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The use of anticoagulation and antiplatelet agents (ACAP) has steadily increased over recent years. However, the effects of ACAP on traumatic brain injuries (TBI) are not well investigated. The aim of this study was to investigate the effects of pre-injury ACAP use on clinical outcome and mortality in severe TBI. A retrospective case-control study was performed for all patients who presented with severe TBI (GCS < 8) to the National Neuroscience Institute, Singapore, between 2006 and 2009. Patients with pre-injury ACAP use were compared to matched controls. Outcome measures were mortality at 14 days and 6 months, and Glasgow Outcome Score (GOS) at 6 months using a sliding dichotomy approach. Univariate analysis was performed using Chi-square and student's t-test and logistic regression was used to model the effect of ACAP on mortality rate. Forty-five patients with pre-injury use of ACAP were compared with matched controls. The mortality at 14 days (OR = 0.5, 95% CI 0.2-1.4) and 6 months (OR = 0.7, 95% CI 0.2-1.9) were not significantly different between the 2 groups. Using the sliding dichotomy approach, there was no difference in the odds for unfavorable functional outcomes at 6 months (OR = 1.2, 95% CI 0.4-3.7). In this case-control study, the use of ACAP did not have a significant effect on mortality and adverse outcomes in patients with severe TBI. This would suggest that in severe TBI, ACAP use may not contribute significantly to the overall prognosis., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Background: Hematoma expansion (HE) occurs in approximately one-third of patients with intracerebral hemorrhage (ICH) and is known to be a strong predictor of neurological deterioration as well as poor functional outcome. This study aims to externally validate three risk prediction models of HE (PREDICT, 9-point, and BRAIN scores) in an Asian population., Methods: A prospective cohort of 123 spontaneous ICH patients admitted to a tertiary hospital (certified stroke center) in Singapore was recruited. Logistic recalibrations were performed to obtain updated calibration slopes and intercepts for all models. The discrimination (c-statistic), calibration (Hosmer-Lemeshow test, le Cessie-van Houwelingen-Copas-Hosmer test, Akaike information criterion), overall performance (Brier score, R 2 ), and clinical usefulness (decision curve analysis) of the risk prediction models were examined., Results: Overall, the recalibrated PREDICT performed best among the three models in our study cohort based on the novel matrix comprising of Akaike information criterion and c-statistic. The PREDICT model had the highest R 2 (0.26) and lowest Brier score (0.14). Decision curve analyses showed that recalibrated PREDICT was more clinically useful than 9-point and BRAIN models over the greatest range of threshold probabilities. The two scores (PREDICT and 9-point) which incorporated computed tomography (CT) angiography spot sign outperformed the one without (BRAIN)., Conclusions: To our knowledge, this is the first study to validate HE scores, namely PREDICT, 9-Point and BRAIN, in a multi-ethnic Asian ICH patient population. The PREDICT score was the best performing model in our study cohort, based on the performance metrics employed in this study. Our findings also showed support for CT angiography spot sign as a predictor of outcome after ICH. Although the models assessed are sufficient for risk stratification, the discrimination and calibration are at best moderate and could be improved.

Objective: Numerous scores have been developed for prognostication of outcomes in intracerebral hemorrhage (ICH). Prediction models must be validated internally and externally before they are considered widely applicable. We aim to independently externally validate and compare 3 prediction models (ICH score, ICH grading scale [ICH-GS], and simplified ICH [sICH]) in our population, which has not been previously done., Methods: We reviewed 1338 patients with spontaneous ICH consecutively admitted to the National Neuroscience Institute, Singapore, between January 2009 and November 2013. We analyzed prospectively collected data of admission characteristics (clinical, neuroimaging, and laboratory findings). All 3 scores prognosticated 30-day mortality. Validation was based on calibration, goodness-of-fit tests, and discrimination (area under receiver operating characteristic curve [AUC]). Akaike information criterion (AIC) and decision curve analysis (DCA) were used to directly compare the scores., Results: All 3 models showed good calibration and both the Hosmer-Lemeshow and the le Cessie-van Houwelingen-Copas goodness-of-fit test showed P values >0.05. AUCs ranged from 0.86 to 0.90, indicating good discriminative ability, with the ICH-GS performing the best with the highest AUC, lowest AIC (849), and overall highest net benefit in the DCA., Conclusions: This study successfully independently validates the ICH score, ICH-GS, and sICH score in a large patient cohort with spontaneous ICH, which has not been previously done in this non-Western population. We recommend the use of the ICH-GS as a prognostication tool in our patients instead of the widely used ICH score., (Copyright © 2017 Elsevier Inc. All rights reserved.)