL), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e0.6 (0.01-3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e0.8 (0.05-5.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.001\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eTotal protein (g/dL), mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e5.7\u0026plusmn;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e5.1\u0026plusmn;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eAlbumin (g/dL), mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e2.9\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e2.2\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eINR, median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e1.1 (0.1-2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e1.2 (0.12-52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.001\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eProcalcitonin (\u0026mu;g/L), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e0.4 (0-75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e1.1 (0.03-63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eCRP (mg/dL), mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e165.5\u0026plusmn;136.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e185.0\u0026plusmn;130.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.309\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eFGSI score, mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e3.5\u0026plusmn;3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e6.9\u0026plusmn;4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eUFGSI score, mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e5.7\u0026plusmn;4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e10.5\u0026plusmn;5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eACCI, mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e1.8\u0026plusmn;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e2.9\u0026plusmn;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eLRINEC index, mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e5.5\u0026plusmn;3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e7.1\u0026plusmn;3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eCUPI, mean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e4.3\u0026plusmn;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e5.9\u0026plusmn;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eT\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eMicrobial growth in wound culture, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e163 (60.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e34 (59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.869\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eWound culture sterilization time (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e17.6\u0026plusmn;18.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eTime to surgery (hours), median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e8 (0.5-168)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e12.5 (1-480)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.016\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eSurgery after 24 hours, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e50 (17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e15 (24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.167\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eSurgery after 12 hours, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e97 (33.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e31 (50.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.009\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eSurgery after 6 hours, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e176 (60.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e40 (65.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.422\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eSurgery after 3 hours, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e241 (82.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e52 (85.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.573\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eSurgery after 1 hour, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e274 (93.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e58 (95.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.645\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eVAC of a wound, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e83 (28.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e16 (26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.740\u003csup\u003e\u0026nbsp;P\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eVAC duration, median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e15 (3-60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e13.5 (1-85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.875\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eDefinitive wound closure type, n (%)\u003c/p\u003e\n \u003cp\u003ePrimary\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003cp\u003eGraft-Flap\u003c/p\u003e\n \u003cp\u003eExitus \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e121 (41.3)\u003c/p\u003e\n \u003cp\u003e111 (37.9)\u003c/p\u003e\n \u003cp\u003e61 (20.8)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2 (3.3)\u003c/p\u003e\n \u003cp\u003e2 (3.3)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e57 (93.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eNumber of debridement in the operating room, median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e1 (1-13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e1 (1-20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.966\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eNeed for ICU, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e109 (37.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e56 (91.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eLength of hospital stay, days, median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e15 (1-93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e14 (1-120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.374\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eLength of stay in the ICU, days, median (min-max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e3 (1-35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e6 (1-90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.001\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e \u003cp\u003eThe mean FGSI, UFGSI, ACCI, LRINEC, and CUPI scores were 3.5, 5.7, 1.8, 5.5, 4.3 in survivors, and 6.9, 10.5, 2.9, 7.1, 5.9 in non-survivors, respectively. All of these scores were statistically higher in deceased patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all). In the comparison of both groups, the median time to surgery was 8 hours in the surviving patients and 12.5 hours in those who died (p\u0026thinsp;=\u0026thinsp;0.016). Time to surgery longer than 12 hours was associated with increased mortality (p\u0026thinsp;=\u0026thinsp;0.009).