Evidence map›Paper›PMID 38939804›Full record

ArticleJACC. Advances2024

How Good Are Cardiologists at Predicting Major Adverse Events in Fontan Patients?

Robert W Elder, Anne Marie Valente, Brooke Davey, Fred Wu, Nancy Drucker, Kristin Lombardi, Seohyuk Lee, Sarah McCollum, Veronika Shabanova, Nicole St Clair and 3 more

Abstract read
In one paragraph

Article in JACC. Advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Correlation between Olink and SomaScan proteomics platforms in adults with a Fontan circulation.International journal of cardiology. Congenital heart disease · 2025
    Article
  3. Review
  4. 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

13 authors.

Robert W ElderDepartment of Pediatrics and Internal Medicine (Cardiology), Yale University School of Medicine, New Haven, Connecticut, USA.
Anne Marie ValenteDepartment of Cardiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Brooke DaveyDivision of Cardiology, Connecticut Children's Hospital, Hartford, Connecticut, USA.
Fred WuDepartment of Cardiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Nancy DruckerDivision of Pediatric Cardiology, The University of Vermont Children's Hospital, Burlington, Vermont, USA.
Kristin LombardiDepartment of Pediatrics, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
Seohyuk LeeDepartment of Pediatrics and Internal Medicine (Cardiology), Yale University School of Medicine, New Haven, Connecticut, USA.
Sarah McCollumDepartment of Pediatrics and Internal Medicine (Cardiology), Yale University School of Medicine, New Haven, Connecticut, USA.
Veronika ShabanovaDepartment of Pediatrics and Internal Medicine (Cardiology), Yale University School of Medicine, New Haven, Connecticut, USA.
Nicole St ClairDepartment of Cardiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Nina AzcueDepartment of Cardiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Olga H Toro-SalazarDivision of Cardiology, Connecticut Children's Hospital, Hartford, Connecticut, USA.
Rahul H RathodDepartment of Cardiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: It is unknown how well cardiologists predict which Fontan patients are at risk for major adverse events (MAEs). Objectives: The purpose of this study was to examine the accuracy of cardiologists' ability to identify the "good Fontan" patient, free from MAE within the following year, and compare that predicted risk cohort to patients who experienced MAE. Methods: This prospective, multicenter study included patients ≥10 years with lateral tunnel or extracardiac Fontan. The cardiologist was asked the yes/no "surprise" question: would you be surprised if your patient has a MAE in the next year? After 12 months, the cardiologist was surveyed to assess MAE. Agreement between cardiologist predictions of MAE and observed MAE was determined using the simple kappa coefficient. Multivariable generalized linear mixed effects models were performed to identify factors associated with MAE. Results: Overall, 146 patients were enrolled, and 99/146 (68%) patients w`ere predicted to be a "good Fontan." After 12 months, 17 (12%) experienced a MAE. The simple kappa coefficient of cardiologists' prediction was 0.17 (95% CI: 0.02-0.32), suggesting prediction of MAE was 17% better than random chance. In the multivariable cardiologist-predicted MAE (N = 47) model, diuretic/beta-blocker use ( Conclusions: Cardiologists are marginally able to predict which Fontan patients are at risk for MAE over a year. There was overlap between factors associated with a cardiologist's prediction of risk and observed MAE, namely the use of diuretic/beta-blocker.

Indexed as

atrioventricular valve regurgitationFontanmajor adverse eventsprediction of risksurprise questionunplanned cardiac admission

Identifiers

PMID38939804
PMCPMC11198720

What OpenQuestion holds

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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.