Evidence map›Paper›PMID 39257037›Full record

Observational studyAnnals of clinical and translational neurology2024

Endogenous tPA levels: A biomarker for discriminating hemorrhagic stroke from ischemic stroke and stroke mimics.

Melissa Jauquet, Pierre Gagnepain, Estelle La Porte, Audrey M Thiebaut, Ambre Rochey, Helene Legros, Baptiste Laine, Marion Berthelot, Valerie Roussel, Joan Montaner and 5 more

Abstract readObservational Study
In one paragraph

Observational study in Annals of clinical and translational neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Melissa JauquetNormandie University, UNICAEN, INSERM, UMR-S U1237, Physiopathology and Imaging of Neurological Disorders (PhIND), Institute Blood and Brain @Caen-Normandie (BB@C), GIP Cyceron, Caen, France.
Pierre GagnepainNormandie University, UNICAEN, PSL Research University, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, 14000, France.
Estelle La PorteNormandie University, UNICAEN, INSERM, UMR-S U1237, Physiopathology and Imaging of Neurological Disorders (PhIND), Institute Blood and Brain @Caen-Normandie (BB@C), GIP Cyceron, Caen, France.
Audrey M ThiebautNormandie University, UNICAEN, INSERM, UMR-S U1237, Physiopathology and Imaging of Neurological Disorders (PhIND), Institute Blood and Brain @Caen-Normandie (BB@C), GIP Cyceron, Caen, France.
Ambre RocheyNormandie University, UNICAEN, INSERM, UMR-S U1237, Physiopathology and Imaging of Neurological Disorders (PhIND), Institute Blood and Brain @Caen-Normandie (BB@C), GIP Cyceron, Caen, France.
Helene LegrosCentre de Ressources Biologiques InnovaBIO, Caen University Hospital, Caen, France.
Baptiste LaineDepartment of Clinical Research, Caen University Hospital, Caen, France.
Marion BerthelotNormandie University, UNICAEN, INSERM, UMR-S U1237, Physiopathology and Imaging of Neurological Disorders (PhIND), Institute Blood and Brain @Caen-Normandie (BB@C), GIP Cyceron, Caen, France.
Valerie RousselNormandie University, UNICAEN, INSERM, UMR-S U1237, Physiopathology and Imaging of Neurological Disorders (PhIND), Institute Blood and Brain @Caen-Normandie (BB@C), GIP Cyceron, Caen, France.
Joan MontanerDepartment of Neurology, Hospital Universitario Virgen Macarena, Sevilla, Spain.
Barbara CasollaUR2CA-URRIS, Stroke Unit, CHU Pasteur 2, Nice Cote d'Azur University, Nice, France.
Denis VivienNormandie University, UNICAEN, INSERM, UMR-S U1237, Physiopathology and Imaging of Neurological Disorders (PhIND), Institute Blood and Brain @Caen-Normandie (BB@C), GIP Cyceron, Caen, France.
Eloise LemarchandNormandie University, UNICAEN, INSERM, UMR-S U1237, Physiopathology and Imaging of Neurological Disorders (PhIND), Institute Blood and Brain @Caen-Normandie (BB@C), GIP Cyceron, Caen, France.
Richard Macrez *Normandie University, UNICAEN, INSERM, UMR-S U1237, Physiopathology and Imaging of Neurological Disorders (PhIND), Institute Blood and Brain @Caen-Normandie (BB@C), GIP Cyceron, Caen, France.
Benoit D Roussel *Normandie University, UNICAEN, INSERM, UMR-S U1237, Physiopathology and Imaging of Neurological Disorders (PhIND), Institute Blood and Brain @Caen-Normandie (BB@C), GIP Cyceron, Caen, France.ORCID 0000-0003-0575-8112

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveStroke is the leading cause of death and disability. Timely differentiation between ischemic stroke, hemorrhagic stroke, and stroke mimics is critical for tailored treatment and triage. To accelerate the identification of stroke's subtype, we propose to use the levels of circulating tPA as a biomarker.

methodsBiostroke is an observational study performed at the Caen Hospital. We quantified tPA levels in 110 patients with ischemic strokes, 30 patients with hemorrhagic strokes, and 67 stroke mimic patients upon their arrival at the emergency. Two logistic regression models were formulated: one with parameters measurable in an ambulance (Model A) and one with parameters measurable at the hospital (Model H). These models were both tested with or without plasma tPA measurements. Our initial assessment involved evaluating the effectiveness of both models in distinguishing between hemorrhagic strokes, ischemic strokes, and stroke mimics within our study cohort.

resultsPlasmatic tPA levels exhibit significant distinctions between hemorrhagic, ischemic, and mimic stroke patients (1.8; 2.5; 2.4 ng/mL, respectively). The inclusion of tPA in model A significantly enhances the classification accuracy of hemorrhagic patients only, increasing identification from 0.67 (95% CI, 0.59 to 0.75) to 0.78 (95% CI, 0.7 to 0.85) (p = 0.0098). Similarly, in model H, classification accuracy of hemorrhagic patients significantly increased with the addition of tPA, rising from 0.75 (95% CI, 0.67 to 0.83) without tPA to 0.86 (95% CI, 0.81 to 0.91) with tPA (p = 0.024). INTERPRETATIONS: Our findings underscore the valuable role of tPA levels in distinguishing between stroke subtypes.

Indexed as

BiomarkersHemorrhagic StrokeIschemic StrokeTissue Plasminogen ActivatorAgedAged, 80 and overDiagnosis, DifferentialFemaleHumansMaleMiddle AgedStrokeBiomarkersTissue Plasminogen Activator

Identifiers

PMID39257037
PMCPMC11572725

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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.