Evidence map›Paper›PMID 35930034›Full record

ArticleClinical research in cardiology : official journal of the German Cardiac Society2023

Prognostic model for atrial fibrillation after cardiac surgery: a UK cohort study.

Sheng-Chia Chung, Benjamin O'Brien, Gregory Y H Lip, Kara G Fields, Jochen D Muehlschlegel, Anshul Thakur, David Clifton, Gary S Collins, Peter Watkinson, Rui Providencia

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical research in cardiology : official journal of the German Cardiac Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. 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

10 authors.

Sheng-Chia Chung *Institute of Health Informatics Research, University College London, London, UK.
Benjamin O'Brien *St. Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK. ben.obrien@charite.de.ORCID http://orcid.org/0000-0001-7024-2337
Gregory Y H LipLiverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart and Chest Hospital, Liverpool, UK.
Kara G FieldsDepartment of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Jochen D MuehlschlegelDepartment of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Anshul ThakurDepartment of Engineering Science, University of Oxford, Oxford, UK.
David CliftonDepartment of Engineering Science, University of Oxford, Oxford, UK.
Gary S CollinsCentre for Statistics in Medicine, Botnar Research Centre, NDORMS, University of Oxford, Oxford, UK.
Peter WatkinsonNIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Rui ProvidenciaInstitute of Health Informatics Research, University College London, London, UK.

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
National Institute for Health Research NIHR131227NHLBI NIH HHS R01 HL149998
6 · The paper itself

Abstract

objectiveTo develop a validated clinical prognostic model to determine the risk of atrial fibrillation after cardiac surgery as part of the PARADISE project (NIHR131227).

methodsProspective cohort study with linked electronic health records from a cohort of 5.6 million people in the United Kingdom Clinical Practice Research Datalink from 1998 to 2016. For model development, we considered a priori candidate predictors including demographics, medical history, medications, and clinical biomarkers. We evaluated associations between covariates and the AF incidence at the end of follow-up using logistic regression with the least absolute shrinkage and selection operator. The model was validated internally with the bootstrap method; subsequent performance was examined by discrimination quantified with the c-statistic and calibration assessed by calibration plots. The study follows TRIPOD guidelines.

resultsBetween 1998 and 2016, 33,464 patients received cardiac surgery among the 5,601,803 eligible individuals. The final model included 13-predictors at baseline: age, year of index surgery, elevated CHA

conclusionsWe developed a model to identify a group of individuals at high risk of AF and adverse outcomes who could benefit from long-term arrhythmia monitoring, risk factor management, rhythm control and/or thromboprophylaxis.

Indexed as

Atrial FibrillationCardiac Surgical ProceduresVenous ThromboembolismAnticoagulantsCohort StudiesHumansPrognosisProspective StudiesRisk AssessmentRisk FactorsAnticoagulantsAtrial fibrillationAtrial fibrillation after cardiac surgeryCardiac surgeryElectronic health recordsEpidemiologyPrognostic modelRisk predictionRisk scoreUnited Kingdom

Identifiers

PMID35930034
PMCPMC9898166

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.