Evidence map›Paper›PMID 39350836›Full record

ArticleCureus2024

Evaluation of Antipsychotic-Induced Neuroleptic Malignant Syndrome Using a Self-Organizing Map.

Koumi Miyasaka, Sakiko Hirofuji, Mika Maezawa, Satoshi Nakao, Moe Yamashita, Nanaka Ichihara, Yuka Nokura, Hirofumi Tamaki, Kazuhiro Iguchi, Mitsuhiro Nakamura

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Koumi MiyasakaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu, JPN.
Sakiko HirofujiLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu, JPN.
Mika MaezawaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu, JPN.
Satoshi NakaoLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu, JPN.
Moe YamashitaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu, JPN.
Nanaka IchiharaLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu, JPN.
Yuka NokuraLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu, JPN.
Hirofumi TamakiLaboratory of Community Pharmacy, Gifu Pharmaceutical University, Gifu, JPN.
Kazuhiro IguchiLaboratory of Community Pharmacy, Gifu Pharmaceutical University, Gifu, JPN.
Mitsuhiro NakamuraLaboratory of Drug Informatics, Gifu Pharmaceutical University, Gifu, JPN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction In neuropsychiatric pharmacotherapy, neuroleptic malignant syndrome (NMS) is a potentially serious side effect of antipsychotics characterized primarily by fever, disorientation, extrapyramidal disorders, and autonomic nervous system imbalance, which can lead to death if left untreated. We visualized the NMS profile of antipsychotics using a self-organizing map (SOM). We combined it with decision tree analysis to discriminate between 31 antipsychotics in more detail than typical antipsychotic (TAP) and atypical antipsychotic (AAP) classifications. Method A total of 20 TAPs and 11 AAPs were analyzed. We analyzed NMS reports extracted from the Japanese Adverse Drug Event Report (JADER) database based on standardized Medical Dictionary for Regulatory Activities (MedDRA) queries (Standardized MedDRA Queries (SMQ) code: 20000044, including 68 preferred terms). The SOM was applied using the SOM package in R version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria). Results The Japanese Adverse Drug Event Report (JADER) database contained 887,704 reports published between April 2004 and March 2024. The numbers of cases of NMS (SMQ code: 20000044) reported for risperidone, aripiprazole, haloperidol, olanzapine, and quetiapine were 1691, 1294, 1132, 1056, and 986, respectively. After the antipsychotics were classified into six units using SOM, they were adapted for decision tree analysis. First, 31 antipsychotics branched off into groups with loss of consciousness, with one group (10 TAPs) consisting entirely of TAPs, and the other consisting of antipsychotics that were further separated into two groups with coma induced by TAPs and AAPs. Conclusion The results of this study provide a reference for healthcare providers when predicting the NMS characteristics induced by each drug in patients, thereby facilitating the effective treatment of schizophrenia.

Indexed as

antipsychotic side effectatypical antipsychoticjapanese adverse drug event report (jader) databaseneuroleptic malignant syndrome (nms)self-organizing maptypical antipsychotic

Identifiers

PMID39350836
PMCPMC11440105

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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.