Evidence map›Paper›PMID 27723808›Full record

ArticlePloS one2016

Time-to-Onset Analysis of Drug-Induced Long QT Syndrome Based on a Spontaneous Reporting System for Adverse Drug Events.

Sayaka Sasaoka, Toshinobu Matsui, Yuuki Hane, Junko Abe, Natsumi Ueda, Yumi Motooka, Haruna Hatahira, Akiho Fukuda, Misa Naganuma, Shiori Hasegawa and 2 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
5.2field-weighted citation impact, top 4% 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

24 citing papers in PubMed, 51 citations in OpenAlex.

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  12. Lethal Arrhythmia (Clinical medicine insights. Case reports · 2020
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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

12 authors at 2 institutions in 1 country.

Sayaka SasaokaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Gifu, Japan.
Toshinobu MatsuiLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Gifu, Japan.
Yuuki HaneLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Gifu, Japan.
Junko AbeLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Gifu, Japan.
Natsumi UedaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Gifu, Japan.
Yumi MotookaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Gifu, Japan.
Haruna HatahiraLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Gifu, Japan.
Akiho FukudaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Gifu, Japan.
Misa NaganumaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Gifu, Japan.
Shiori HasegawaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Gifu, Japan.
Yasutomi KinosadaUnited Graduate School of Drug Discovery and Medical Information Sciences, Gifu University, Gifu-shi, Gifu, Japan.
Mitsuhiro NakamuraLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu-shi, Gifu, Japan.ORCID http://orcid.org/0000-0002-5062-5522
Gifu Pharmaceutical University · JPGifu University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long QT syndrome (LQTS) is a disorder of the heart's electrical activity that infrequently causes severe ventricular arrhythmias such as a type of ventricular tachycardia called torsade de pointes (TdP) and ventricular fibrillation, which can be fatal. There have been no previous reports on the time-to-onset for LQTS based on data from spontaneous reporting systems. The aim of this study was to assess the time-to-onset of LQTS according to drug treatment. We analyzed the association between 113 drugs in 37 therapeutic categories and LQTS including TdP using data obtained from the Japanese Adverse Drug Event Report database. For signal detection, we used the reporting odds ratio (ROR). Furthermore, we analyzed the time-to-onset data and assessed the hazard type using the Weibull shape parameter. The RORs (95% confidence interval) for bepridil, amiodarone, pilsicainide, nilotinib, disopyramide, arsenic trioxide, clarithromycin, cibenzoline, donepezil, famotidine, sulpiride, and nifekalant were 174.4 (148.6-204.6), 17.3 (14.7-20.4), 52.0 (43.4-62.4), 13.9 (11.5-16.7), 69.3 (55.3-86.8), 54.2 (43.2-68.0), 4.7 (3.8-5.8), 19.9 (15.9-25.0), 8.1 (6.5-10.1), 3.2 (2.5-4.1), 7.1 (5.5-9.2), and 254.8 (168.5-385.4), respectively. The medians and quartiles of time-to-onset for aprindine (oral) and bepridil were 20.0 (11.0-35.8) and 18.0 (6.0-43.0) days, respectively. The lower 95% confidence interval of the shape parameter β of bepridil was over 1 and the hazard was considered to increase over time.Our study indicated that the pattern of LQTS onset might differ among drugs. Based on these results, careful long-term observation is recommended, especially for specific drugs such as bepridil and aprindine. This information may be useful for the prevention of sudden death following LQTS and for efficient therapeutic planning.

Indexed as

Databases, FactualLong QT SyndromeAdministration, OralAprindineBepridilFemaleHumansMaleTime FactorsAprindineBepridil

Identifiers

PMID27723808
PMCPMC5056697
OpenAlexW2530978218

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.