\u003c/p\u003e \u003cp\u003eThe results of the multivariate logistic regression analysis of the factors predicting mortality in patients with FG are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Multivariate analysis showed that advanced age (p\u0026thinsp;=\u0026thinsp;0.001), increased RR (p\u0026thinsp;=\u0026thinsp;0.003), high serum chloride level (p\u0026thinsp;=\u0026thinsp;0.027), low serum bicarbonate level (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), low serum albumin level (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and prolonged time to surgery (p\u0026thinsp;=\u0026thinsp;0.005) were independent predictors of mortality in FG.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate logistic regression analysis of factors predicting mortality in patients with Fournier gangrene (n: number, BUN: blood urea nitrogen, ALT: alanine aminotransferase, AST: aspartate aminotransferase, ALP: alkaline phospatase, INR: international normalized ratio, CRP: C-reactive protein, OR: odds ratio, FGSI: Fournier Gangrene Severity Index, UFGSI: Uludağ Fournier Gangrene Severity Index, ACCI: Age-adjusted Charlson Comorbidity Index, LRINEC: Laboratory risk indicator for necrotizing fasciitis, CUPI: \u003cem\u003ethe Combined Urology and Plastics Index\u003c/em\u003e, VAC: vacuum assisted closure, ICU: intensive care unit)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003eBinary\u0026nbsp;Logistic Regression (n\u0026thinsp;=\u0026thinsp;354)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eUnivariate Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003eMultivariate Model\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (reference: female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresence of risk factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody temperature (\u0026deg;C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease extend (reference: urogenital)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematocrit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukocyte\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil lymphocyte ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChloride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBicarbonate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.860\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal bilirubin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.977\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcalcitonin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFGSI score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUFGSI score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLRINEC Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCUPI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to surgery (hours)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔ-hours\u0026thinsp;\u0026gt;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of debridement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVAC duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhen the survivors and the deceased were compared (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), it was determined that the time to surgery exceeding 12 hours was significantly different between the two groups. For this reason, patients whose time to surgery exceeded 12 hours and those who did not exceed 12 hours were evaluated separately (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, patients with a time to surgery of up to 12 hours (n\u0026thinsp;=\u0026thinsp;226) and those with a time to surgery of more than 12 hours (n\u0026thinsp;=\u0026thinsp;128) were compared with each other. Accordingly, mortality was 13.3% in patients with a time of up to 12 hours until surgery and 24.2% in patients with a time of more than 12 hours until surgery (p\u0026thinsp;=\u0026thinsp;0.009). In addition, a time to surgery longer than 12 hours was associated with longer LOS (p\u0026thinsp;=\u0026thinsp;0.001) and longer length of stay in the ICU (p\u0026thinsp;=\u0026thinsp;0.044). No significant difference was found in the need for ICU admission (p\u0026thinsp;=\u0026thinsp;0.459) and the number of debridements in the operating room (p\u0026thinsp;=\u0026thinsp;0.774).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of time to surgery longer than 12 hours on mortality and length of hospital stay (n: number, ICU: intensive care unit, \u003csup\u003eM\u003c/sup\u003e: Mann-Whitney U test, \u003csup\u003eP\u003c/sup\u003e: Pearson\u0026rsquo;s Chi-square test)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΔ-hours\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;12 (n\u0026thinsp;=\u0026thinsp;226)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eΔ-hours\u0026thinsp;\u0026gt;\u0026thinsp;12 (n\u0026thinsp;=\u0026thinsp;128)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (24.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeed for ICU, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102 (45.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (49.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.459\u003csup\u003eP\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of debridement in the operating room, median (min-max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1\u0026ndash;20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1\u0026ndash;18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.774\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of hospital stay, days, median (min-max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (1-103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (1-120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of stay in the ICU, days, median (min-max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (1\u0026ndash;64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (1\u0026ndash;90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.044\u003csup\u003eM\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDetails of the ROC analysis of the scoring systems predicting FG severity were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The area