Evidence map›Paper›PMID 36712240›Full record

ArticleFrontiers in cardiovascular medicine2022

External validation of the SWEDEHEART score for predicting in-hospital major bleeding among East Asian patients with acute myocardial infarction.

Yabin Liu, Fei Lv, Qucheng Wei, Qiyue Gao, Jun Jiang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2022. 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
0.2field-weighted citation impact, top 49% 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

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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, 1 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 1 institution in 1 country.

Yabin LiuThe Second Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang, China.
Fei LvThe Second Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang, China.
Qucheng WeiThe Second Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang, China.
Qiyue GaoThe Second Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang, China.
Jun JiangThe Second Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang, China.
Second Affiliated Hospital of Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Risk scores for predicting in-hospital major bleeding in patients with acute myocardial infarction (AMI) are rare. The Swedish web-system for the enhancement and development of evidence-based care in heart disease evaluated according to recommended therapies (SWEDEHEART) score (SS), consisting of five common clinical variables, is a novel model for predicting in-hospital major bleeding. External validation of SS has not yet been completed. Methods and results: A retrospective study recruiting consecutive East Asian patients diagnosed with AMI was conducted in the Second Affiliated Hospital, Zhejiang University. The primary endpoint was the ability of SS to predict in-hospital major bleeding, which was defined as Bleeding Academic Research Consortium (BARC) type 3 or 5 bleeding. To validate SS, the discrimination and calibration were assessed in the overall population and several subgroups. The receiver operating characteristic (ROC) curves and the areas under ROC curves (AUCs) were calculated for discrimination. The calibration of SS was evaluated with the unreliability Conclusion: This external validation study showed that SS failed to exhibit sufficient accuracy in predicting in-hospital major bleeding among East Asian patients with AMI despite demonstrating acceptable performance in the diabetic subgroup of patients. Studies to uncover optimal prediction tools for in-hospital major bleeding risk in AMI are urgently warranted.

Indexed as

AMIdiabetesEast Asianin-hospital major bleedingSWEDEHEART score

Identifiers

PMID36712240
PMCPMC9873996
OpenAlexW4315650532

What OpenQuestion holds

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LicenceCC BY
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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.