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How Good Are Cardiologists at Predicting Major Adverse Events in Fontan Patients?
Elder, Robert W; Valente, Anne Marie; Davey, Brooke; Wu, Fred; Drucker, Nancy; Lombardi, Kristin; Lee, Seohyuk; McCollum, Sarah; Shabanova, Veronika; St Clair, Nicole; Azcue, Nina; Toro-Salazar, Olga H; Rathod, Rahul H.
Afiliação
  • Elder RW; Department of Pediatrics and Internal Medicine (Cardiology), Yale University School of Medicine, New Haven, Connecticut, USA.
  • Valente AM; Department of Cardiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Davey B; Division of Cardiology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Wu F; Division of Cardiology, Connecticut Children's Hospital, Hartford, Connecticut, USA.
  • Drucker N; Department of Cardiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Lombardi K; Division of Cardiology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Lee S; Division of Pediatric Cardiology, The University of Vermont Children's Hospital, Burlington, Vermont, USA.
  • McCollum S; Department of Pediatrics, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
  • Shabanova V; Department of Pediatrics and Internal Medicine (Cardiology), Yale University School of Medicine, New Haven, Connecticut, USA.
  • St Clair N; Department of Pediatrics and Internal Medicine (Cardiology), Yale University School of Medicine, New Haven, Connecticut, USA.
  • Azcue N; Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA.
  • Toro-Salazar OH; Department of Pediatrics and Internal Medicine (Cardiology), Yale University School of Medicine, New Haven, Connecticut, USA.
  • Rathod RH; Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA.
JACC Adv ; 3(1): 100736, 2024 Jan.
Article em En | MEDLINE | ID: mdl-38939804
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 (P ≤ 0.001) and systolic dysfunction (P = 0.005) were associated with MAE. In the observed multivariable MAE (N = 17) model, prior unplanned cardiac admission (P = 0.006), diuretic/beta-blocker use (P = 0.028), and ≥moderate atrioventricular valve regurgitation (P = 0.049) were associated with MAE.

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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: JACC Adv Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: JACC Adv Ano de publicação: 2024 Tipo de documento: Article