under ROC curve (AUC) values of FGSI, UFGSI, ACCI, LRINEC and CUPI score were 0.719, 0.751, 0.641, 0.636, and 0.751, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn a disease with high mortality rates, such as FG, determining the factors that affect the course of the disease is one of the most important elements. By determining these factors, it is possible to prevent the morbidity and mortality associated with FG [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdvancing age causes a decrease in physiological functions and a weakening of the immune system. This can lead to an increased risk of infection and a reduced ability to fight infection. At the same time, comorbidities that may occur due to advanced age can cause a more dramatic FG course [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. While age was not included in the FSGI and LRINEC indices, it was one of the parameters in the UFGSI and CUPI scores. Although there are studies claiming the contrary, [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] many have stated that advanced age is associated with mortality due to FG [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In a regression analysis of mortality due to FG in the study by Sugihara et al., advanced age was found to be an independent risk factor, similar to our study [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRR is one of the parameters of the two most commonly used scoring systems for FG (FGSI and UFGSI). Some studies have shown that RR is higher in patients who died, and [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] as well as there are some studies have shown that there is no significant difference between survivors and non-survivors [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In our study, multivariate regression analysis showed that an increased RR was an independent predictor of mortality (p\u0026thinsp;=\u0026thinsp;0.003).\u003c/p\u003e \u003cp\u003eChloride is an electrolyte that is often overlooked, but has important effects on the patient, which can lead to many disorders, including disorders of hemostasis, acid-base balance, and immunomodulation [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Increased serum chloride levels can lead to metabolic acidosis, renal failure, and hemodynamic instability [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Although literature indicates that mortality rates increase in patients with hyperchloremia, it is not yet clear whether the effect of chloride levels on mortality is direct or indirect [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In our study, high serum chloride level was found to be an independent predictor of FG-related mortality. Based on this result, our study is the first and only study in the literature to show the existence of a relationship between serum chloride levels and FG-related mortality.\u003c/p\u003e \u003cp\u003eLow serum bicarbonate level is an indicator of metabolic acidosis. In metabolic acidosis, interleukin production is stimulated by macrophages and lymphocyte function is suppressed. This leads to increased inflammation and an impaired immune response [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Studies have generally reported that serum bicarbonate levels were significantly lower in patients who died of FG [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In our study, a low serum bicarbonate level was found to be an independent predictor of FG-related mortality (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eSerum albumin is known as a negative acute phase reactant. Hypoalbuminemia can be observed in patients with metabolic stress. Serum albumin levels may reflect the patient's nutritional status and immune function [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Low serum albumin levels may play a role in disease progression, and advanced disease may cause a decrease in serum albumin levels. Low serum albumin level was found to be an independent risk factor for mortality related to FG in the multivariate regression analysis in the study by Shin et al. and in the study by \u0026Ccedil;om\u0026ccedil;alı et al, as in our study [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMore than 10 scoring systems, both specific and non-specific to FG, have been investigated to predict mortality in FG [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Scoring systems should be easy to calculate, relatively less time consuming, and have high sensitivity and specificity. There is no clear consensus in the literature on whether scoring systems are useful in FG, and if so, which system should be used first [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe FGSI is the first and most commonly used FG-specific scoring method; however, it is time consuming to calculate. The threshold value for the FGSI was found to be 9. If the score was higher than 9, the mortality rate would be 75%, and if it was lower than 9, the mortality rate would drop to 22% [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Sparenborg et al. emphasized the necessity of adding diabetes to FGSI score [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The threshold value for the UFGSI score was 9, which is similar to the FGSI score. The authors stated that the predictive power was higher and emphasized that if the score was higher than 9, the mortality rate would be 94%, whereas when it was 9 or less, this rate would drop to 18% [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This calculation is time consuming. Although the ACCI is not a scoring system specific to FG, it is used to evaluate the mortality risk based on the severity and number of diseases the patient has. It is easy to calculate and has validation for a large number of diseases. In a study by Sugihara et al., increased ACCI was found to be an independent risk factor for FG-related mortality in multivariate regression analysis [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. LRINEC index is an easy-to-calculate scoring system. It is not specific to FG, and was developed for diagnostic purposes. In the LRINEC index, patients were divided into three risk categories for NSTIs: low (LRINEC index\u0026thinsp;\u0026le;\u0026thinsp;5), intermediate (LRINEC index 6\u0026ndash;7) and high (LRINEC index\u0026thinsp;\u0026ge;\u0026thinsp;8). A LRINEC index of 6 and above increases the suspicion of necrotizing fasciitis, and a score of 8 or above is a strong predictor of this disease [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The CUPI is specific for FG and is the first scoring system that prioritizes morbidity and LOS in patients with FG. The threshold value for the CUPI was 5. For values 5 and​​ below, the mean LOS was 25 days, whereas for values ​​above 5, the mean LOS was 71 days [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. CUPI is a scoring system that has not been extensively studied.