Evidence map›Paper›PMID 32637646›Full record

ArticleEuropean stroke journal2020

Refining prediction of major bleeding on antiplatelet treatment after transient ischaemic attack or ischaemic stroke.

Nina A Hilkens, Linxin Li, Peter M Rothwell, Ale Algra, Jacoba P Greving

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European stroke journal, 2020. 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
0.3field-weighted citation impact, top 41% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

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

5 authors at 2 institutions in 2 countries.

Nina A HilkensJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands.
Linxin LiCentre for Prevention of Stroke and Dementia, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, UK.ORCID https://orcid.org/0000-0002-3636-8355
Peter M RothwellCentre for Prevention of Stroke and Dementia, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, UK.ORCID https://orcid.org/0000-0001-9739-9211
Ale AlgraJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands.
Jacoba P GrevingJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands.ORCID https://orcid.org/0000-0001-8533-2175
Utrecht University · NLJohn Radcliffe Hospital · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

introductionBleeding is the main safety concern of treatment with antiplatelet drugs. We aimed to refine prediction of major bleeding on antiplatelet treatment after a transient ischaemic attack (TIA) or stroke by assessing the added value of new predictors to the existing S PATIENTS AND

methodsWe used Cox regression analysis to study the association between candidate predictors and major bleeding among 2072 patients with a transient ischaemic attack or ischaemic stroke included in a population-based study (Oxford Vascular Study - OXVASC). An updated model was proposed and validated in 1094 patients with a myocardial infarction included in OXVASC. Models were compared with c-statistics, calibration plots, and net reclassification improvement.

resultsIndependent predictors for major bleeding on top of S DISCUSSION AND

conclusionPeptic ulcer, cancer, anaemia and renal failure improve predictive performance of the S

Indexed as

antiplatelet treatmentmajor bleedingpredictionStroke

Identifiers

PMID32637646
PMCPMC7309362
OpenAlexW3001429022

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.