Development and validation of a clinical score combining the sequential organ failure assessment score with inflammation-based markers to predict outcome of patients with sepsis.

backgroundWhether combining the Sequential Organ Failure Assessment (SOFA) score at admission with inflammation-based markers can improve performance of prediction and risk stratification of patients with sepsis, compared to use of the SOFA score alone, remains unknown.

methodsData from septic patients included in the Medical Information Mart for Intensive Care database (MIMIC-IV) database were used for model development and internal validation. We developed a predictive nomogram model that included SOFA score, Charlson Comorbidity Index (CCI), red cell distribution width (RDW), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and mean corpuscular volume (MCV) values. The primary outcome was the performance of the risk score.

resultsData from 4704 septic patients included in the database were used for the primary cohort and to build the model. The multivariate analyses included SOFA score, CCI, RDW, NLR, LMR, and MCV values. These values were used for nomogram model construction. The nomogram model showed good calibration, and had better discrimination in terms of area under the receiver operating characteristic (AUROC) curve results than use of the SOFA score alone (0.724 (95% CI: 0.705-0.743) vs. 0.585 (95% CI: 0.562-0.609), respectively; P<0.001). It also had better classification in terms of net reclassification improvement (20.5% (95% CI: 16.2%-24.7%; P<0.001)) and integrated discrimination improvement (6.0% (95% CI: 5.1%-6.8%; P<0.001)). The validation cohort results supported these findings.

conclusionThe results suggested that this simple-to-use nomogram model provided a relatively accurate risk of death prediction in patients with sepsis.