Objective:In an international collaborative multicenter pooled analysis, we compared mortality, functional outcome, intracerebral hemorrhage (ICH) volume, and hematoma expansion (HE) between non–vitamin K antagonist oral anticoagulation–related ICH (NOAC-ICH) and vitamin K antagonist–associated ICH (VKA-ICH).Methods:We compared all-cause mortality within 90 days for NOAC-ICH and VKA-ICH using a Cox proportional hazards model adjusted for age; sex; baseline Glasgow Coma Scale score, ICH location, and log volume; intraventricular hemorrhage volume; and intracranial surgery. We addressed heterogeneity using a shared frailty term. Good functional outcome was defined as discharge modified Rankin Scale score ≤2 and investigated in multivariable logistic regression. ICH volume was measured by ABC/2 or a semiautomated planimetric method. HE was defined as an ICH volume increase >33% or >6 mL from baseline within 72 hours.Results:We included 500 patients (97 NOAC-ICH and 403 VKA-ICH). Median baseline ICH volume was 14.4 mL (interquartile range [IQR] 3.6–38.4) for NOAC-ICH vs 10.6 mL (IQR 4.0–27.9) for VKA-ICH (p = 0.78). We did not find any difference between NOAC-ICH and VKA-ICH for all-cause mortality within 90 days (33% for NOAC-ICH vs 31% for VKA-ICH [p = 0.64]; adjusted Cox hazard ratio (for NOAC-ICH vs VKA-ICH) 0.93 [95% confidence interval (CI) 0.52–1.64] [p = 0.79]), the rate of HE (NOAC-ICH n = 29/48 [40%] vs VKA-ICH n = 93/140 [34%] [p = 0.45]), or functional outcome at hospital discharge (NOAC-ICH vs VKA-ICH odds ratio 0.47; 95% CI 0.18–1.19 [p = 0.11]).Conclusions:In our international collaborative multicenter pooled analysis, baseline ICH volume, hematoma expansion, 90-day mortality, and functional outcome were similar following NOAC-ICH and VKA-ICH.

ObjectiveThere is little evidence to guide treatment strategies for intracerebral hemorrhage on vitamin K antagonists (VKA‐ICH). Treatments utilized in clinical practice include fresh frozen plasma (FFP) and prothrombin complex concentrate (PCC). Our aim was to compare case fatality with different reversal strategies.MethodsWe pooled individual ICH patient data from 16 stroke registries in 9 countries (n = 10 282), of whom 1,797 (17%) were on VKA. After excluding 250 patients with international normalized ratio < 1.3 and/or missing data required for analysis, we compared all‐cause 30‐day case fatality using Cox regression.ResultsWe included 1,547 patients treated with FFP (n = 377, 24%), PCC (n = 585, 38%), both (n = 131, 9%), or neither (n = 454, 29%). The crude case fatality and adjusted hazard ratio (HR) were highest with no reversal (61.7%, HR = 2.540, 95% confidence interval [CI] = 1.784–3.616, p < 0.001), followed by FFP alone (45.6%, HR = 1.344, 95% CI = 0.934–1.934, p = 0.112), then PCC alone (37.3%, HR = 1.445, 95% CI = 1.014–2.058, p = 0.041), compared to reversal with both FFP and PCC (27.8%, reference). Outcomes with PCC versus FFP were similar (HR = 1.075, 95% CI = 0.874–1.323, p = 0.492); 4‐factor PCC (n = 441) was associated with higher case fatality compared to 3‐factor PCC (n = 144, HR = 1.441, 95% CI = 1.041–1.995, p = 0.027).InterpretationThe combination of FFP and PCC might be associated with the lowest case fatality in reversal of VKA‐ICH, and FFP may be equivalent to PCC. Randomized controlled trials with functional outcomes are needed to establish the most effective treatment. Ann Neurol 2015;78:54–62

Additional supporting information may be found online in the Supporting Information section at the end of the article.

BackgroundThe intracerebral hemorrhage (ICH) score is a commonly used prognostic model for 30-day mortality in ICH, based on five independent predictors (ICH volume, location, Glasgow Coma Scale, age, and intraventricular extension). Use of oral anticoagulants (OAC) is also associated with mortality but was not considered in the ICH score. We investigated (a) whether the predictive performance of ICH score is similar in OAC-ICH and non-OAC-ICH and (b) whether addition of OAC use to the ICH score increases the prognostic performance of the score.MethodsWe retrospectively selected all consecutive adult non-traumatic ICH cases (three hospitals, region South-Limburg, the Netherlands 2004–2009). Mortality at 30 days was recorded. Using univariable and multivariable logistic regression, association between OAC use and 30-day mortality was tested. Then (a) we computed receiver operating characteristic (ROC) curves for ICH score and determined the area under the curve (AUC) in OAC-ICH and non-OAC-ICH. Then (b) we created a New ICH score by adding OAC use to the ICH score. We calculated correlation between 30-day mortality and ICH score, respectively, New ICH score using Spearman correlation test. We computed ROC curves and calculated the AUC.ResultsWe analyzed 1,232 cases, 282 (22.9%) were OAC related ICH. Overall, 30-day mortality was 39.3%. OAC use was independently associated with 30-day mortality (OR 2.09, 95% CI, 1.48–2.95; p < 0.001), corrected for the five predictors of the ICH score. The ICH score performed slightly better in non-OAC-ICH (AUC 0.840) than in OAC-ICH (AUC 0.816), but this difference was not significant (p = 0.39). The ICH score and the New ICH score were both significantly correlated with 30-day mortality (rho 0.58, p < 0.001 and 0.59, p < 0.001, respectively). The AUC for the ICH score was 0.837, for New ICH score 0.840. This difference was not significant.ConclusionThe ICH score is a useful tool for predicting 30-day mortality both in patient who use and patients who do not use OAC. Although OAC use is an independent predictor of 30-day mortality, addition of OAC use to the existing ICH score does not increase the prognostic performance of this score.

Low platelet counts and hematocrit levels hinder whole blood point-of-care testing of platelet function. Thus far, no reference ranges for MEA (multiple electrode aggregometry) and PFA-100 (platelet function analyzer 100) devices exist for low ranges. Through dilution methods of volunteer whole blood, platelet function at low ranges of platelet count and hematocrit levels was assessed on MEA for four agonists and for PFA-100 in two cartridges. Using (multiple) regression analysis, 95% reference intervals were computed for these low ranges. Low platelet counts affected MEA in a positive correlation (all agonists showed r ≥ 0.75) and PFA-100 in an inverse correlation (closure times were prolonged with lower platelet counts). Lowered hematocrit did not affect MEA testing, except for arachidonic acid activation (ASPI), which showed a weak positive correlation (r = 0.14). Closure time on PFA-100 testing was inversely correlated with hematocrit for both cartridges. Regression analysis revealed different 95% reference intervals in comparison with originally established intervals for both MEA and PFA-100 in low platelet or hematocrit conditions. Multiple regression analysis of ASPI and both tests on the PFA-100 for combined low platelet and hematocrit conditions revealed that only PFA-100 testing should be adjusted for both thrombocytopenia and anemia. 95% reference intervals were calculated using multiple regression analysis. However, coefficients of determination of PFA-100 were poor, and some variance remained unexplained. Thus, in this pilot study using (multiple) regression analysis, we could establish reference intervals of platelet function in anemia and thrombocytopenia conditions on PFA-100 and in thrombocytopenia conditions on MEA.