Evidence map›Paper›PMID 39085620›Full record

ArticleJournal of neurology2024

A novel prediction score determining individual clinical outcome 3 months after juvenile stroke (PREDICT-score).

Verena S Hoffmann, Sonja Schönecker, Moustafa Amin, Paul Reidler, Anna Brauer, Anna Kopczak, Silke Wunderlich, Sven Poli, Katharina Althaus, Susanne Müller and 2 more

Abstract read
In one paragraph

Article in Journal of neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

12 authors.

Verena S HoffmannInstitute for Medical Information Processing, Biometry and Epidemiology, Faculty of Medicine, Ludwig-Maximilians University München, Marchioninistr. 15, 81377, Munich, Germany.ORCID http://orcid.org/0000-0003-1478-5390
Sonja SchöneckerDepartment of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.ORCID http://orcid.org/0000-0003-4499-7861
Moustafa AminInstitute for Medical Information Processing, Biometry and Epidemiology, Faculty of Medicine, Ludwig-Maximilians University München, Marchioninistr. 15, 81377, Munich, Germany.
Paul ReidlerDepartment of Radiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany.ORCID http://orcid.org/0000-0001-7961-3018
Anna BrauerInstitute for Medical Information Processing, Biometry and Epidemiology, Faculty of Medicine, Ludwig-Maximilians University München, Marchioninistr. 15, 81377, Munich, Germany.
Anna KopczakInstitute for Stroke and Dementia Research (ISD), Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany.ORCID http://orcid.org/0000-0002-5037-2342
Silke WunderlichDepartment of Neurology, University Hospital Rechts der Isar of the Technical University Munich, Munich, Germany.ORCID http://orcid.org/0000-0003-1208-3686
Sven PoliDepartment of Neurology & Stroke, Hertie Institute for Clinical Brain Research, Eberhard-Karls-University Tübingen, Tübingen, Germany.ORCID http://orcid.org/0000-0002-0286-8781
Katharina AlthausDepartment of Neurology, University of Ulm, Ulm, Germany.ORCID http://orcid.org/0000-0002-9004-4335
Susanne MüllerDepartment of Neurology, University of Ulm, Ulm, Germany.ORCID http://orcid.org/0009-0007-6099-4333
Ulrich MansmannInstitute for Medical Information Processing, Biometry and Epidemiology, Faculty of Medicine, Ludwig-Maximilians University München, Marchioninistr. 15, 81377, Munich, Germany.ORCID http://orcid.org/0000-0002-9955-8906
Lars KellertDepartment of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany. lars.kellert@med.uni-muenchen.de.ORCID http://orcid.org/0000-0002-4967-8336

Funding

Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie 01ZZ1804BBundesministerium für Bildung, Wissenschaft, Forschung und Technologie 01ZZ1804C
6 · The paper itself

Abstract

backgroundJuvenile strokes (< 55 years) account for about 15% of all ischemic strokes. Structured data on clinical outcome in those patients are sparse. Here, we aimed to fill this gap by systematically collecting relevant data and modeling a juvenile stroke prediction score for the 3-month functional outcome.

methodsWe retrospectively integrated and analyzed clinical and outcome data of juvenile stroke and TIA patients treated at the LMU University Hospital, LMU Munich, Munich. Good outcome was defined as a modified Rankin Scale of 0-2 or return to baseline of function. We analyzed candidate predictors and developed a predictive model. Predictive abilities were inspected using Area Under the ROC curve (AUROC) and visual representation of the calibration. The model was validated internally.

results346 patients were included in the analysis. We observed a good outcome in n = 293 patients (84.7%). The prediction model for an unfavourable outcome had an AUROC of 89.1% (95% CI 83.3-93.1%). The model includes age NIHSS, ASPECTS, blood glucose and type of vessel occlusion as predictors for the individual patient outcome.

conclusionsHere, we introduce the highly accurate PREDICT-score for the 3-month outcome after juvenile stroke derived from clinical routine data. The PREDICT-score might be helpful in guiding individual patient decisions and designing future studies but needs further prospective validation which is already planned. Trial registration The study has been registered at https://drks.de (DRKS00024407) on March 31, 2022.

Indexed as

Ischemic StrokeAdultAge FactorsFemaleHumansIschemic Attack, TransientMaleMiddle AgedOutcome Assessment, Health CarePrognosisRetrospective StudiesSeverity of Illness IndexStroke3-month outcomeJuvenile strokePrediction scorePredictive factors

Identifiers

PMID39085620
PMCPMC11377658

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.