Background: Necrotizing fasciitis (NF) is a life-threatening infection of the skin and soft tissue that spreads quickly and requires immediate surgery and medical treatment. Amputation or radical debridement of necrotic tissue is generally always required. The risks and benefits of both the surgical options are weighed before deciding whether to amputate or debride. This study set forth to create an easy-to-use risk scoring system for predicting the risk scoring system for amputation in patients with NF (ANF). Methods: This retrospective study included 1,506 patients diagnosed with surgically confirmed NF at three general hospitals in Thailand from January 2009 to December 2012. All diagnoses were made by surgeons who strictly observed the guidelines for skin and soft tissue infections produced by the Infectious Diseases Society of America. Patients were randomly allocated to either the derivation (n = 1,193) or validation (n = 313) cohort. Clinical risk factors assessed at the time of recruitment were used to create the risk score, which was then developed using logistic regression. The regression coefficients were converted into item scores, and the total score was calculated. Results: The following four clinical predictors were used to create the model: female gender, diabetes mellitus, wound appearance stage 3 (skin necrosis and gangrene), and creatinine ≥1.6 mg/dL. Using the area under the receiver operating characteristic curve (AuROC), the ANF system showed moderate power (78.68%) to predict amputation in patients with NF with excellent calibration (Hosmer-Lemeshow χ2 = 2.59; p = 0.8586). The positive likelihood ratio of amputation in low-risk (score ≤ 4) and high-risk (score ≥ 7) patients was 2.17 (95%CI: 1.66-2.82) and 6.18 (95%CI: 4.08-9.36), respectively. The ANF system showed good performance (AuROC 76.82%) when applied in the validation cohort. Conclusion: The developed ANF risk scoring system, which includes four easy to obtain predictors, provides physicians with prediction indices for amputation in patients with NF. This model will assist clinicians with surgical decision-making in this time-sensitive clinical setting.
Necrotizing fasciitis (NF) is a life-threatening soft tissue infection that rapidly progresses and requires urgent surgery and medical therapy. If treatment is delayed, the likelihood of an unfavorable outcome, including death, is significantly increased. The goal of this study was to develop and validate a novel scoring model for predicting mortality in patients with NF. The proposed system is hereafter referred to as the Mortality in Necrotizing Fasciitis (MNF) scoring system. A total of 1503 patients with NF were recruited from 3 provincial hospitals in Thailand during January 2009 to December 2012. Patients were randomly allocated into either the derivation cohort (n = 1192) or the validation cohort (n = 311). Clinical risk factors used to develop the MNF scoring system were determined by logistic regression. Regression coefficients were transformed into item scores, the sum of which reflected the total MNF score. The following 6 clinical predictors were included: female gender; age > 60 years; white blood cell (WBC) ≤5000/mm3; WBC ≥ 35,000/mm3; creatinine ≥ 1.6 mg/dL, and pulse rate > 130/min. Area under the receiver operating characteristic curve (AuROC) analysis showed the MNF scoring system to have moderate power for predicting mortality in patients with NF (AuROC: 76.18%) with good calibration (Hosmer-Lemeshow χ2: 1.01; P = .798). The positive likelihood ratios of mortality in patients with low-risk scores (≤2.5) and high-risk scores (≥7) were 11.30 (95% confidence interval [CI]: 6.16-20.71) and 14.71 (95%CI: 7.39-29.28), sequentially. When used to the validation cohort, the MNF scoring system presented good performance with an AuROC of 74.25%. The proposed MNF scoring system, which includes 6 commonly available and easy-to-use parameters, was shown to be an effective tool for predicting mortality in patients with NF. This validated instrument will help clinicians identify at-risk patients so that early investigations and interventions can be performed that will reduce the mortality rate among patients with NF.