Lethal Dose 50 Of ISS Or NISS And Its Application In Development Of Novel Formulae For Predicting Complications And Deaths Post Trauma

BackgroundMajor complications such as acute respiratory distress syndrome (ARDS), multiple organ dysfunction syndrome (MODS) and sepsis are the leading causes of deaths in trauma patients during the hospital stay. Early identification of patients at risk of these complications or death would allow timely implementation of effective intervention to improve outcomes. Injury severity score (ISS) and new injury severity score (NISS) are widely used in evaluating trauma severity and predicting outcomes of trauma patients; race and age are also risk factors related to the occurrence of poor outcomes. The purpose of this study is to develop and validate a clinical prediction formula using risk factors above for predicting complications accurately and rapidly post trauma.Methods1. We analyzed data of 6417 Chinese Han trauma patients entered in Chinese Trauma Databank (CTDB) by using probit regression models to get the lethal dose 50 (LD50) values of ISS and NISS at different age groups. LD50 comprised the effects of risk factors race, age and injury severity.2. Data of 1148 trauma patients were enrolled to validate the predictive value of ISS/LD50ISS and NISS/LD50NISS which represented relative injury severity in predicting ARDS, MODS, sepsis and death. Then we compared the predictive ability of ISS/LD50ISS and ISS, NISS/LD50NISS and NISS, respectively. In case of the lack capacity of ISS/LD50ISS and NISS/LD50NISS, systemic inflammatory response syndrome (SIRS) score was introduced as a candidate index. The formulae which had the SIRS score introduction were then compared with the logistic regression models in their predictive ability.3. In prediction of sepsis, novel formulae and the most used biomarker procalcitonin (PCT) was compared in their predictive values.4. Predictive value was assessed using area under the receiver operating characteristic (ROC) curves (AUC). DeLong et al. technique was used to compare the AUCs. SPSS 18.0 software was used to establish the probit regression models and logistic regression models. MedCalc 12.1 software was used to perform the comparison of ROC curves.Results1. The LD50 values of ISS in the age of 16-44,45-64 and>65 were 55,49 and 33, respectively; the LD50 values of NISS in the age of 16-44,45-64 and>65 were 62,56 and 43, respectively.2. In prediction of ARDS, ISS/LD50ISS was better than ISS (AUC:0.888 versus 0.874, p<0.05), and NISS/LD50NISS was better than NISS (AUC:0.877 versus 0.864, p<0.05); in prediction of MODS, ISS/LD50IS performed better than ISS (AUC:0.893 versus 0.882, p< 0.05), and NISS/LD5ONISS showed better ability than NISS (AUC:0.890 versus 0.880, p< 0.05); ISS/LD50ISS and ISS, NISS/LD50NISS and NISS were equivalent in predicting sepsis (AUC:0.857 versus 0.861, p>0.05, and 0.863 versus 0.862, p>0.05, respectively); in prediction of death, ISS/LD50ISS was better than ISS (AUC:0.907 versus 0.894, p<0.05), and NISS/LD50NISS was better than NISS (AUC:0.903 versus 0.882, p<0.05).3. The formula models ISS/LD50ISS+SIRS score and NISS/LD500NISS+SIRS score showed excellent predictive value (AUC,0.941 and 0.940, respectively) in the validation using the data of 1148 patients. Four logistic regression models were established, and they were Y1=-5.138+0.070 ISS+1.466 SIRS score, Y2=-5.138+3.338 ISS/LD50NISS+1-478 SIRS score, Y3=-5.321+0.067 NISS+1.443 SIRS score, Y4=-5.383+3.944 NISS/LD50NISS+1.446 SIRS score. The AUCs of the four logistic regression models were 0.940,0.940,0.940, and 0.941, respectively. Four logistic regression models were equivalent in predictive value with the formulae ISS/LD50NISS+SIRS score and NISS/LD50NISS+SIRS score.221 patients’data with PCT levels were analyzed to compare the predictive ability of formula models and PCT, and the predictive ability of ISS/LD50ISS +SIRS score and NISS/LD50NISS+SIRS score was better than that of PCT (AUC,0.816 versus 0.592, p<0.05, and 0.819 versus 0.592, p<0.05,respectively).ConclusionsLD50 values of ISS or NISS at different ages of Chinese Han population were proposed in this study. The new formulae ISS/LDsoISS and NISS/LD50NISS were developed, which can be easily calculated in the early phase after trauma to predict ARDS, MODS, and death more accurately than ISS and NISS. We developed ISS/LD50ISS+SIRS score and NISS/LD50NISS+SIRS score as post-trauma sepsis prediction formula (PTSPF). The application of PTSPF would help to early identify the patients at risk of sepsis following trauma and allow the timely implementation of aggressive inventions to prevent sepsis and improve the outcomes of trauma patients.