Predicting hemorrhagic transformation in patients not submitted to reperfusion therapies.

Autor: de Andrade JBC; Universidade Federal de São Paulo, Sao Paulo, SP, Brazil; Columbia University, Doris and Stanley Tananbaum Stroke Center, 710 W 168th St. Neurological Institute of New York. 6TH Floor. NI 614. ZIP 10032. New York City, NY, USA. Electronic address: joao.brainer@unifesp.br., Mohr JP; Columbia University, Doris and Stanley Tananbaum Stroke Center, 710 W 168th St. Neurological Institute of New York. 6TH Floor. NI 614. ZIP 10032. New York City, NY, USA., Lima FO; Universidade de Fortaleza, Fortaleza, Ceará, Brazil; Hospital Geral de Fortaleza, Ceara, Brazil., Carvalho JJF; Hospital Geral de Fortaleza, Ceara, Brazil., de Farias VAE; Universidade Federal do Ceara, Brazil., Oliveira-Filho J; Universidade Federal da Bahia, Brazil., Pontes-Neto OM; Universidade de São Paulo, Ribeirão Preto, Brazil., Bazan R; Universidade Estadual Paulista, Brazil., Merida KLB; Hospital Instituto de Neurologia de Curitiba, Brazil., Franciscato L; Universidade de São Paulo, Ribeirão Preto, Brazil., Pires MM; Universidade Federal da Bahia, Brazil., Modolo GP; Universidade Estadual Paulista, Brazil., Marques MS; Hospital Instituto de Neurologia de Curitiba, Brazil., Miranda RCAN; Universidade Federal de São Paulo, Sao Paulo, SP, Brazil., Silva GS; Universidade Federal de São Paulo, Sao Paulo, SP, Brazil.
Jazyk: angličtina
Zdroj: Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association [J Stroke Cerebrovasc Dis] 2020 Aug; Vol. 29 (8), pp. 104940. Date of Electronic Publication: 2020 Jun 12.
DOI: 10.1016/j.jstrokecerebrovasdis.2020.104940
Abstrakt: Background: Well studied in patients with ischemic stroke after reperfusion therapies (RT), hemorrhagic transformation (HT) is also common in patients not treated with RT and can lead to disability even in initially asymptomatic cases. The best predictors of HT in patients not treated with RT are not well established. Therefore, we aimed to identify predictors of HT in patients not submitted to RT and create a user-friendly predictive score (PROpHET).
Material and Methods: Patients admitted to a Comprehensive Stroke Center from 2015 to 2017 were prospectively evaluated and randomly selected to the derivation cohort. A multivariable logistic regression modeling was built to produce a predictive grading score for HT. The external validation was assessed using datasets from 7 Comprehensive Stroke Centers using the area under the receiver operating characteristic curve (AUROC).
Results: In the derivation group, 448 patients were included in the final analysis. The validation group included 2,683 patients. The score derived from significant predictors of HT in the multivariate logistic regression analysis was male sex (1 point), ASPECTS ≤ 7 (2 points), presence of leukoaraiosis (1 point), hyperdense cerebral middle artery sign (1 point), glycemia at admission ≥180 mg/dL (1 point), cardioembolism (1 point) and lacunar syndrome (-3 points) as a protective factor. The grading score ranges from -3 to 7. A Score ≥3 had 78.2% sensitivity and 75% specificity, and AUROC of 0.82 for all cases of HT. In the validation cohort, our score had an AUROC of 0.83.
Conclusions: The PROpHET is a simple, quick, cost-free, and easy-to-perform tool that allows risk stratification of HT in patients not submitted to RT. A cost-free computerized version of our score is available online with a user-friendly interface.
Competing Interests: Declaration of Competing Interest The authors state not disclosures related to the main subject of this research.
(Copyright © 2020 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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