Necrotizing Soft Tissue Infection in the Elderly: Effect of Pre-Operative Factors on Mortality and Discharge Disposition.

Background

Necrotizing soft tissue infections (NSTIs) are rapidly progressing, life-threatening diseases associated with substantial morbidity and mortality, especially in patients 65 years or older. We aimed to evaluate clinical factors associated with mortality and discharge disposition after NSTIs in elderly patients. Patients and

Methods

Retrospective data were obtained from the 2007-2017 American College of Surgeons-National Surgical Quality (ACS-NSQIP) database. Patients aged 65 years or older with a post-operative diagnosis of an NSTI (defined as gas gangrene, necrotizing fasciitis, or Fournier gangrene) were included. Univariable and multivariable analyses were performed to identify independent clinical and demographic factors associated with mortality and with discharge disposition.

Results

A total of 1,460 patients were included. Median age was 71 years, 43% were females. Overall, 30-day mortality was 18.5% and 30-day morbidity was 63.6%. The most important predictors of mortality included pre-operative septic shock (odds ratio [OR], 6.36; 95% confidence interval [CI], 3.61-11.18), pre-operative dialysis dependence (OR, 2.99; 95% CI, 1.77-5.05), coagulopathy (international normalized ratio [INR], >1.5, OR, 2.25; 95% CI, 1.51-3.37), hepatobiliary disease (bilirubin >1.0 mg/dL; OR, 2.05; 95% CI, 1.38-3.04) and aged 80 years or older (OR, 3.36; 95% CI, 2.08-5.44). Patients without any of these risk factors had a mortality of 7.3%. Predictors of discharge to inpatient rehabilitation or skilled care included age 80 years or older (OR, 2.49; 95% CI, 1.44-4.30), American Society of Anesthesiologists (ASA) ≥3 (OR, 2.05; 95% CI, 1.03-4.05)] and amputation as opposed to debridement (OR, 2.53; 95% CI,1.48-4.32).

Conclusions

We identified several pre-operative clinical factors that were associated with increased post-operative mortality and discharge to post-acute care. The next steps should focus on determining if optimization of modifiable predictors would improve mortality.