Predictive Models for Necrotizing Soft Tissue Infections: Are the Available Scores Trustable?

Necrotizing soft tissue infections (NSTIs) remain a significant source of in-hospital morbidity and mortality in the U.S. and around the world, yet the need for a reliable tool to assess prognosis early in treatment remains unaddressed in the current medical literature. Many scoring systems have been developed; however, none have proven to be entirely reliable for use in patients with NSTIs. Using collected data through a PubMed and Google Scholar search, this review provides an overview of five scoring systems-LRINEC, platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), NECROSIS, and POTTER-while highlighting potential areas for further improvement of these scoring systems or the conception of a novel, more effective system. The most widely used scoring tool, the Laboratory Risk Indicator for Necrotizing Fasciitis Score (LRINEC), lacks high sensitivity and requires supplementation of other clinical parameters. The NECROSIS score offers a potentially improved system, though it lacks necessary external validation. NLR and PLR provide reliable measurements for immune response; however, they lack specificity for NSTI and require further research to determine parameters like cutoff values. The POTTER score, though not valid for use in patients with NSTI, poses a novel system utilizing AI technology and machine learning. This review concludes that further development of a reliable scoring system that accounts for the many factors involved in NSTI is required and may benefit from an integrative model like the POTTER score.