Universität zu Köln

Bonkhoff, Anna K., Rubsamen, Nicole, Grefkes, Christian ORCID: 0000-0002-1656-720X, Rost, Natalia S., Berger, Klaus and Karch, Andre (2022). Development and Validation of Prediction Models for Severe Complications After Acute Ischemic Stroke: A Study Based on the Stroke Registry of Northwestern Germany. J. Am. Heart Assoc., 11 (6). HOBOKEN: WILEY. ISSN 2047-9980

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Abstract

Background The treatment of stroke has been undergoing rapid changes. As treatment options progress, prediction of those under risk for complications becomes more important. Available models have, however, frequently been built based on data no longer representative of today's care, in particular with respect to acute stroke management. Our aim was to build and validate prediction models for 4 clinically important, severe outcomes after stroke. Methods and Results We used German registry data from 152 710 patients with acute ischemic stroke obtained in 2016 (development) and 2017 (validation). We took into account potential predictors that were available at admission and focused on in-hospital mortality, intracranial mass effect, secondary intracerebral hemorrhage, and deep vein thrombosis as outcomes. Validation cohort prediction and calibration performances were assessed using the following 4 statistical approaches: logistic regression with backward selection, l1-regularized logistic regression, k-nearest neighbor, and gradient boosting classifier. In-hospital mortality and intracranial mass effects could be predicted with high accuracy (both areas under the curve, 0.90 [95% CI, 0.90-0.90]), whereas the areas under the curve for intracerebral hemorrhage (0.80 [95% CI, 0.80-0.80]) and deep vein thrombosis (0.73 [95% CI, 0.73-0.73]) were considerably lower. Stroke severity was the overall most important predictor. Models based on gradient boosting achieved better performances than those based on logistic regression for all outcomes. However, area under the curve estimates differed by a maximum of 0.02. Conclusions We validated prediction models for 4 severe outcomes after acute ischemic stroke based on routinely collected, recent clinical data. Model performance was superior to previously proposed approaches. These predictions may help to identify patients at risk early after stroke and thus facilitate an individualized level of care.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Bonkhoff, Anna K. UNSPECIFIED UNSPECIFIED UNSPECIFIED Rubsamen, Nicole UNSPECIFIED UNSPECIFIED UNSPECIFIED Grefkes, Christian UNSPECIFIED orcid.org/0000-0002-1656-720X UNSPECIFIED Rost, Natalia S. UNSPECIFIED UNSPECIFIED UNSPECIFIED Berger, Klaus UNSPECIFIED UNSPECIFIED UNSPECIFIED Karch, Andre UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-686886
DOI:	10.1161/JAHA.121.023175
Journal or Publication Title:	J. Am. Heart Assoc.
Volume:	11
Number:	6
Date:	2022
Publisher:	WILEY
Place of Publication:	HOBOKEN
ISSN:	2047-9980
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language SYMPTOMATIC INTRACRANIAL HEMORRHAGE; DEEP-VEIN THROMBOSIS; THROMBOLYSIS; PROPHYLAXIS; MORTALITY; DEATH; SCORE Multiple languages Cardiac & Cardiovascular Systems Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/68688