Risk factors for in-hospital mortality in patients with severe trauma and their predictive value
Objective To explore the risk factors for in-hospital mortality in patients with severe trauma and their predictive predictive value.Methods A retrospective case-control study was used to analyze the data of 509 patients with severe trauma in the trauma database of the Trauma Center of the Second Affiliated Hospital of Soochow University from January 2017 to December 2021,including 377 males and 132 females,aged 18-94 years[53(42,65)years].Injury severity score(ISS)was 16-75 points[22(18,29)points].Injured parts included the head and neck in 409 patients(80.35％),the chest in 328(64.44％),the abdomen in 193(37.91％),the pelvis in 142(27.90％),the spine in 79(15.52％),and the limb in 247(48.53％).According to the clinical outcome during the hospital stay,the patients were divided into survival group(n=390)and non-survival group(n=119).Baseline and clinical data of the two groups were compared,including gender,age,cause of injury(traffic injury,fall from height,sharp instrument injury,etc.),injury site(head and neck,chest,abdomen,pelvis,spine,limb),vital signs on admission(temperature,systolic blood pressure,heart rate,respiratory rate),blood tests on admission[hemoglobin,platelets,prothrombin time(PT),activated partial thromboplastin time(APTT),international normalized ratio(INR),fibrinogen(FIB)],Glasgow coma scale(GCS)upon admission to the emergency room,revised trauma score(RTS)upon admission to the emergency room,ISS after whole-body CT examination,quick sequential organ failure assessment(qSOFA)score upon admission to the emergency room,and INR combined with qSOFA score.The baseline and clinical data of the survival group and the non-survival group were first compared with univariate analysis.Then,the independent risk factors of in-hospital mortality in patients with severe trauma were determined by multivariate Logistic stepwise regression(forward and backward).Based on the above data,receiver operating characteristic(ROC)curves were generated with Medcalc statistical software to analyze the efficacy of each risk factor in assessing in-hospital mortality in patients with severe trauma.Results Univariate analysis showed that there were significant differences in age,injury site,temperature,systolic blood pressure,hemoglobin,platelet,PT,APTT,INR,FIB,GCS,RTS,ISS,qSOFA score,and INR combined with qSOFA score between the two groups(P＜0.05 or 0.01),while there were no significant differences in gender,cause of injury,heart rate,and respiratory rate between the two groups(P＞0.05).Multivariate Logistic stepwise regression analysis showed that age,systolic blood pressure,APTT,ISS,and INR combined with qSOFA score were significantly correlated with in-hospital mortality in patients with severe trauma(P＜0.01).ROC curve analysis results showed that the area under the curve(AUC)of in-hospital mortality in patients with severe trauma predicted by age,systolic blood pressure,APTT,ISS,and INR combined with qSOFA score were 0.63(95％CI 0.59,0.68)and 0.60(95％CI 0.55,0.64),0.66(95％CI 0.62,0.70),0.73(95％CI 0.69,0.77),and 0.75(95％CI 0.72,0.80),respectively.Conclusions Age,systolic blood pressure,APTT,ISS,and INR combined with qSOFA score are the independent risk factors for in-hospital mortality in patients with severe trauma.ISS and INR combined qSOFA score can better predict in-hospital mortality of patients with severe trauma than age,systolic blood pressure and APTT.
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