Evidence map›Paper›PMID 39450233›Full record

ArticleFrontiers in cardiovascular medicine2024

Prevalence and predictors of false positive QTc prolongation by the automated measurement.

Wael Alqarawi, Marwah Allwaim

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. QTcNet: a deep learning model for direct heart rate corrected QT interval estimation.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025
    Article
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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Wael AlqarawiDepartment of Cardiac Sciences, College of Medicine, King Saud University, Riyadh, Saudi Arabia.
Marwah AllwaimDepartment of Cardiac Sciences, College of Medicine, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Corrected QT (QTc) is an important electrocardiographic (ECG) interval. Physicians rely on automated QTc provided by ECG machines while the manual method is the recommended method. We sought to assess the prevalence and predictors of false positive QTc prolongation by the automated measurement. Methods and results: Consecutive ECGs were retrieved from the ECG database at King Khaled University Hospital. Manual QT was measured by a trained physician using the tangent method and was corrected for heart rate and QRS duration. Automated QTc measurement was recorded by the ECG machine. "Long QT (LQT)" was defined as QTc≥470 ms for males and ≥480 for females. False positive LQT was defined as LQT by automated QTc but not manual QTc. Pre-determined factors were included in a multivariate logistic regression to assess predictors of false positive LQT. A total of 567 ECGs were included in this study. Automated QTc was longer than manual QTc (440 ms [±35] vs. 417 ms [±35], respectively) which resulted in a high negative predictive value (NPV) (99%) and a low positive predictive value (PPV) (32%). Male gender and abnormal rhythm were found to be independently associated with false positive LQT (OR = 1.9 [95% 1.1-3.5], Conclusion: Automated QTc measurement is unreliable for detecting long QT, necessitating manual verification and further research to enhance its accuracy.

Indexed as

atrial fibrillationautomated QTBazett's formulaQT measurementtangent method

Identifiers

PMID39450233
PMCPMC11499183

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