\u003c/p\u003e \u003cp\u003eIf we evaluate the studies comparing the scoring systems predicting FG-related mortality, in the meta-analysis conducted by Tufano et al. investigating the predictive values ​​of FGSI and UFGSI scores for mortality in patients with FG, they stated that mortality increased as scores increased in both scoring systems, but the accuracy rate of UFGSI was higher [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Atilla et al. stated that both FGSI and UFGSI scores have a strong predictive value for mortality, whereas LRINEC is weak [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Among the studies comparing FGSI, UFGSI, and ACCI, Although \u0026Ccedil;om\u0026ccedil;alı et al. found that UFGSI has a higher prediction than FGSI and ACCI [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], Roghmann et al. stated that all three scoring systems can be used to predict mortality; however, if possible, ACCI, which is easier to calculate and generally accepted, should be preferred [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In a study by Azmi et al. comparing FGSI, UFGSI, ACCI, and LRINEC scores, all scoring systems were found to be significantly higher in non-survivors, but among these, FSGI was found to be superior to the other three scoring systems [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In our study, although all five scoring systems were found to be statistically higher in the non-survivors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the UFSGI score and CUPI were found to be superior to the others in the ROC analysis.\u003c/p\u003e \u003cp\u003eThe general consensus among surgeons is that the earlier the necrotic tissue is debrided, the better is the outcome. However, how early is early enough is not well defined. Studies on this subject have mainly covered NSTIs, which are a more general definition. In a meta-analysis by Nawijn et al., the time from the onset of NSTI symptoms to hospital admission or surgery did not affect the mortality. Surgical treatment within 12 hours of hospital admission is necessary to reduce the mortality rate, but surgical treatment within 6 hours may further improve outcomes [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In a study by Gelbard et al., in patients with NSTI, including the pediatric age group, mortality was found to be 14% and 25.8% in patients with a time to surgery of less than and more than 12 hours, respectively [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In a systematic review evaluating patients with necrotizing fasciitis, the survival rate decreased from 93.2\u0026ndash;75.2% when the time from admission to surgery increased from 24 to 48 hours [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Lin et al. found that the only significant factor in comparing surviving and deceased patients with FG was time to surgery. This period was found to be an average of 12.2 hours in survivors and 28.8 hours in non-survivors (p\u0026thinsp;=\u0026thinsp;0.039). It has been stated that the appropriate time for surgical debridement of FG is the first 14 hours, and any delay is associated with increased mortality [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In their study evaluating 379 patients with FG, Sugihara et al. reported that 1, 2, 3, 4, and 5 days between admission and surgery resulted in 16%, 16.9%, 19%, 26.7%, and 25% mortality, respectively. Accordingly, in the multivariate regression analysis, it was stated that a time to surgery shorter than 48 hours significantly reduced mortality compared to surgery within 3\u0026ndash;5 days (p\u0026thinsp;=\u0026thinsp;0.031) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In our study, in the multivariate regression analysis investigating the factors affecting mortality in patients with FG, time to surgery was found to be an independent predictor (p\u0026thinsp;=\u0026thinsp;0.005). When the time to surgery was compared between survivors and non-survivors, the median time to surgery was 8 hours in survivors and 12.5 hours in non-survivors (p\u0026thinsp;=\u0026thinsp;0.016). In our study, mortality was 13.3% in patients with a time of up to 12 hours until surgery and 24.2% in patients with a time of more than 12 hours until surgery (p\u0026thinsp;=\u0026thinsp;0.009).\u003c/p\u003e \u003cp\u003eAlthough our study included a certain population, it included a larger number of patients than similar studies. One of the limitations of this study was that not all scoring systems were used. In addition, the lack of detailed information on the type of microorganism isolated in the wound culture, antibiotic therapy administered, and antibiotic resistance pattern of patients with FG are among the limitations of this study. The retrospective single-center nature is a potential source of bias and another limitation that prevents the generalization of the study results. A multicenter prospective study with a larger sample size is required for further confirmation.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThere are various clinical and laboratory findings and scoring systems that help predict the relationship between FG and mortality. According to our study, advanced age, increased RR, high serum chloride level, low serum bicarbonate level, low serum alb\u0026uuml;min level, and the time between hospital admission and surgery were independent predictors of FG mortality. Our study is the first and only study in the literature to show that high serum chloride increases mortality due to FG. If a scoring system is to be used for FG-related mortality, the UFGSI and CUPI scores should be evaluated primarily. Complete debridement is the basis for patient survival. Complete debridement within 12 hours of hospital admission is one of the most important factors in reducing mortality.