Evidence map›Paper›PMID 32703198›Full record

ArticleBMC medical informatics and decision making2020

Development and validation of a tool to assess the risk of QT drug-drug interactions in clinical practice.

Florine A Berger, Heleen van der Sijs, Matthijs L Becker, Teun van Gelder, Patricia M L A van den Bemt

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
3.4field-weighted citation impact, top 6% 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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.

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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

5 authors at 4 institutions in 1 country.

Florine A BergerDepartment of Hospital Pharmacy, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015, GD, Rotterdam, the Netherlands. f.berger@erasmusmc.nl.ORCID 0000-0003-2723-8919
Heleen van der SijsDepartment of Hospital Pharmacy, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015, GD, Rotterdam, the Netherlands.
Matthijs L BeckerPharmacy Foundation of Haarlem Hospitals, Haarlem, the Netherlands.
Teun van GelderDepartment of Hospital Pharmacy, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015, GD, Rotterdam, the Netherlands.
Patricia M L A van den BemtDepartment of Hospital Pharmacy, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015, GD, Rotterdam, the Netherlands.
Erasmus MC · NLLeiden University Medical Center · NLStichting Apotheek der Haarlemse Ziekenhuizen · NLUniversity Medical Center Groningen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe exact risk of developing QTc-prolongation when using a combination of QTc-prolonging drugs is still unknown, making it difficult to interpret these QT drug-drug interactions (QT-DDIs). A tool to identify high-risk patients is needed to support healthcare providers in handling automatically generated alerts in clinical practice. The main aim of this study was to develop and validate a tool to assess the risk of QT-DDIs in clinical practice.

methodsA model was developed based on risk factors associated with QTc-prolongation determined in a prospective study on QT-DDIs in a university medical center inthe Netherlands. The main outcome measure was QTc-prolongation defined as a QTc interval > 450 ms for males and > 470 ms for females. Risk points were assigned to risk factors based on their odds ratios. Additional risk factors were added based on a literature review. The ability of the model to predict QTc-prolongation was validated in an independent dataset obtained from a general teaching hospital against QTc-prolongation as measured by an ECG as the gold standard. Sensitivities, specificities, false omission rates, accuracy and Youden's index were calculated.

resultsThe model included age, gender, cardiac comorbidities, hypertension, diabetes mellitus, renal function, potassium levels, loop diuretics, and QTc-prolonging drugs as risk factors. Application of the model to the independent dataset resulted in an area under the ROC-curve of 0.54 (95% CI 0.51-0.56) when QTc-prolongation was defined as > 450/470 ms, and 0.59 (0.54-0.63) when QTc-prolongation was defined as > 500 ms. A cut-off value of 6 led to a sensitivity of 76.6 and 83.9% and a specificity of 28.5 and 27.5% respectively.

conclusionsA clinical decision support tool with fair performance characteristics was developed. Optimization of this tool may aid in assessing the risk associated with QT-DDIs.

trial registrationNo trial registration, MEC-2015-368.

Indexed as

Drug InteractionsPharmaceutical PreparationsAgedElectrocardiographyFemaleHumansMaleMiddle AgedNetherlandsProspective StudiesRisk FactorsPharmaceutical PreparationsDecision support systems, clinicalDrug interactionsRisk factorsROC curveSensitivity and specificity

Identifiers

PMID32703198
PMCPMC7376881
OpenAlexW3044624260

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.