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. 2013:2013:681673.
doi: 10.1155/2013/681673.

Hemorrhagic Transformation (HT) and Symptomatic Intracerebral Hemorrhage (sICH) Risk Prediction Models for Postthrombolytic Hemorrhage in the Stroke Belt

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Hemorrhagic Transformation (HT) and Symptomatic Intracerebral Hemorrhage (sICH) Risk Prediction Models for Postthrombolytic Hemorrhage in the Stroke Belt

James E Siegler et al. ISRN Stroke. 2013.

Abstract

Background: Symptomatic intracerebral hemorrhage (sICH) remains the most feared complication of intravenous tissue plasminogen activator (IV tPA) treatment. We aimed to investigate how previously validated scoring methodologies would perform in treated patients in two US Stroke Belt states.

Methods and results: We retrospectively reviewed consecutive patients from two centers in two Stroke Belt states who received IV tPA (2008-2011). We assessed the ability of three models to predict sICH. sICH was defined as a type 2 parenchymal hemorrhage with deterioration in National Institutes of Health Stroke Scale (NIHSS) score of ≥4 points or death. Among 457 IV tPA-treated patients, 19 (4.2%) had sICH (mean age 68, 26.3% Black, 63.2% female). The Cucchiara model was most predictive of sICH in the entire cohort (AUC: 0.6528) and most predictive of sICH among Blacks (OR = 6.03, 95% CI 1.07-34.1, P = 0.0422) when patients were dichotomized by score.

Conclusions: In our small sample from the racially heterogeneous US Stroke Belt, the Cucchiara model outperformed the other models at predicting sICH. While predictive models should not be used to justify nontreatment with thrombolytics, those interested in understanding contributors to sICH may choose to use the Cucchiara model until a Stroke Belt model is developed for this region.

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Figures

Figure 1
Figure 1
Receiver operator characteristic assessing ability of scores to predict sICH for all patients (a), Black patients (b), and White patients (c). sICH denotes symptomatic intracranial hemorrhage, AUC area under the curve, SPAN-100 stroke prognostication using age and National Institutes of Health Stroke Scale score, and SITS safe implementation of treatments in stroke.
Figure 2
Figure 2
Odds of sICH according to selected scoring methodologies in our cohort of Stroke Belt patients using (a) 4-group and (b) dichotomized comparisons. sICH denotes symptomatic intracranial hemorrhage and SITS safe implementation of treatments in stroke.
Figure 3
Figure 3
Percentage of patients with sICH according to clinical score. Values represent percentage of patients who experienced sICH according to score type and score value. In the SITS-sICH score, low corresponds to 0–2 points, average corresponds to 3–5 points, moderate corresponds to 6–8 points, and high corresponds to 9–12 points. sICH denotes symptomatic intracranial hemorrhage, SITS safe implementation of treatments in stroke, and SPAN-100 stroke prognostication using age and National Institutes of Health Stroke Scale score.

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References

    1. Cucchiara B, Tanne D, Levine SR, Demchuk AM, Kasner S. A risk score to predict intracranial hemorrhage after recombinant tissue plasminogen activator for acute ischemic stroke. Journal of Stroke and Cerebrovascular Diseases. 2008;vol. 17(no. 6):331–333. - PubMed
    1. Mazya M, Egido JA, Ford GA, et al. Predicting the risk of symptomatic intracerebral hemorrhage in ischemic stroke treated with intravenous alteplase: safe implementation of treatments in stroke (SITS) symptomatic intracerebral hemorrhage risk score. Stroke. 2012;vol. 43:1524–1531. - PubMed
    1. Saposnik G, Guzik AK, Reeves M, Ovbiagele B, Johnston SC. Stroke prognostication using age and nih stroke scale: Span-100. Neurology. 2013;vol. 80(no. 1):21–28. - PMC - PubMed
    1. Saver JL, Yafeh B. Confirmation of tPA treatment effect by baseline severity-adjusted end point reanalysis of the NINDS-tPA stroke trials. Stroke. 2007;vol. 38(no. 2):414–416. - PubMed
    1. Marler JR. Tissue plasminogen activator for acute ischemic stroke. The New England Journal of Medicine. 1995;vol. 333(no. 24):1581–1587. - PubMed

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