Evidence map›Paper›PMID 39846077›Full record

ArticleEuropean heart journal. Digital health2025

Performance of computerized self-reported medical history taking and HEAR score for safe early rule-out of cardiac events in acute chest pain patients: the CLEOS-CPDS prospective cohort study.

Helge Brandberg, Fanny Schierenbeck, Carl Johan Sundberg, Sabine Koch, Jonas Spaak, Thomas Kahan

Registry-linked trialAbstract 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. It is linked to trial NCT03439449 (Computerized, Patient-entered Medical Histories for Managing Chest Pain in the Emergency Department), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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.

NCT03439449 active not recruitingnot on this map

Computerized, Patient-entered Medical Histories for Managing Chest Pain in the Emergency Department

Typeobservational_patient_registrySponsorKarolinska InstitutetRan2017 to 2025Enrolled2,000ConditionsChest Pain, Acute Coronary SyndromeArmsCLEOS software program, Physician taken history
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Helge BrandbergDivision of Cardiovascular Medicine, Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, SE-182 88 Stockholm, Sweden.ORCID https://orcid.org/0000-0003-1507-4099
Fanny SchierenbeckDivision of Cardiovascular Medicine, Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, SE-182 88 Stockholm, Sweden.ORCID https://orcid.org/0009-0003-2417-8575
Carl Johan SundbergDepartment of Learning, Informatics, Management and Ethics, Karolinska Institutet, SE-171 77 Stockholm, Sweden.ORCID https://orcid.org/0000-0002-7000-466X
Sabine KochDepartment of Learning, Informatics, Management and Ethics, Karolinska Institutet, SE-171 77 Stockholm, Sweden.ORCID https://orcid.org/0000-0001-7144-8740
Jonas SpaakDivision of Cardiovascular Medicine, Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, SE-182 88 Stockholm, Sweden.ORCID https://orcid.org/0000-0002-2135-1294
Thomas KahanDivision of Cardiovascular Medicine, Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, SE-182 88 Stockholm, Sweden.ORCID https://orcid.org/0000-0001-9909-4956

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: A simplified version of the history, electrocardiogram, age, risk factors, troponin (HEART) score, excluding troponin, has been proposed to rule-out major adverse cardiac events (MACEs). Computerized history taking (CHT) provides a systematic and automated method to obtain information necessary to calculate the HEAR score. We aimed to evaluate the efficacy and diagnostic accuracy of CHT in calculating the HEAR score for predicting MACE. Methods and results: Prospective study including clinically stable adults presenting with chest pain at the emergency department (ED) of Danderyd University Hospital (Stockholm, Sweden), in 2017-19. Participants entered their medical histories on touchscreen tablets using CHT software. The HEAR and HEART scores were calculated from CHT data. Thirty-day MACE and acute coronary syndrome (ACS) outcomes were retrieved, and the diagnostic accuracy was assessed. Logistic regression was used to determine the most predictive components of the HEAR score. Among 1000 patients, HEART and HEAR scores could be calculated from CHT data in 648 and 666 cases, respectively, with negative predictive values [95% confidence interval (CI)] of 0.98 (0.97-0.99) and 0.99 (0.96-1.00). Two patients with HEAR score <2 experienced a 30-day MACE. The age [odds ratio (OR) 2.75, 95% CI 1.62-4.66] and history (OR 2.38, 95% CI 1.52-3.71) components of the HEAR score were most predictive of MACE. Acute coronary syndrome outcomes provided similar results. Conclusion: The HEAR score acquired by CHT identifies very-low-risk patients with chest pain in the ED, safely ruling out ACS and MACE. This highlights the value of computerized history taking by patients, which may reduce unnecessary tests and hospital admissions. Trial Registration: ClinicalTrials.gov NCT03439449.

Indexed as

Artificial intelligenceChest painCoronary artery diseaseMedical history takingMedical informaticsRisk assessment

Identifiers

PMID39846077
PMCPMC11750193

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Registered trials

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.