Evidence map›Paper›PMID 27317349›Full record

ArticleJournal of the American Heart Association2016

Which QT Correction Formulae to Use for QT Monitoring?

Bert Vandenberk, Eline Vandael, Tomas Robyns, Joris Vandenberghe, Christophe Garweg, Veerle Foulon, Joris Ector, Rik Willems

Erratum issuedOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Heart Association, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 191 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
191citing papers in PubMed, 4 pooled it
20.0field-weighted citation impact, top 1% 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

191 citing papers in PubMed, 4 syntheses or guidelines pooled it, 384 citations in OpenAlex.

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  4. Risk factors for QTc-prolongation: systematic review of the evidence.International journal of clinical pharmacy · 2017
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131 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Bert VandenberkDepartment of Cardiovascular Sciences, University of Leuven, Belgium Department of Cardiology, University Hospitals Leuven, Leuven, Belgium bert.vandenberk@med.kuleuven.be.
Eline VandaelDepartment of Pharmaceutical and Pharmacological Sciences, University of Leuven, Belgium.
Tomas RobynsDepartment of Cardiovascular Sciences, University of Leuven, Belgium Department of Cardiology, University Hospitals Leuven, Leuven, Belgium.
Joris VandenbergheDepartment of Neurosciences, University of Leuven, Belgium.
Christophe GarwegDepartment of Cardiovascular Sciences, University of Leuven, Belgium Department of Cardiology, University Hospitals Leuven, Leuven, Belgium.
Veerle FoulonDepartment of Pharmaceutical and Pharmacological Sciences, University of Leuven, Belgium.
Joris EctorDepartment of Cardiovascular Sciences, University of Leuven, Belgium Department of Cardiology, University Hospitals Leuven, Leuven, Belgium.
Rik WillemsDepartment of Cardiovascular Sciences, University of Leuven, Belgium Department of Cardiology, University Hospitals Leuven, Leuven, Belgium.
KU Leuven · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDrug safety precautions recommend monitoring of the corrected QT interval. To determine which QT correction formula to use in an automated QT-monitoring algorithm in our electronic medical record, we studied rate correction performance of different QT correction formulae and their impact on risk assessment for mortality. METHODS AND

resultsAll electrocardiograms (ECGs) in patients >18 years with sinus rhythm, normal QRS duration and rate <90 beats per minute (bpm) in the University Hospitals of Leuven (Leuven, Belgium) during a 2-month period were included. QT correction was performed with Bazett, Fridericia, Framingham, Hodges, and Rautaharju formulae. In total, 6609 patients were included (age, 59.8±16.2 years; 53.6% male and heart rate 68.8±10.6 bpm). Optimal rate correction was observed using Fridericia and Framingham; Bazett performed worst. A healthy subset showed 99% upper limits of normal for Bazett above current clinical standards: men 472 ms (95% CI, 464-478 ms) and women 482 ms (95% CI 474-490 ms). Multivariate Cox regression, including age, heart rate, and prolonged QTc, identified Framingham (hazard ratio [HR], 7.31; 95% CI, 4.10-13.05) and Fridericia (HR, 5.95; 95% CI, 3.34-10.60) as significantly better predictors of 30-day all-cause mortality than Bazett (HR, 4.49; 95% CI, 2.31-8.74). In a point-prevalence study with haloperidol, the number of patients classified to be at risk for possibly harmful QT prolongation could be reduced by 50% using optimal QT rate correction.

conclusionsFridericia and Framingham correction formulae showed the best rate correction and significantly improved prediction of 30-day and 1-year mortality. With current clinical standards, Bazett overestimated the number of patients with potential dangerous QTc prolongation, which could lead to unnecessary safety measurements as withholding the patient of first-choice medication.

Indexed as

Arrhythmias, CardiacDrug-Related Side Effects and Adverse ReactionsElectrocardiographyElectrophysiologic Techniques, CardiacFemaleHeart RateHumansLong QT SyndromeMaleMiddle AgedMonitoring, PhysiologicRisk AssessmentelectrocardiographymortalitypopulationQT interval electrocardiographyrisk factorsrisk prediction

Identifiers

PMID27317349
PMCPMC4937268
OpenAlexW2435493985

What OpenQuestion 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 OpenQuestion graph.