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFournier\u0026rsquo;s gangrene\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBUN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eblood urea nitrogen\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ealanine aminotransferase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAST\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003easpartate aminotransferase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ealkaline phospatase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eINR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einternational normalized ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eC-reactive protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFGSI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFournier Gangrene Severity Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUFGSI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUludağ Fournier Gangrene Severity Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAge-adjusted Charlson Comorbidity Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLRINEC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLaboratory risk indicator for necrotizing fasciitis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCUPI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ethe Combined Urology and Plastics Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elength of hospital stay\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVAC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003evacuum assisted closure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSTI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enecrotizing soft tissue infections\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintensive care unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ereceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003earea under curves\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIRB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einstitutional review board\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMH Ozbilen:\u0026nbsp;\u003c/strong\u003eProtocol/project development, Manuscript writing/editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMC Karabacak:\u0026nbsp;\u003c/strong\u003eData analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eE Tekin:\u0026nbsp;\u003c/strong\u003eData analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUC Erdogan:\u0026nbsp;\u003c/strong\u003eData analysis\u003c/p\u003e\n\u003cp\u003eM\u0026Ccedil; \u0026Ccedil;akıcı:\u0026nbsp;Manuscript writing/editing\u003c/p\u003e\n\u003cp\u003eM Yoldas:\u0026nbsp;Data collection or management\u003c/p\u003e\n\u003cp\u003eA Altunkol:\u0026nbsp;Data collection or management\u003c/p\u003e\n\u003cp\u003eE Alma:\u0026nbsp;Protocol/project development\u003c/p\u003e\n\u003cp\u003eH Ercil:\u0026nbsp;Protocol/project development\u003c/p\u003e\n\u003cp\u003eMZ Keskin: Protocol/project development\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure of potential conflicts of interest\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e The author(s) received no financial support for the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch involving Human Participants and/or Animals\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and \u003cstrong\u003eEthical approval:\u003c/strong\u003e\u003c/strong\u003e The study protocol was approved by\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eInstitutional Review Board (IRB No. 2025/01-33).\u0026nbsp;The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent:\u0026nbsp;\u003c/strong\u003eInformed consent form was obtained from all patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e None\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEke N (2000) Fournier\u0026rsquo;s gangrene: a review of 1726 cases. 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Int J Urol 26(7):737\u0026ndash;743. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/iju.13989\u003c/span\u003e\u003cspan address=\"10.1111/iju.13989\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Fournier’s gangrene, mortality, scoring systems, time to surgery, emergency","lastPublishedDoi":"10.21203/rs.3.rs-6671475/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6671475/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eTo evaluate the clinical and laboratory findings that predict mortality,the role of five scoring systems in mortality prediction,and the importance of the time from admission to emergency department to surgery in Fournier\u0026rsquo;s Gangrene(FG) patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 354 patients who were diagnosed with FG were divided into survivors (n\u0026thinsp;=\u0026thinsp;293) and non-survivors (n\u0026thinsp;=\u0026thinsp;61).Multivariate logistic regression analysis was applied for variables that were statistically significant in the univariate analysis regarding factors predicting mortality in patients with FG.Fournier Gangrene Severity Index(FGSI) score,Uludağ Fournier Gangrene Severity Index(UFGSI) score,Age-adjusted Charlson Comorbidity Index(ACCI),Laboratory risk indicator for necrotizing fasciitis(LRINEC) index and \u003cem\u003eThe Combined Urology and Plastics Index(CUPI)\u003c/em\u003e were analyzed with receiver operating characteristic(ROC) curve for the predicting the mortality of FG.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mortality rate due to FG was found to be 17.2%.Advanced age,increased respiratory rate,high serum chloride,low serum bicarbonate,low serum albumin,and the time between hospital admission and surgery are independent predictors of FG mortality in the multivariate analysis.The area under ROC curve (AUC) values of FGSI score,UFGSI score,ACCI,LRINEC index,CUPI were found to be 0.719,0.751,0.641,0.636,0.751,respectively.Mortality was 13.3% in patients with a time of up to 12 hours until surgery,and 24.2% in patients with a time of more than 12 hours until surgery.Also,a time to surgery longer than 12 hours was associated with longer length of hospital stay (p\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIf a scoring system is to be used for FG-related mortality,the UFGSI score and CUPI should be evaluated primarily.One of the most important aspects of reducing mortality is complete debridement within 12 hours of hospital admission.\u003c/p\u003e","manuscriptTitle":"Prediction of Mortality in Patients with Fournier's Gangrene: Importance of Time to Surgery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-30 16:13:57","doi":"10.21203/rs.3.rs-6671475/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"54e0ae10-a88d-4304-b074-8e2eb149f3f1","owner":[],"postedDate":"May 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-05T07:55:46+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-30 16:13:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6671475","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6671475","identity":"rs-6671475","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}