Evidence map›Paper›PMID 29417762›Full record

ArticlePharmacology research & perspectives2018

Improving the assessment of adverse drug reactions using the Naranjo Algorithm in daily practice: The Japan Adverse Drug Events Study.

Hiroki Murayama, Mio Sakuma, Yuri Takahashi, Takeshi Morimoto

Abstract readEvaluation Study
In one paragraph

Article in Pharmacology research & perspectives, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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.

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3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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  9. The evaluation of adverse drug reactions in Saudi Arabia: A retrospective observational study.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2022
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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

4 authors.

Hiroki MurayamaDepartment of Clinical Epidemiology, Hyogo College of Medicine, Nishinomiya, Japan.
Mio SakumaDepartment of Clinical Epidemiology, Hyogo College of Medicine, Nishinomiya, Japan.
Yuri TakahashiDepartment of Clinical Epidemiology, Hyogo College of Medicine, Nishinomiya, Japan.
Takeshi MorimotoDepartment of Clinical Epidemiology, Hyogo College of Medicine, Nishinomiya, Japan.ORCID 0000-0002-6844-739X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is difficult to determine adverse drug reactions (ADRs) in daily complicated clinical practice in which many kinds of drugs are prescribed. We evaluated how well the Naranjo Algorithm (NA) categorized ADRs among suspected ADRs. The Japan Adverse Drug Events (JADE) study was a prospective cohort study of 3459 inpatients. After all suspected ADRs were reported from research assistants, a single physician reviewer independently assigned an NA score to each. After all NA score of suspected ADRs were scored, two physician reviewers discussed and determined ADRs based on the literature. We investigated the sensitivity and specificity of NA and each component to categorize ADRs among suspected ADRs. A total of 1579 suspected ADRs were reported in 962 patients. Physician reviewers determined 997 ADRs. The percentage of ADRs was 94% if the total NA score reached 5. The modified NA consisted of 5 components that showed high classification abilities; its area under the curve (AUC) was 0.92 for categorizing ADRs, the same as the original. When we set the total NA score cut-off value to 5, specificity was 0.95 and sensitivity was 0.59. When we reclassified NA components as binary variables, the specificity increased to 0.98 with a cut-off value of 4 and yielded an AUC of 0.93. In conclusion, we showed that both NA and modified NA could categorize ADRs among suspected ADRs with a high likelihood in daily clinical practice.

Indexed as

AlgorithmsAdverse Drug Reaction Reporting SystemsAgedAged, 80 and overDrug-Related Side Effects and Adverse ReactionsFemaleHospitalizationHumansIncidenceJapanMaleMiddle AgedPrescription DrugsProspective StudiesSensitivity and SpecificityPrescription Drugsadverse drug reactionscategorizationdaily practiceJADE studymodificationNaranjo Algorithmpatient safetypharmacovigilancesensitivityspecificity

Identifiers

PMID29417762
PMCPMC5817823

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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.