Evidence map›Paper›PMID 35132872›Full record

ArticleJournal of the American Heart Association2022

Automated In-Line Artificial Intelligence Measured Global Longitudinal Shortening and Mitral Annular Plane Systolic Excursion: Reproducibility and Prognostic Significance.

Hui Xue, Jessica Artico, Rhodri H Davies, Robert Adam, Abhishek Shetye, João B Augusto, Anish Bhuva, Fredrika Fröjdh, Timothy C Wong, Miho Fukui and 8 more

Open access · goldAbstract read
In one paragraph

Article in Journal of the American Heart Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
4.9field-weighted citation impact, top 4% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Observational
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Longitudinal Displacement for Left Ventricular Function Assessment.Journal of cardiovascular development and disease · 2025
    Article
  14. Article
  15. Article
  16. Article
  17. The future of cardiovascular magnetic resonance: All-in-one vs. real-time (Part 1).Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2024
    Review
  18. Article
  19. Article
  20. Relationships between heart shape, function, and disease in 38,858 UK biobank participants.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
    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

18 authors at 8 institutions in 5 countries.

Hui XueNational Heart, Lung, and Blood InstituteNational Institutes of Health Bethesda MD.ORCID 0000-0002-4561-5530
Jessica ArticoBarts Heart CentreBarts Health NHS Trust London United Kingdom.
Rhodri H DaviesBarts Heart CentreBarts Health NHS Trust London United Kingdom.
Robert AdamBarts Heart CentreBarts Health NHS Trust London United Kingdom.ORCID 0000-0002-5018-1482
Abhishek ShetyeBarts Heart CentreBarts Health NHS Trust London United Kingdom.
João B AugustoBarts Heart CentreBarts Health NHS Trust London United Kingdom.
Anish BhuvaBarts Heart CentreBarts Health NHS Trust London United Kingdom.
Fredrika FröjdhDepartment of Clinical Physiology Karolinska University Hospital, and Karolinska Institute Stockholm Sweden.
Timothy C WongUPMC Cardiovascular Magnetic Resonance CenterUPMC Pittsburgh PA.ORCID 0000-0002-1045-2698
Miho FukuiMinneapolis Heart InstituteAbbott Northwestern Hospital Minneapolis MN.ORCID 0000-0002-7235-5551
João L CavalcanteMinneapolis Heart InstituteAbbott Northwestern Hospital Minneapolis MN.
Thomas A TreibelBarts Heart CentreBarts Health NHS Trust London United Kingdom.
Charlotte ManistyBarts Heart CentreBarts Health NHS Trust London United Kingdom.
Marianna FontanaUniversity College London London United Kingdom.
Martin UganderDepartment of Clinical Physiology Karolinska University Hospital, and Karolinska Institute Stockholm Sweden.ORCID 0000-0003-3665-2038
James C MoonBarts Heart CentreBarts Health NHS Trust London United Kingdom.ORCID 0000-0001-8071-1491
Erik B SchelbertMinneapolis Heart Institute, United HospitalSt. Paul, Minnesota and Abbott Northwestern Hospital Minneapolis MN.ORCID 0000-0003-0356-4437
Peter KellmanNational Heart, Lung, and Blood InstituteNational Institutes of Health Bethesda MD.ORCID 0000-0002-9875-6070
Barts Health NHS Trust · GBAbbott Northwestern Hospital · USNational Institutes of Health · USKarolinska University Hospital · SEThe Royal Free Hospital · GBThe University of Sydney · AUUniversity of Pittsburgh · USUniversity of Trieste · IT

Funding

British Heart Foundation FS/16/46/32187British Heart Foundation FS/18/21/33447
6 · The paper itself

Abstract

Background Global longitudinal shortening (GL-Shortening) and the mitral annular plane systolic excursion (MAPSE) are known markers in heart failure patients, but measurement may be subjective and less frequently reported because of the lack of automated analysis. Therefore, a validated, automated artificial intelligence (AI) solution can be of strong clinical interest. Methods and Results The model was implemented on cardiac magnetic resonance scanners with automated in-line processing. Reproducibility was evaluated in a scan-rescan data set (n=160 patients). The prognostic association with adverse events (death or hospitalization for heart failure) was evaluated in a large patient cohort (n=1572) and compared with feature tracking global longitudinal strain measured manually by experts. Automated processing took ≈1.1 seconds for a typical case. On the scan-rescan data set, the model exceeded the precision of human expert (coefficient of variation 7.2% versus 11.1% for GL-Shortening,

Indexed as

Artificial IntelligenceHeart FailureHumansMitral ValvePrognosisReproducibility of ResultsStroke VolumeSystoleVentricular Function, Leftartificial intelligencecardiac magnetic resonance imagingglobal longitudinal shortening, reproducibilityimage processingprognosis

Identifiers

PMID35132872
PMCPMC9245823
OpenAlexW4210835724

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.