Evidence map›Paper›PMID 36914189›Full record

ArticleBMJ open2023

Multivariable prediction models for atrial fibrillation after cardiac surgery: a systematic review protocol.

Kara G Fields, Jie Ma, Tatjana Petrinic, Hassan Alhassan, Anthony Eze, Ankith Reddy, Mona Hedayat, Rui Providencia, Gregory Y H Lip, Jonathan P Bedford and 6 more

Abstract read
In one paragraph

Article in BMJ open, 2023. 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

16 authors.

Kara G FieldsDepartment of Anesthesiology, Perioperative and Pain Medicine, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0002-8910-4863
Jie MaCentre for Statistics in Medicine, Nuffield Department of Orthopedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.ORCID 0000-0002-3900-1903
Tatjana PetrinicBodleian Health Care Libraries, University of Oxford, Oxford, UK.
Hassan AlhassanDepartment of Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.ORCID 0000-0003-1663-1045
Anthony EzeDepartment of Surgery, Duke University Medical Center, Durham, North Carolina, USA.ORCID 0000-0003-2534-4515
Ankith ReddyUniversity of Texas Medical Branch, School of Medicine, Galveston, Texas, USA.ORCID 0000-0001-7979-7611
Mona HedayatDepartment of Anesthesiology, Perioperative and Pain Medicine, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0009-0005-8125-5914
Rui ProvidenciaInstitute of Health Informatics Research, University College London, London, UK.ORCID 0000-0001-9141-9883
Gregory Y H LipLiverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, UK.ORCID 0000-0002-7566-1626
Jonathan P BedfordKadoorie Centre for Critical Care Research and Education, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0001-9455-022X
David A CliftonDepartment of Engineering Science, University of Oxford, Oxford, UK.ORCID 0000-0002-9848-8555
Oliver C RedfernKadoorie Centre for Critical Care Research and Education, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0002-3596-3806
Benjamin O'BrienDepartment of Cardiac Anesthesiology and Intensive Care Medicine, Deutsches Herzzentrum Berlin, Charité Universitätsmedizin Berlin, Berlin, Germany.ORCID 0000-0001-7024-2337
Peter J WatkinsonKadoorie Centre for Critical Care Research and Education, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0003-1023-3927
Gary S CollinsCentre for Statistics in Medicine, Nuffield Department of Orthopedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.ORCID 0000-0002-2772-2316
Jochen D MuehlschlegelDepartment of Anesthesiology, Perioperative and Pain Medicine, Harvard Medical School, Boston, Massachusetts, USA jmuehlschlegel@bwh.harvard.edu.ORCID 0000-0002-6209-7253

Funding

Genomics of Post-Operative Atrial Fibrillation After Cardiac SurgeryR01HL149998 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI MUEHLSCHLEGEL, JOCHEN DANIEL, STRANGER, BARBARA E · 2021 to 2024
$3.1M
NHLBI NIH HHS R01 HL149998
6 · The paper itself

Abstract

introductionDozens of multivariable prediction models for atrial fibrillation after cardiac surgery (AFACS) have been published, but none have been incorporated into regular clinical practice. One of the reasons for this lack of adoption is poor model performance due to methodological weaknesses in model development. In addition, there has been little external validation of these existing models to evaluate their reproducibility and transportability. The aim of this systematic review is to critically appraise the methodology and risk of bias of papers presenting the development and/or validation of models for AFACS.

methodsWe will identify studies that present the development and/or validation of a multivariable prediction model for AFACS through searches of PubMed, Embase and Web of Science from inception to 31 December 2021. Pairs of reviewers will independently extract model performance measures, assess methodological quality and assess risk of bias of included studies using extraction forms adapted from a combination of the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist and the Prediction Model Risk of Bias Assessment Tool. Extracted information will be reported by narrative synthesis and descriptive statistics. ETHICS AND DISSEMINATION: This systemic review will only include published aggregate data, so no protected health information will be used. Study findings will be disseminated through peer-reviewed publications and scientific conference presentations. Further, this review will identify weaknesses in past AFACS prediction model development and validation methodology so that subsequent studies can improve upon prior practices and produce a clinically useful risk estimation tool. PROSPERO REGISTRATION NUMBER: CRD42019127329.

Indexed as

Atrial FibrillationCardiac Surgical ProceduresBiasHumansReproducibility of ResultsReview Literature as TopicSystematic Reviews as TopicCardiologyCardiothoracic surgeryPacing & electrophysiology

Identifiers

PMID36914189
PMCPMC10016290

What OpenQuestion holds

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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.