Evidence map›Paper›PMID 36597038›Full record

ArticleBMC neurology2023

PREDICT-juvenile-stroke: PRospective evaluation of a prediction score determining individual clinical outcome three months after ischemic stroke in young adults - a study protocol.

Sonja Schönecker, Verena Hoffmann, Fady Albashiti, Reinhard Thasler, Marlien Hagedorn, Marie-Luise Louiset, Anna Kopczak, Jennifer Rösler, Enayatullah Baki, Silke Wunderlich and 14 more

Open access · goldAbstract readClinical Trial Protocol
In one paragraph

Article in BMC neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors at 6 institutions in 1 country.

Sonja SchöneckerDepartment of Neurology, Ludwig-Maximilians-Universität München, Marchioninistr. 15, D-81377, Munich, Germany.
Verena HoffmannInstitute for Medical Informatics, Biometry, and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany.
Fady AlbashitiCenter for Medical Data Integration and Analysis, Ludwig-Maximilians-Universität München, Munich, Germany.
Reinhard ThaslerCenter for Medical Data Integration and Analysis, Ludwig-Maximilians-Universität München, Munich, Germany.
Marlien HagedornCenter for Medical Data Integration and Analysis, Ludwig-Maximilians-Universität München, Munich, Germany.
Marie-Luise LouisetInstitute of Laboratory Medicine, Ludwig-Maximilians-Universität München, Munich, Germany.
Anna KopczakInstitute for Stroke and Dementia Research (ISD), Ludwig-Maximilians-Universität München, Munich, Germany.
Jennifer RöslerDepartment of Neurology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Enayatullah BakiDepartment of Neurology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Silke WunderlichDepartment of Neurology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Florian KohlmayerInstitute of Medical Informatics, Statistics and Epidemiology, University Hospital rechts der Isar of the Technical University Munich, Munich, Germany.
Klaus KuhnInstitute of Medical Informatics, Statistics and Epidemiology, University Hospital rechts der Isar of the Technical University Munich, Munich, Germany.
Martin BoekerInstitute of Medical Informatics, Statistics and Epidemiology, University Hospital rechts der Isar of the Technical University Munich, Munich, Germany.
Johannes TünnerhoffDepartment of Neurology & Stroke, Eberhard Karls University Tübingen, Tübingen, Germany.
Sven PoliDepartment of Neurology & Stroke, Eberhard Karls University Tübingen, Tübingen, Germany.
Ulf ZiemannDepartment of Neurology & Stroke, Eberhard Karls University Tübingen, Tübingen, Germany.
Oliver KohlbacherDepartment of Computer Science, Center for Bioinformatics and Quantitative Biology Center, Eberhard-Karls-University Tübingen, Tübingen, Germany.
Katharina AlthausDepartment of Neurology, University of Ulm, Ulm, Germany.
Susanne MüllerDepartment of Neurology, University of Ulm, Ulm, Germany.
Albert LudolphDepartment of Neurology, University of Ulm, Ulm, Germany.
Hans A KestlerIntitute of Medical Systems Biology, University of Ulm, Ulm, Germany.
Ulrich MansmannInstitute for Medical Informatics, Biometry, and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany.
Marianne DieterichDepartment of Neurology, Ludwig-Maximilians-Universität München, Marchioninistr. 15, D-81377, Munich, Germany.
Lars KellertDepartment of Neurology, Ludwig-Maximilians-Universität München, Marchioninistr. 15, D-81377, Munich, Germany. lars.kellert@med.uni-muenchen.de.ORCID http://orcid.org/0000-0002-4967-8336
Ludwig-Maximilians-Universität München · DETUM Klinikum · DEUniversität Ulm · DEHertie Institute for Clinical Brain Research · DEGerman Center for Neurodegenerative Diseases · DEMax Planck Institute for Developmental Biology · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough of high individual and socioeconomic relevance, a reliable prediction model for the prognosis of juvenile stroke (18-55 years) is missing. Therefore, the study presented in this protocol aims to prospectively validate the discriminatory power of a prediction score for the 3 months functional outcome after juvenile stroke or transient ischemic attack (TIA) that has been derived from an independent retrospective study using standard clinical workup data.

methodsPREDICT-Juvenile-Stroke is a multi-centre (n = 4) prospective observational cohort study collecting standard clinical workup data and data on treatment success at 3 months after acute ischemic stroke or TIA that aims to validate a new prediction score for juvenile stroke. The prediction score has been developed upon single center retrospective analysis of 340 juvenile stroke patients. The score determines the patient's individual probability for treatment success defined by a modified Rankin Scale (mRS) 0-2 or return to pre-stroke baseline mRS 3 months after stroke or TIA. This probability will be compared to the observed clinical outcome at 3 months using the area under the receiver operating characteristic curve. The primary endpoint is to validate the clinical potential of the new prediction score for a favourable outcome 3 months after juvenile stroke or TIA. Secondary outcomes are to determine to what extent predictive factors in juvenile stroke or TIA patients differ from those in older patients and to determine the predictive accuracy of the juvenile stroke prediction score on other clinical and paraclinical endpoints. A minimum of 430 juvenile patients (< 55 years) with acute ischemic stroke or TIA, and the same number of older patients will be enrolled for the prospective validation study. DISCUSSION: The juvenile stroke prediction score has the potential to enable personalisation of counselling, provision of appropriate information regarding the prognosis and identification of patients who benefit from specific treatments.

trial registrationThe study has been registered at https://drks.de on March 31, 2022 ( DRKS00024407 ).

Indexed as

Ischemic Attack, TransientIschemic StrokeStrokeAgedHumansObservational Studies as TopicPredictive Value of TestsPrognosisRetrospective StudiesYoung AdultJuvenile strokePrediction scoreThree months outcomeValidation

Identifiers

PMID36597038
PMCPMC9811707
OpenAlexW4313545659

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.