Symptomatic Intracranial Hemorrhage After Endovascular Stroke Treatment: External Validation of Prediction Models

Author:

van der Ende Nadinda A.M.12ORCID,Kremers Femke C.C.1ORCID,van der Steen Wouter12ORCID,Venema Esmee13ORCID,Kappelhof Manon4ORCID,Majoie Charles B.L.M.ORCID,Postma Alida A.5ORCID,Boiten Jelis6,van den Wijngaard Ido R.67ORCID,van der Lugt AadORCID,Dippel Diederik W.J.1ORCID,Roozenbeek Bob12ORCID,

Affiliation:

1. Departments of Neurology (N.A.M.v.d.E, F.C.C.K., W.v.d.S, E.V., D.W.J.D., B.R.), Erasmus MC University Medical Center, the Netherlands.

2. Radiology and Nuclear Medicine (N.A.M.v.d.Ee, W.v.d.S., B.R.), Erasmus MC University Medical Center, the Netherlands.

3. Emergency Medicine (E.V.), Erasmus MC University Medical Center, the Netherlands.

4. Department of Radiology and Nuclear Medicine (M.K.), Amsterdam UMC, University of Amsterdam, the Netherlands.

5. Department of Radiology and Nuclear Medicine, School for Mental Health and Sciences, Maastricht University Medical Center, the Netherlands (A.A.P.).

6. Departments of Neurology (J.B., I.R.v.d.W.), Haaglanden Medical Center, the Netherlands.

7. Radiology and Nuclear Medicine (I.R.v.d.W.), Haaglanden Medical Center, the Netherlands.

Abstract

Background: Symptomatic intracranial hemorrhage (sICH) is a severe complication of reperfusion therapy for ischemic stroke. Multiple models have been developed to predict sICH or intracranial hemorrhage (ICH) after reperfusion therapy. We provide an overview of published models and validate their ability to predict sICH in patients treated with endovascular treatment in daily clinical practice. Methods: We conducted a systematic search to identify models either developed or validated to predict sICH or ICH after reperfusion therapy (intravenous thrombolysis and/or endovascular treatment) for ischemic stroke. Models were externally validated in the MR CLEAN Registry (n=3180; Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands). The primary outcome was sICH according to the Heidelberg Bleeding Classification. Model performance was evaluated with discrimination (c-statistic, ideally 1; a c-statistic below 0.7 is considered poor in discrimination) and calibration (slope, ideally 1, and intercept, ideally 0). Results: We included 39 studies describing 40 models. The most frequently used predictors were baseline National Institutes of Health Stroke Scale (NIHSS; n=35), age (n=22), and glucose level (n=22). In the MR CLEAN Registry, sICH occurred in 188/3180 (5.9%) patients. Discrimination ranged from 0.51 (SPAN-100 [Stroke Prognostication Using Age and National Institutes of Health Stroke Scale]) to 0.61 (SITS-SICH [Safe Implementation of Treatments in Stroke Symptomatic Intracerebral Hemorrhage] and STARTING-SICH [STARTING Symptomatic Intracerebral Hemorrhage]). Best calibrated models were IST-3 (intercept, −0.15 [95% CI, −0.01 to −0.31]; slope, 0.80 [95% CI, 0.50−1.09]), SITS−SICH (intercept, 0.15 [95% CI, −0.01 to 0.30]; slope, 0.62 [95% CI, 0.38−0.87]), and STARTING−SICH (intercept, −0.03 [95% CI, −0.19 to 0.12]; slope, 0.56 [95% CI, 0.35−0.76]). Conclusions: The investigated models to predict sICH or ICH discriminate poorly between patients with a low and high risk of sICH after endovascular treatment in daily clinical practice and are, therefore, not clinically useful for this patient population.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Advanced and Specialized Nursing,Cardiology and Cardiovascular Medicine,Neurology (clinical)

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