Evidence map›Paper›PMID 37820551›Full record

ArticleThe American journal of cardiology2023

Impact of a Center of Excellence in Confirming or Excluding a Diagnosis of Hypertrophic Cardiomyopathy.

Elizabeth Farrar, Kenneth C Bilchick, Sneha R Gadi, Nisha Hosadurg, Christopher M Kramer, Amit R Patel, Karen Mcclean, Matthew Thomas, Michael P Ayers

Open access · hybridAbstract read
In one paragraph

Article in The American journal of cardiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 23% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
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

9 authors at 1 institution in 1 country.

Elizabeth FarrarCardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia. Electronic address: eaf2yhz@virginia.edu.
Kenneth C BilchickCardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia.
Sneha R GadiCardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia.
Nisha HosadurgCardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia.
Christopher M KramerCardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia; Department of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia.
Amit R PatelCardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia.
Karen MccleanCardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia.
Matthew ThomasCardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia.
Michael P AyersCardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia.
University of Virginia Health System · US

Funding

Training in Cardiovascular Imaging ResearchT32EB003841 · NIBIB · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Jonathan R Lindner · 2004 to 2026
$4.4M
Multiscale Models for Predicting Short and Long-term Outcome of Cardiac Resynchronization TherapyR01HL159945 · NHLBI · UNIVERSITY OF VIRGINIA · PI BILCHICK, KENNETH C, HOLMES, JEFFREY W · 2021 to 2024
$2.6M
NHLBI NIH HHS R01 HL159945NIBIB NIH HHS T32 EB003841
6 · The paper itself

Abstract

Tertiary hospitals with expertise in hypertrophic cardiomyopathy (HCM) are assuming a greater role in confirming and correcting HCM diagnoses at referring centers. The objectives were to establish the frequency of alternate diagnoses from referring centers and identify predictors of accuracy of an HCM diagnosis from the referring centers. Imaging findings from echocardiography, cardiac computed tomography, and cardiac magnetic resonance imaging (CMR) in 210 patients referred to an HCM Center of Excellence between September 2020 and October 2022 were reviewed. Clinical and imaging characteristics from pre-referral studies were used to construct a model for predictors of ruling out HCM or confirming the diagnosis using machine learning methods (least absolute shrinkage and selection operator logistic regression). Alternative diagnoses were found in 38 of the 210 patients (18.1%) (median age 60 years, 50% female). A total of 17 of the 38 patients (44.7%) underwent a new CMR after their initial visit, and 14 of 38 patients (36.8%) underwent review of a previous CMR. Increased left ventricular end-diastolic volume, indexed, greater septal thickness measurements, greater left atrial size, asymmetric hypertrophy on echocardiography, and the presence of an implantable cardioverter-defibrillator were associated with higher odds ratios for confirming a diagnosis of HCM, whereas increasing age and the presence of diabetes were more predictive of rejecting a diagnosis of HCM (area under the curve 0.902, p <0.0001). In conclusion, >1 in 6 patients with presumed HCM were found to have an alternate diagnosis after review at an HCM Center of Excellence, and both clinical findings and imaging parameters predicted an alternate diagnosis.

Indexed as

Cardiomyopathy, HypertrophicEchocardiographyFemaleHeart AtriaHumansMagnetic Resonance ImagingMaleMiddle Agedcardiac magnetic resonance imagingcardiomyopathyCenter of Excellenceechocardiographygenetic screeninghypertrophic cardiomyopathy

Identifiers

PMID37820551
PMCPMC10792590
OpenAlexW4387443151

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.