Evidence map›Paper›PMID 36201099›Full record

ArticleThe international journal of cardiovascular imaging2022

Machine learning evaluation of LV outflow obstruction in hypertrophic cardiomyopathy using three-chamber cardiovascular magnetic resonance.

Manisha Sahota, Sepas Ryan Saraskani, Hao Xu, Liandong Li, Abdul Wahab Majeed, Uxio Hermida, Stefan Neubauer, Milind Desai, William Weintraub, Patrice Desvigne-Nickens and 6 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The international journal of cardiovascular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Cardiovascular magnetic resonance-derived metrics as diagnostic markers for left ventricular outflow tract obstruction in hypertrophic cardiomyopathy.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 8 institutions in 3 countries.

Manisha Sahota *Department of Biomedical Engineering, King's College London, 1 Lambeth Palace Rd, London, SE1 7EU, UK.
Sepas Ryan Saraskani *Department of Biomedical Engineering, King's College London, 1 Lambeth Palace Rd, London, SE1 7EU, UK.
Hao XuDepartment of Biomedical Engineering, King's College London, 1 Lambeth Palace Rd, London, SE1 7EU, UK.
Liandong LiDepartment of Biomedical Engineering, King's College London, 1 Lambeth Palace Rd, London, SE1 7EU, UK.
Abdul Wahab MajeedDepartment of Biomedical Engineering, King's College London, 1 Lambeth Palace Rd, London, SE1 7EU, UK.
Uxio HermidaDepartment of Biomedical Engineering, King's College London, 1 Lambeth Palace Rd, London, SE1 7EU, UK.
Stefan NeubauerDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Milind DesaiCardiovascular Institute, Cleveland Clinic, Cleveland, OH, USA.
William WeintraubMedStar Heart and Vascular Institute, Washington, DC, USA.
Patrice Desvigne-NickensNational Heart, Lung, and Blood Institute, Bethesda, MD, USA.
Jeanette Schulz-MengerECRC and Department of Cardiology, HELIOS Klinik Berlin-Buch, Clinic for Cardiology and Nephrology, DZHK Partnersite Berlin, Charité Medical University Berlin, Berlin, Germany.
Raymond Y KwongCardiovascular Division, Department of Medicine and Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.
Christopher M KramerCardiovascular Division, University of Virginia Health, Charlottesville, VA, USA.
Alistair A YoungDepartment of Biomedical Engineering, King's College London, 1 Lambeth Palace Rd, London, SE1 7EU, UK. alistair.young@kcl.ac.uk.
Pablo LamataDepartment of Biomedical Engineering, King's College London, 1 Lambeth Palace Rd, London, SE1 7EU, UK.
HCMR investigators
King's College London · GBBrigham and Women's Hospital · USCharité - Universitätsmedizin Berlin · DECleveland Clinic · USMedStar Heart & Vascular Institute · USNational Heart Lung and Blood Institute · USUniversity of Oxford · GBUniversity of Virginia · US

Funding

HCMR Novel Markers of Prognosis in Hypertrophic CardiomyopathyU01HL117006 · NHLBI · UNIVERSITY OF VIRGINIA · PI KRAMER, CHRISTOPHER M., NEUBAUER, STEFAN · 2013 to 2017
$14.5M
The Cardiac Atlas ProjectR01HL121754 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MCCULLOCH, ANDREW D., OMENS, JEFFREY H. · 2014 to 2023
$5.0M
British Heart Foundation PG/16/75/32383NHLBI NIH HHS R01 HL121754NHLBI NIH HHS U01 HL117006NHLBI NIH HHS U01HL117006-01A1Wellcome Trust 209450/Z/17/Z
6 · The paper itself

Abstract

Left ventricular outflow tract obstruction (LVOTO) is common in hypertrophic cardiomyopathy (HCM), but relationships between anatomical metrics and obstruction are poorly understood. We aimed to develop machine learning methods to evaluate LVOTO in HCM patients and quantify relationships between anatomical metrics and obstruction. This retrospective analysis of 1905 participants of the HCM Registry quantified 11 anatomical metrics derived from 14 landmarks automatically detected on the three-chamber long axis cine CMR images. Linear and logistic regression was used to quantify strengths of relationships with the presence of LVOTO (defined by resting Doppler pressure drop of > 30 mmHg), using the area under the receiver operating characteristic (AUC). Intraclass correlation coefficients between the network predictions and three independent observers showed similar agreement to that between observers. The distance from anterior mitral valve leaflet tip to basal septum (AML-BS) was most highly correlated with Doppler pressure drop (R

Indexed as

Cardiomyopathy, HypertrophicMagnetic Resonance SpectroscopyVentricular Outflow ObstructionHumansMachine LearningPredictive Value of TestsRetrospective StudiesAtlas shape analysisHypertrophic cardiomyopathyLV outflow tract obstruction

Identifiers

PMID36201099
PMCPMC9708771
OpenAlexW4302288218

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.