Impact of comorbidities on the prognoses of trauma patients: Analysis of a hospital-based trauma registry database

Abstract

Here we conducted a retrospective analysis of hospital-based trauma registry database for evaluating the impacts of comorbidities on the prognosis for traumatized patients using Index of Coexistent Comorbidity Disease (ICED) scores. We analyzed the data of patients with blunt trauma who visited emergency department between January 1, 2011, and December 31, 2015 in Chang-Gung Memorial Hospital, Keelung branch, a single level I trauma center in the Northern Taiwan. All consecutive patients with blunt trauma who admitted to the intensive care unit or ordinary ward after initial managements in the emergency department were included. We measured the hospital mortality of blunt traumatized patients using alive discharge as a competing risk. To investigate conditional independence of mortality and ICED scores given Injury Severity Score (ISS), we used log-linear models for modeling independence structures. Overall, we included 4997 patients (median age [IQR], 59 years old (44-75 years); 55.3% male). The mortality rate of blunt traumatized patients was higher in the higher ICED scores group compared to lower ICED scores group (4.7% vs 1.8%, p < 0.001). Meanwhile, the higher ICED scores group were associated with older age, higher ISS, and longer hospital stay than lower ICED scores group. Higher ICED group had higher probability of transition-to-death and lower probability of transition-to-discharge under the competing risk model. In the multivariable analysis of transition-specific Cox models, higher ICED group were associated with higher risk for hospital mortality compared to lower ICED group (HR 1.60; [95% CI 1.04-2.47]; p = 0.032). Also, higher ICED group were associated with lower probability of transition-to-discharge (HR 0.79; [95%CI 0.73-0.86]; p < 0.001). Additionally, higher ICED scores accounted for hospital mortality among patients with ISS < 25. In conclusion, our study suggested that severity of comorbidity was associated with higher hospital mortality among traumatized patients, particularly lower ISS.

Fig 1. Cumulative hazards stratified by the ICED scores in the competing risk model.

Orange lines indicated lower ICED group (n = 4153) whereas blue lines represented higher ICED group (n = 844). Higher ICED group had higher cumulative hazards for transition-to-death and lower cumulative hazards for transition-to-discharge compared with lower ICED group.

Fig 2. Non-linear effects of injury severity scores on transition-to-death and transition-to-discharge, and non-linear effects of systolic blood pressure on transition-to-discharge.

When the ISS reached above 20, the risk for transition-to-death increased exponentially. The p-value of penalized spline for linear effect of ISS score is <0.001, while p-value of penalized spline for non-linear effect of ISS score is 0.018. In the transition-to-discharge, ISS had a linear effect on discharge when ISS<10. The p-value for linear effect of ISS score is <0.001 as well as the nonlinear effect. Lower and higher systolic blood pressure had lower potential for transition-to-discharge. The p-value for linear effect of systolic blood pressure is 0.450, while p-value of for non-linear effect is 0.001. The reference level of injury severity score was 9, while reference level of systolic blood pressure was 150 mmHg.

Fig 3. Mosaic plot visualizing the distribution of mortality and ICED scores given ISS using the log-linear model.

The size of each cell is proportional to the observed frequency. The Pearson residuals are standardized deviations of observed from expected values. The cut-off points 2 and 4 implies that the highlighted cells are those with residuals individually significant at approximately the alpha = 0.05 and alpha = 0.0001 levels, respectively. Each colored residual violates the null hypotheses of independence. Light blue colored cell indicates positive Pearson residuals at alpha = 0.05 level. Dark blue colored cell indicates positive Pearson residuals at alpha = 0.0001 level. Red colored cell represents negative Pearson residuals at alpha = 0.05 level. The p value is for the log-linear model investigating conditional independence of mortality and ICED scores given ISS, which is highly significant.