Multiple organ dysfunction syndrome (MODS) prediction score in multi-trauma patients

Abstract

Background Multiple organ dysfunction syndrome (MODS) in patients with major trauma remains a frequent and devastating complication in emergency departments and intensive care units. Easily and accurately identifying patients at risk for MODS post-injury, especially in multi-trauma cases, is important. The aim of this study was to develop an instrument to predict the development of MODS in adult multi-trauma patients using clinical and laboratory data available in the first 24 h after trauma. Methods We prospectively enrolled adult multi-trauma patients with Injury Severity Score (ISS) ≥16, between 16 and 65 years old, admitted to four academic Level-I trauma centers for 1 year between September 2014 and 2015. Sequential organ failure assessment score was used to determine MODS during hospitalization. A risk score was created from the final regression model consisting of significant variables as MODS predictors. Result During the period of the study, 98 multi-trauma patients were included. The mean age was 35.2 years, and most were male (85.71%). The mean ISS was 23.6, mostly (76.53%) caused by blunt injury mechanism. MODS occurred in 43 patients (43.87%). The prediction risk score consists of Revised Trauma Score (<7.25) and lactate level ≥2.75 mmol/L. This study also verified several independent risk factors for post-multi-trauma MODS such as ISS >25, presence of systemic inflammatory response syndrome, shock grade 2 or more, and white blood cells >12,000. Conclusion We derived a novel simple and applicable instrument to predict MODS in adults following multi-trauma. The use of this scoring system may allow early identification of trauma patients who are at risk for MODS and result in more aggressive targeted resuscitation and damage control surgery. Trial registration ISCRTN ISRCTN16661943. 09/11/2016 retrospectively registered. Highlights

Trauma-Induced Damage-Associated Molecular Patterns-Mediated Remote Organ Injury and Immunosuppression in the Acutely Ill Patient

“…The ISS predicts further organ failure and patient outcome ( 126 ). MODS incidence can reach 60% of patients ( 127 ).…”

Machine learning for the detection of early immunological markers as predictors of multi-organ dysfunction

“…Specifically, we have addressed the inadequacies of the current clinical scoring systems used for the assessment of trauma severity, namely New Injury Severity Score (NISS) and Probability of Survival (PS14). They are the main outcome measurements evaluated in TARN (the Trauma Audit and Research Network) and have both shown a high correlation with mortality and length of stay and act as the general predictors for outcomes such as MODS development 14 and sepsis, irrespective of the underlying biological differences of the outcomes. NISS is based on the sum of squares of the Abbreviated Injury Scale (AIS) scores of a patient’s injuries and hence is limited to anatomical information only, whereas PS14 is modelled based on age, gender, Injury Severity Score (ISS), pre-existing medical conditions, patient outcome (up to 30 days) 15 and Glasgow Coma Score (GCS) 16 .…”

Anemia after Pediatric Congenital Heart Surgery

“…The postoperative degree of severity was determined using three scores of mortality and morbidity: the Pediatric Risk of Mortality (PRISM) III scoring system, the PELOD-2 score, and the Multiple Organ Dysfunction (MODS) score. 18 19 20…”

“…The postoperative degree of severity was determined using three scores of mortality and morbidity: the Pediatric Risk of Mortality (PRISM) III scoring system, the PELOD-2 score, and the Multiple Organ Dysfunction (MODS) score. [18][19][20] We defined surgical complexity using the RACHS-1 score. The RACHS-1 score has been used as a standardized classification tool for cardiac repairs in children younger than 18 years; it is predictive of major adverse events and prolonged lengths of hospitalization stay.…”