OBJECTIVE Traumatic brain injury (TBI) remains a significant cause of neurological morbidity and mortality. Each year, more than 1.7 million patients present to the emergency department with TBI. The goal of this study was to evaluate the prognosis of traumatic cerebral intraparenchymal hemorrhage (tIPH), to develop subclassifications of these injuries that relate to prognosis, and to provide a more comprehensive assessment of hemorrhagic progression contusion (HPC) by analyzing the rate at which tIPH "blossom" (i.e., expansion), depending on a variety of intrinsic and modifiable factors. METHODS In this retrospective study, 726 patients (age range 0-100 years) were admitted to a level 1 trauma center with tIPH during an 8-year period (2005-2013). Of these patients, 491 underwent both admission and follow-up head CT (HCT) within 72 hours. The change in tIPH volume over time, the expansion rate, was recorded for all 491 patients. Effects of prehospital and in-hospital variables were examined using ordinal response logistic regression analyses. These variables were further examined using multivariate linear regression analysis to accurately predict the extent to which a hemorrhage will progress. RESULTS Of the 491 (67.6%) patients who underwent both admission and follow-up HCT, 368 (74.9%) patients experienced HPC. These hemorrhages expanded on average by 61.6% (4.76 ml) with an average expansion rate of 0.71 ml per hour. On univariate analysis, certain patient characteristics were significantly (p < 0.05) related to HPC, including age (> 60 years), admission Glasgow Coma Scale score, blood alcohol level, international normalized ratio, absolute platelet count, transfusion of platelets, concomitant anticoagulation and antiplatelet medication, the initial tIPH volume on admission HCT, and ventriculostomy. Increased expansion rate was significantly associated with patient disposition to hospice or death (p < 0.001). To determine which factors most accurately predict overall patient disposition, an ordinal-response logistic regression identified systolic blood pressure, Injury Severity Score, admission Glasgow Coma Scale score, follow-up scan volume, transfusion of platelets, and ventriculostomy as predictors of patient discharge disposition following tIPH. A multivariate logistic regression identified several prehospital and in-hospital variables (age, Injury Severity Score, blood alcohol level, initial scan volume, concomitant epidural hematoma, presence of subarachnoid hemorrhage, transfusion of platelets, and ventriculostomy) that predicted the volumetric expansion of tIPH. Among these variables, the admission tIPH volume by HCT proved to be the factor most predictive of HPC. CONCLUSIONS Several factors contribute to the rate at which traumatic cerebral contusions blossom in the acute posttraumatic period. Identifying the intrinsic and modifiable aspects of cerebral contusions can help predict the rate of expansion and highlight potential therapeutic interventions to improve TBI-associated morbidity and mortality.
OBJECTIVETraumatic intracranial hemorrhage (tICH) is a significant source of morbidity and mortality in trauma patients. While prognostic models for tICH outcomes may assist in alerting clinicians to high-risk patients, previously developed models face limitations, including low accuracy, poor generalizability, and the use of more prognostic variables than is practical. This study aimed to construct a simpler and more accurate method of risk stratification for all tICH patients.METHODSThe authors retrospectively identified a consecutive series of 4110 patients admitted to their institution’s level 1 trauma center between 2003 and 2013. For each admission, they collected the patient’s sex, age, systolic blood pressure, blood alcohol concentration, antiplatelet/anticoagulant use, Glasgow Coma Scale (GCS) score, Injury Severity Score, presence of epidural hemorrhage, presence of subdural hemorrhage, presence of subarachnoid hemorrhage, and presence of intraparenchymal hemorrhage. The final study population comprised 3564 patients following exclusion of records with missing data. The dependent variable under study was patient death. A k-fold cross-validation was carried out with the best models selected via the Akaike Information Criterion. These models risk stratified the study partitions into grade I (< 1% predicted mortality), grade II (1%–10% predicted mortality), grade III (10%–40% predicted mortality), or grade IV (> 40% predicted mortality) tICH. Predicted mortalities were compared with actual mortalities within grades to assess calibration. Concordance was also evaluated. A final model was constructed using the entire data set. Subgroup analysis was conducted for each hemorrhage type.RESULTSCross-validation demonstrated good calibration (p < 0.001 for all grades) with a mean concordance of 0.881 (95% CI 0.865−0.898). In the authors’ final model, older age, lower blood alcohol concentration, antiplatelet/anticoagulant use, lower GCS score, and higher Injury Severity Score were all associated with greater mortality. Subgroup analysis showed successful stratification for subarachnoid, intraparenchymal, grade II–IV subdural, and grade I epidural hemorrhages.CONCLUSIONSThe authors developed a risk stratification model for tICH of any GCS score with concordance comparable to prior models and excellent calibration. These findings are applicable to multiple hemorrhage subtypes and can assist in identifying low-risk patients for more efficient resource allocation, facilitate family conversations regarding goals of care, and stratify patients for research purposes. Future work will include testing of more variables, validation of this model across institutions, as well as creation of a simplified model whose outputs can be calculated mentally.
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