Evidence map›Paper›PMID 34462002›Full record

ArticleBMC pharmacology & toxicology2021

Pharmacovigilance study of anti-infective-related acute kidney injury using the Japanese adverse drug event report database.

Satoshi Nakao, Shiori Hasegawa, Ryogo Umetsu, Kazuyo Shimada, Ririka Mukai, Mizuki Tanaka, Kiyoka Matsumoto, Yu Yoshida, Misaki Inoue, Riko Satake and 3 more

Abstract read
In one paragraph

Article in BMC pharmacology & toxicology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

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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

13 authors.

Satoshi NakaoLaboratory of Drug Informatics, Gifu Pharmaceutical University; Gifu, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan.
Shiori HasegawaLaboratory of Drug Informatics, Gifu Pharmaceutical University; Gifu, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan.
Ryogo UmetsuLaboratory of Drug Informatics, Gifu Pharmaceutical University; Gifu, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan.
Kazuyo ShimadaLaboratory of Drug Informatics, Gifu Pharmaceutical University; Gifu, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan.
Ririka MukaiLaboratory of Drug Informatics, Gifu Pharmaceutical University; Gifu, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan.
Mizuki TanakaLaboratory of Drug Informatics, Gifu Pharmaceutical University; Gifu, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan.
Kiyoka MatsumotoLaboratory of Drug Informatics, Gifu Pharmaceutical University; Gifu, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan.
Yu YoshidaLaboratory of Drug Informatics, Gifu Pharmaceutical University; Gifu, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan.
Misaki InoueLaboratory of Drug Informatics, Gifu Pharmaceutical University; Gifu, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan.
Riko SatakeLaboratory of Drug Informatics, Gifu Pharmaceutical University; Gifu, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan.
Yuri NishibataLaboratory of Drug Informatics, Gifu Pharmaceutical University; Gifu, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan.
Jun LiaoDepartment of Pharmaceutical Informatics and Biological Statistics, School of Science, China Pharmaceutical University, Nanjing, China.
Mitsuhiro NakamuraLaboratory of Drug Informatics, Gifu Pharmaceutical University; Gifu, 1-25-4, Daigaku-Nishi, Gifu, 501-1196, Japan. mnakamura@gifu-pu.ac.jp.ORCID 0000-0002-5062-5522

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute kidney injury (AKI) is associated with significant increases in short- and long-term morbidity and mortality. Drug-induced AKI is a major concern in the present healthcare system. Our spontaneous reporting system (SRS) analysis assessed links between AKI, along with patients' age, as healthcare-associated risks and administered anti-infectives. We also generated anti-infective-related AKI-onset profiles.

methodWe calculated reporting odds ratios (RORs) for reports of anti-infective-related AKI (per Medical Dictionary for Regulatory Activities) in the Japanese Adverse Drug Event Report database and evaluated the effect of anti-infective combination therapy. The background factors of cases with anti-infective monotherapy and combination therapy (≥ 2 anti-infectives) were matched using propensity score. We evaluated time-to-onset data and hazard types using the Weibull parameter.

resultsAmong 534,688 reports (submission period: April 2004-June 2018), there were 21,727 AKI events. The reported number of AKI associated with glycopeptide antibacterials, fluoroquinolones, third-generation cephalosporins, triazole derivatives, and carbapenems were 596, 494, 341, 315, and 313, respectively. Crude RORs of anti-infective-related AKI increased among older patients and were higher in anti-infective combination therapies [anti-infectives, ≥ 2; ROR, 1.94 (1.80-2.09)] than in monotherapies [ROR, 1.29 (1.22-1.36)]. After propensity score matching, the adjusted RORs of anti-infective monotherapy and combination therapy (≥ 2 anti-infectives) were 0.67 (0.58-0.77) and 1.49 (1.29-1.71), respectively. Moreover, 48.1% of AKI occurred within 5 days (median, 5.0 days) of anti-infective therapy initiation.

conclusionRORs derived from our new SRS analysis indicate potential AKI risks and number of administered anti-infectives.

Indexed as

Acute Kidney InjuryAdultAdverse Drug Reaction Reporting SystemsAgedAged, 80 and overAnti-Infective AgentsDrug Therapy, CombinationFemaleHumansJapanMaleMiddle AgedOdds RatioPharmacovigilanceYoung AdultAnti-Infective AgentsAcute kidney injuryAnti-infectiveJADERJapanese adverse drug event report databasePolypharmacyPropensity score

Identifiers

PMID34462002
PMCPMC8404262

What OpenQuestion holds

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Registered trials

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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.