Evidence map›Paper›PMID 34472654›Full record

ArticleJournal of cardiac surgery2021

Improving the prediction of long-term readmission and mortality using a novel biomarker panel.

Jeremiah R Brown, Devin M Parker, Meagan E Stabler, Marshall L Jacobs, Jeffrey P Jacobs, Allen D Everett, Kevin W Lobdell, Moritz C Wyler von Ballmoos, Heather Thiessen-Philbrook, Chirag Parikh and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of cardiac surgery, 2021. 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

5 · Who and what money

Authors and funding

16 authors.

Jeremiah R BrownDepartment of Epidemiology, Dartmouth Geisel School of Medicine, Hanover, New Hampshire, USA.ORCID http://orcid.org/0000-0003-4512-9716
Devin M ParkerDepartment of Epidemiology, Dartmouth Geisel School of Medicine, Hanover, New Hampshire, USA.ORCID http://orcid.org/0000-0003-0471-9269
Meagan E StablerDepartment of Epidemiology, Dartmouth Geisel School of Medicine, Hanover, New Hampshire, USA.
Marshall L JacobsDivision of Pediatric Cardiology, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Jeffrey P JacobsDivision of Thoracic and Cardiovascular Surgery, Department of Surgery, University of Florida, Gainesville, Florida, USA.
Allen D EverettDivision of Cardiac Surgery, Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Kevin W LobdellRegional Cardiovascular and Thoracic Quality, Education, and Research, Atrium Health, Charlotte, North Carolina, USA.
Moritz C Wyler von BallmoosDivision of Cardiovascular and Thoracic Surgery, Duke University Medical Center, Durham, North Carolina, USA.
Heather Thiessen-PhilbrookDivision of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
Chirag ParikhDivision of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
Todd MackenzieDepartment of Biomedical Data Science, Geisel School of Medicine, Lebanon, New Hampshire, USA.
Anthony DiScipioDivision of Cardiology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, USA.
David MalenkaDivision of Cardiology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, USA.
Michael E MathenyDepartment of Biomedical Informatics, Vanderbilt University Medical School, Nashville, Tennessee, USA.
Alexander TurchinDivision of Endocrinology, Diabetes and Hypertension, Harvard Medical School, Boston, Massachusetts, USA.
Donald S LikoskyDepartment of Cardiac Surgery, Michigan Medicine, Ann Arbor, Michigan, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Novel Biomarkers to Predict Readmission in Pediatric and Adult Heart SurgeryR01HL119664 · NHLBI · DARTMOUTH COLLEGE · PI BROWN, JEREMIAH R · 2014 to 2017
$3.2M
National Heart Lung and Blood Institute (NHLBI) R01HL119664NCATS NIH HHS UL1 TR001863NHLBI NIH HHS R01 HL119664
6 · The paper itself

Abstract

objectiveSeveral short-term readmission and mortality prediction models have been developed using clinical risk factors or biomarkers among patients undergoing coronary artery bypass graft (CABG) surgery. The use of biomarkers for long-term prediction of readmission and mortality is less well understood. Given the established association of cardiac biomarkers with short-term adverse outcomes, we hypothesized that 5-year prediction of readmission or mortality may be significantly improved using cardiac biomarkers. MATERIALS AND

methodsPlasma biomarkers from 1149 patients discharged alive after isolated CABG surgery from eight medical centers were measured in a cohort from the Northern New England Cardiovascular Disease Study Group between 2004 and 2007. We assessed the added predictive value of a biomarker panel with a clinical model against the clinical model alone and compared the model discrimination using the area under the receiver operating characteristic (AUROC) curves.

resultsIn our cohort, 461 (40%) patients were readmitted or died within 5 years. Long-term outcomes were predicted by applying the STS ASCERT clinical model with an AUROC of 0.69. The biomarker panel with the clinical model resulted in a significantly improved AUROC of 0.74 (p value <.0001). Across 5 years, the hazard ratio for patients in the second to fifth quintile predicted probabilities from the biomarker augmented STS ASCERT model ranged from 2.2 to 7.9 (p values <.001).

conclusionsWe report that a panel of biomarkers significantly improved prediction of long-term readmission or mortality risk following CABG surgery. Our findings suggest biomarkers help clinical care teams better assess the long-term risk of readmission or mortality.

Indexed as

Coronary Artery BypassPatient ReadmissionBiomarkersHospital MortalityHumansRisk FactorsROC CurveBiomarkersbiomarkersCABGcardiac surgeryrisk prediction

Identifiers

PMID34472654
PMCPMC8560027

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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.