Evidence map›Paper›PMID 41110116›Full record

ArticleTransfusion2025

Predictive accuracy of diagnostic tests for excessive bleeding in cardiac surgery: The COPTIC-C study.

Weiqi Liao, Robert Grant, Florence Y Lai, Hardeep Aujla, Marcin Wozniak, Hasmukh R Patel, Laura Green, Andrew Mumford, Gavin J Murphy

Abstract read
In one paragraph

Article in Transfusion, 2025. 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

9 authors.

Weiqi LiaoDepartment of Cardiovascular Sciences, University of Leicester, UK.ORCID https://orcid.org/0000-0002-8605-3749
Robert GrantDepartment of Cardiovascular Sciences, University of Leicester, UK.
Florence Y LaiDepartment of Cardiovascular Sciences, University of Leicester, UK.
Hardeep AujlaDepartment of Cardiovascular Sciences, University of Leicester, UK.
Marcin WozniakDepartment of Cardiovascular Sciences, University of Leicester, UK.
Hasmukh R PatelDepartment of Cardiovascular Sciences, University of Leicester, UK.
Laura GreenBlizard Institute, Queen Mary University of London, UK.ORCID https://orcid.org/0000-0003-4063-9768
Andrew MumfordBristol Heart Institute, University of Bristol, UK.
Gavin J MurphyDepartment of Cardiovascular Sciences, University of Leicester, UK.

Funding

British Heart Foundation AA/18/3/34220British Heart Foundation CH/12/1/29419British Heart Foundation RG/17/9/32812British Heart Foundation Leicester Accelerator AA/18/3/34220National Institute for Health and Care Research RP-PG-0407-10384NHS Blood and TransplantNIHR Leicester Biomedical Research Centre NIHR203327
6 · The paper itself

Abstract

backgroundWe tested the hypothesis that the addition of biomarkers of multimorbidity and biological aging would improve the predictive accuracy of point-of-care viscoelastometry or laboratory tests of coagulation for clinically important bleeding following cardiac surgery. STUDY DESIGN AND

methodsThis predictive accuracy study included 2437 participants in the coagulation and platelet laboratory testing in cardiac surgery (COPTIC study) with complete clinical, TEG 5000 thromboelastography, ROTEM, multiplate aggregometry, full blood count, laboratory reference tests of coagulopathy, and biomarkers of biological aging and multimorbidity. Models with different biomarkers to predict the composite primary outcome, clinically important bleeding, were developed using logistic regression and internally validated using 10-fold cross-validation. Discrimination, calibration, and clinical utility of the models were assessed comprehensively.

resultsFor the composite primary outcome, the AUROC for the best predictive model using TEG or ROTEM plus other biomarkers was 0.694 (0.612-0.775). The best predictive model overall included laboratory reference tests of coagulation, full blood count results, and biomarkers of multimorbidity and aging, AUROC = 0.701 (0.620-0.781), although clinical utility was not superior to using laboratory reference tests alone. Discrimination was higher for individual components of the primary outcome: large volume (≥4 units) red cell transfusion 0.754 (0.602-0.903) and large volume procoagulant transfusion 0.723 (0.590-0.857), but not for excess loss in drains/re-sternotomy 0.701 (0.613-0.788). Calibration was generally good among the models. DISCUSSION: The addition of biomarkers of multimorbidity and biological aging yielded only small improvements in model predictive accuracy for bleeding over tests of coagulation. Existing clinical definitions of bleeding likely represent heterogeneous phenotypes and disease mechanisms.

Indexed as

Cardiac Surgical ProceduresPostoperative HemorrhageAgedBiomarkersBlood Coagulation TestsFemaleHumansMaleMiddle AgedPredictive Value of TestsThrombelastographyBiomarkersbiomarkerscardiac surgerydiagnostic testspostoperative excessive bleedingpredictive accuracy

Identifiers

PMID41110116
PMCPMC12618898

What OpenQuestion 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 OpenQuestion graph.