Incorporating Immunoproteins in the Development of Classification Models of Progression of Intracranial Hemorrhage After Traumatic Brain Injury.

OBJECTIVE: To define clinical, radiographic, and blood-based biomarker features to be incorporated into a classification model of progression of intracranial hemorrhage (PICH), and to provide a pilot assessment of those models. METHODS: Patients with hemorrhage on admission head computed tomography were identified from a prospectively enrolled cohort of subjects with traumatic brain injury. Initial and follow-up images were interpreted both by 2 independent readers, and disagreements adjudicated. Admission plasma samples were analyzed and principal components (PCs) composed of the immune proteins (IPs) significantly associated with the outcome of interest were selected for further evaluation. A series of logistic regression models were constructed based on (1) clinical variables (CV) and (2) clinical variables + immune proteins (CV+IP). Error rates of these models for correct classification of PICH were estimated; significance was set at P < .05. RESULTS: We identified 106 patients, 36% had PICH. Dichotomized admission Glasgow Coma Scale (P = .004), Marshall score (P = .004), and 3 PCs were significantly associated with PICH. For the CV only model, sensitivity was 1.0 and specificity was 0.29 (95% CI, 0.07-0.67). The CV+IP model performed significantly better, with a sensitivity of 0.93 (95% CI, 0.64-0.99) and a specificity of 1.0 (P = .008). Adjustments to refine the definition of PICH and better define radiographic predictors of PICH did not significantly improve the models' performance. CONCLUSIONS: In this pilot investigation, we observed that composites of IPs may improve PICH classification models when combined with CVs. However, overall model performance must be further optimized; results will inform feature inclusion included in follow-up models.

EAST Multicenter Trial on targeted temperature management for hanging-induced cardiac arrest.

BACKGROUND: We sought to determine the outcome of suicidal hanging and the impact of targeted temperature management (TTM) on hanging-induced cardiac arrest (CA) through an Eastern Association for the Surgery of Trauma (EAST) multicenter retrospective study. METHODS: We analyzed hanging patient data and TTM variables from January 1992 to December 2015. Cerebral performance category score of 1 or 2 was considered good neurologic outcome, while cerebral performance category score of 3 or 4 was considered poor outcome. Classification and Regression Trees recursive partitioning was used to develop multivariate predictive models for survival and neurologic outcome. RESULTS: A total of 692 hanging patients from 17 centers were analyzed for this study. Their overall survival rate was 77%, and the CA survival rate was 28.6%. The CA patients had significantly higher severity of illness and worse outcome than the non-CA patients. Of the 175 CA patients who survived to hospital admission, 81 patients (46.3%) received post-CA TTM. The unadjusted survival of TTM CA patients (24.7% vs 39.4%, p < 0.05) and good neurologic outcome (19.8% vs 37.2%, p < 0.05) were worse than non-TTM CA patients. However, when subgroup analyses were performed between those with an admission Glasgow Coma Scale score of 3 to 8, the differences between TTM and non-TTM CA survival (23.8% vs 30.0%, p = 0.37) and good neurologic outcome (18.8% vs 28.7%, p = 0.14) were not significant. Targeted temperature management implementation and post-CA management varied between the participating centers. Classification and Regression Trees models identified variables predictive of favorable and poor outcome for hanging and TTM patients with excellent accuracy. CONCLUSION: Cardiac arrest hanging patients had worse outcome than non-CA patients. Targeted temperature management CA patients had worse unadjusted survival and neurologic outcome than non-TTM patients. These findings may be explained by their higher severity of illness, variable TTM implementation, and differences in post-CA management. Future prospective studies are necessary to ascertain the effect of TTM on hanging outcome and to validate our Classification and Regression Trees models. LEVEL OF EVIDENCE: Therapeutic study, level IV; prognostic study, level III.