Development and validation of a necrotizing soft-tissue infection mortality risk calculator using NSQIP.

BACKGROUND

Necrotizing soft-tissue infections (NSTI) are a group of uncommon, rapidly progressive infections requiring prompt surgical debridement and systemic support. A previous attempt to define risk factors for mortality from NSTI had multiple limitations. The objective of this study was to develop and validate a 30-day postoperative mortality risk calculator for patients with NSTI using NSQIP.

STUDY

DESIGN

The NSQIP Participant Use Files (2005-2010) were used as the primary data source. Patients diagnosed with NSTI were identified by ICD-9 codes. Multiple logistic regression analysis identified key preoperative variables predicting mortality. Bootstrap analysis was used to validate the model.

RESULTS

In 1,392 identified NSTI cases, demographics were as follows: 42% were female, median age was 55 years (interquartile range 46 to 63 years), and median body mass index was 32 kg/m(2) (interquartile range 26 to 40 kg/m(2)). Thirty-day mortality was 13%. Seven independent variables were identified that correlated with mortality: age older than 60 years (odds ratio [OR] = 2.5; 95% CI 1.7-3.6), functional status (partially dependent: OR = 1.6; 95% CI 1.0-2.7; totally dependent: OR = 2.3; 95% CI 1.4-3.8), requiring dialysis (OR = 1.9; 95% CI 1.2-3.1), American Society of Anesthesiologists class 4 or higher (OR = 3.6; 95% CI 2.3-5.6), emergent surgery (OR = 1.6; 95% CI 1.0-2.3), septic shock (OR = 2.4; 95% CI 1.6-3.6), and low platelet count (<50K/μL: OR = 3.5; 95% CI 1.6-7.4; <150K/μL but >50K/μL: OR = 1.9; 95% CI 1.2-2.9). The receiver operating characteristic area was 0.85 (95% CI 0.82-0.87), which indicated a strong predictive model. Using bootstrap validation, the optimism-corrected receiver operating characteristic area was 0.83 (95% CI 0.81-0.86), which represents the model performance in future patients. The model was used to develop an interactive risk calculator.

CONCLUSIONS

This risk calculator has excellent predictive ability for mortality in patients with NSTI. This simple interactive tool can aid physicians and patients in the decision-making process.