Evidence map›Paper›PMID 40984999›Full record

ArticleEuropean heart journal. Digital health2025

The hope and the hype of artificial intelligence for syncope management.

Samuel L Johnston, E John Barsotti, Constantinos Bakogiannis, Artur Fedorowski, Fabrizio Ricci, Eric G Heller, Robert S Sheldon, Richard Sutton, Win-Kuang Shen, Venkatesh Thiruganasambandamoorthy and 29 more

Abstract read
In one paragraph

Article in European heart journal. Digital health, 2025. 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. Review
  2. Review
  3. Review
  4. 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

39 authors.

Samuel L JohnstonDivision of Cardiovascular Medicine, Division of Cardiology, Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA.ORCID https://orcid.org/0000-0002-5926-679X
E John BarsottiDepartment of Epidemiology, College of Public Health, University of Iowa, Iowa City, IA, USA.
Constantinos BakogiannisDepartment of Cardiology, Aristotle University of Thessaloniki, Thessaloniki, Greece.ORCID https://orcid.org/0000-0002-2423-4595
Artur FedorowskiDepartment of Cardiology, Karolinska University Hospital, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-5352-6327
Fabrizio RicciDepartment of Neurosciences, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, University G. d'Annunzio, Chieti, Italy.ORCID https://orcid.org/0000-0002-1401-6623
Eric G HellerDivision of Cardiovascular Medicine, Division of Cardiology, Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA.
Robert S SheldonLibin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.ORCID https://orcid.org/0000-0002-3463-4082
Richard SuttonDepartment of Cardiology, Hammersmith Hospital, National Heart & Lung Institute, Imperial College, London, UK.ORCID https://orcid.org/0000-0002-5710-1094
Win-Kuang ShenDepartment of Cardiovascular Diseases, Mayo Clinic Arizona, Phoenix, AZ, USA.ORCID https://orcid.org/0000-0003-1915-9815
Venkatesh ThiruganasambandamoorthyDepartment of Emergency Medicine and School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada.ORCID https://orcid.org/0000-0003-4373-3688
Mehul AdhadukDivision of Cardiovascular Medicine, Division of Cardiology, Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA.ORCID https://orcid.org/0000-0001-9455-5127
William H ParkerDivision of Cardiovascular Medicine, Division of Cardiology, Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA.ORCID https://orcid.org/0000-0003-3426-3709
Arwa AburizikDivision of Hematology-Oncology and Bone Marrow Transplant, Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA, USA.ORCID https://orcid.org/0000-0002-7871-7189
Corey R HaseltonDepartment of Neurology, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA, USA.
Alex J CuskeyDivision of Cardiovascular Medicine, Division of Cardiology, Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA.
Sangil LeeDepartment of Emergency Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA, USA.ORCID https://orcid.org/0000-0001-8529-4500
Madeleine JohanssonDepartment of Clinical Sciences, Lund University, Malmö, Sweden.ORCID https://orcid.org/0000-0001-9057-9148
Donald MacfarlaneDivision of Hematology-Oncology and Bone Marrow Transplant, Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA, USA.ORCID https://orcid.org/0000-0001-8785-5690
Paari DominicDivision of Cardiovascular Medicine, Division of Cardiology, Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA.ORCID https://orcid.org/0000-0002-7843-375X
Haruhiko AbeDepartment of Heart Rhythm Management, University of Occupational and Environmental Health, Kitakyushu, Japan.ORCID https://orcid.org/0000-0001-8712-5137
B Hygriv RaoDivision of Pacing and Electrophysiology, KIMS Hospitals, Hyderabad, India.ORCID https://orcid.org/0000-0001-6660-6046
Avinash MudireddyThe Iowa Initiative for Artificial Intelligence, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, IA, USA.ORCID https://orcid.org/0000-0002-5252-6990
Milan SonkaThe Iowa Initiative for Artificial Intelligence, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, IA, USA.ORCID https://orcid.org/0000-0002-9613-9968
Roopinder K SandhuLibin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.ORCID https://orcid.org/0000-0002-2629-3476
Rose Anne KennyDepartment of Medical Gerontology, School of Medicine, Trinity College, Dublin, Ireland.ORCID https://orcid.org/0000-0002-9336-8124
Giselle M StatzDivision of Cardiovascular Medicine, Division of Cardiology, Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA.
Rakesh GopinathannairKansas City Heart Rhythm Institute, Overland Park, Kansas City, KS, USA.ORCID https://orcid.org/0000-0003-4611-3687
David BendittCardiovascular Division, University of Minnesota, Minneapolis, MN, USA.ORCID https://orcid.org/0000-0002-8511-6920
Franca DipaolaInternal Medicine, IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, Italy.ORCID https://orcid.org/0000-0002-1557-8935
Mauro GattiIBM, Active Intelligence Center, Bologna, Italy.ORCID https://orcid.org/0000-0002-4312-8835
Roberto MenèDepartment of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.
Alessandro Giaj LevraDepartment of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, Milan, Italy.ORCID https://orcid.org/0000-0001-7779-5276
Dana ShifferDepartment of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, Milan, Italy.
Giorgio CostantinoEmergency Department, IRCCS Ca' Granda, Ospedale Maggiore, Milan, Italy.
Raffaello FurlanInternal Medicine, IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, Italy.ORCID https://orcid.org/0000-0001-5209-6786
Martin H RuwaldDepartment of Cardiology, Copenhagen University Hospital Gentofte, Copenhagen, Denmark.ORCID https://orcid.org/0000-0002-1541-309X
Vassilios VassilikosDepartment of Cardiology, Aristotle University of Thessaloniki, Thessaloniki, Greece.ORCID https://orcid.org/0000-0003-0885-9170
Milena A GebskaDivision of Cardiovascular Medicine, Division of Cardiology, Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA.ORCID https://orcid.org/0000-0003-2242-4034
Brian OlshanskyDivision of Cardiovascular Medicine, Division of Cardiology, Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA.ORCID https://orcid.org/0000-0002-6044-045X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Syncope remains a diagnostic challenge despite advancements in testing and treatment. Cardiac syncope is an independent predictor of mortality and can be difficult to distinguish from other causes of transient loss of consciousness (TLOC). This paper explores whether artificial intelligence (AI) can improve the evaluation and management of patients with syncope. Methods and results: We conducted a literature review and incorporated the opinions of experts in the fields of syncope and AI. The cause of TLOC is often unclear, hospitalization criteria are ambiguous, diagnostic tests are frequently non-informative, and assessments are costly. Patients are left with unanswered questions and limited guidance. Artificial intelligence (AI) has the potential to optimize syncope evaluation by processing large data sets, detecting imperceptible patterns, and assisting clinicians. However, AI has limitations, including errors, lack of human empathy, and uncertain clinical utility. Liability issues further complicate its integration. We present three viewpoints: (i) AI is crucial for advancing syncope management; (ii) AI can enhance the patient experience; and (iii) AI in syncope care is inevitable. Conclusion: Artificial intelligence may improve syncope diagnosis and management, particularly through machine learning-based test interpretation and wearable device data. However, it has yet to surpass human clinical judgment in complex decision-making. Current challenges include gaps in understanding syncope mechanisms, AI interpretability, generalizability, and clinical integration. Standardized diagnostic approaches, real-world validation, and curated data sets are essential for progress. Artificial intelligence may enhance efficiency and communication but raises concerns regarding confidentiality, bias, inequities, and legal implications.

Indexed as

Artificial intelligenceClinical managementHopeHypePatient experienceSyncope

Identifiers

PMID40984999
PMCPMC12450521

What Socratic 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 Socratic graph.