Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Apr 16, 2025
Date Accepted: Jan 14, 2026

The final, peer-reviewed published version of this preprint can be found here:

Computerized Self-Reported Medical History Taking to Support Early Rule Out of Major Adverse Cardiac Events in Patients With Acute Chest Pain: Post Hoc Analysis of the CLEOS-CPDS Prospective Cohort Study

Brandberg H, Sundberg CJ, Spaak J, Koch S, Kahan T

Computerized Self-Reported Medical History Taking to Support Early Rule Out of Major Adverse Cardiac Events in Patients With Acute Chest Pain: Post Hoc Analysis of the CLEOS-CPDS Prospective Cohort Study

J Med Internet Res 2026;28:e76087

DOI: 10.2196/76087

PMID: 41671573

PMCID: 12936665

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Computerized Self-Reported Medical History-Taking Improves Early Rule-Out of Major Adverse Cardiac Events in Acute Chest Pain Patients: The CLEOS-CPDS Prospective Cohort Study

  • Helge Brandberg; 
  • Carl Johan Sundberg; 
  • Jonas Spaak; 
  • Sabine Koch; 
  • Thomas Kahan

ABSTRACT

Background:

Self-reported, computerized history-taking (CHT) may provide efficient and automated collection of medical histories for calculating risk scores recommended in acute chest pain management.

Objective:

We aimed to determine if risk scores, populated by CHT data, can rule-out a 30-day major adverse cardiac events (MACE), evaluate their diagnostic accuracy, and assess their impact on acute chest pain management.

Methods:

In this prospective cohort study (2017–2019) at a tertiary hospital ED, clinically stable patients aged ≥18 years with chest pain and an ECG not indicating an acute coronary syndrome provided medical histories through a tablet-based CHT program (Clinical Expert Operating System, CLEOS), owned by a public university. The Danderyd History, ECG, Age, Risk factors, and Troponin (D-HEART), HEART, Emergency Department Assessment of Chest Pain Score Accelerated Diagnostic Protocol (EDACS-ADP), and Troponin-only Manchester Acute Coronary Syndrome (T-MACS) scores, were calculated from relevant CHT data and electronic health record (EHR) data, extracted by research staff. EHRs were reviewed for International Classification of Diseases (ICD) codes indicating any 30-day 3-point MACE.

Results:

In the 1,000 participants included (mean age 55±17 years; 46% women), the risk scores could be calculated in 73– 83% using only CHT data, depending on the risk score applied. A 30-day MACE occurred in 7.2% of the total population. The negative predictive value for a 30-day MACE was 0.98–0.99 (95% CI: 0.97–1.00) and a substantial fraction (up to 17%) of patients admitted with acute chest pain could be reclassified from “not low risk” to “low risk” using this method.

Conclusions:

Automated medical history-taking using CHT can offer reliable risk scores in a majority of acute chest pain patients, with high diagnostic accuracy to rule-out a 30-day three-point MACE. This tool could facilitate the management and safe discharge of low-risk patients with acute chest pain in the ED. Clinical Trial: ClinicalTrials.gov NCT03439449. Registration date: 2018-02-13.


 Citation

Please cite as:

Brandberg H, Sundberg CJ, Spaak J, Koch S, Kahan T

Computerized Self-Reported Medical History Taking to Support Early Rule Out of Major Adverse Cardiac Events in Patients With Acute Chest Pain: Post Hoc Analysis of the CLEOS-CPDS Prospective Cohort Study

J Med Internet Res 2026;28:e76087

DOI: 10.2196/76087

PMID: 41671573

PMCID: 12936665

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.