Evidence map›Paper›PMID 39264491›Full record

ArticleInternational journal of clinical pharmacy2024

The usage of anticholinergic medications in a low- and middle-income country: a longitudinal comparison of 2013-15 and 2020-22 datasets.

Xiang Jiang Xu, Phyo Kyaw Myint, Shaun Wen Huey Lee, Kalavathy Ramasamy, Siong Meng Lim, Abu Bakar Abdul Majeed, Yuet Yen Wong, Sumaiyah Mat, Nor Izzati Saedon, Hazlina Mahadzir and 2 more

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in International journal of clinical pharmacy, 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

12 authors.

Xiang Jiang XuAgeing and Age-Associated Disorders Research Group, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia.
Phyo Kyaw MyintAgeing Clinical & Experimental Research (ACER) Group, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK.
Shaun Wen Huey LeeSchool of Pharmacy, Monash University Malaysia, Bandar Sunway, Selangor, Malaysia.
Kalavathy RamasamyFaculty of Pharmacy, Universiti Teknologi MARA(UiTM) Cawangan Selangor, Kampus Puncak Alam, 42300, Bandar Puncak Alam, Selangor Darul Ehsan, Malaysia.
Siong Meng LimFaculty of Pharmacy, Universiti Teknologi MARA(UiTM) Cawangan Selangor, Kampus Puncak Alam, 42300, Bandar Puncak Alam, Selangor Darul Ehsan, Malaysia.
Abu Bakar Abdul MajeedFaculty of Pharmacy, Universiti Teknologi MARA(UiTM) Cawangan Selangor, Kampus Puncak Alam, 42300, Bandar Puncak Alam, Selangor Darul Ehsan, Malaysia.
Yuet Yen WongFaculty of Pharmacy, Universiti Teknologi MARA (UiTM) Cawangan Pulau Pinang, Bertam Campus,, Permatang Pauh, Pulau Pinang, Malaysia.
Sumaiyah MatPhysiotherapy Programme, Faculty of Health Sciences, Center for Healthy Ageing and Wellness, Universiti Kebangsaan Malaysia, Bangi, Malaysia.
Nor Izzati SaedonAgeing and Age-Associated Disorders Research Group, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia.
Hazlina MahadzirGeriatric Unit, Department of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia.
Kejal HasmukharayDivison of Geriatric Medicine, Department of Medicine, University of Malaya Medical Center, Kuala Lumpur, Malaysia.
Maw Pin TanAgeing and Age-Associated Disorders Research Group, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia. mptan@ummc.edu.my.ORCID http://orcid.org/0000-0002-3400-8540

Funding

the Ministry of Higher Education Malaysia LRGS/1/2019/UM/01/1/3
6 · The paper itself

Abstract

backgroundWhile the effects of anticholinergic drug use have been increasingly highlighted, trends in anticholinergic use remain poorly understood.

aimTo determine the changes in frequency and pattern of anticholinergic drug use within a low- and middle-income country.

methodComparisons were made between population-based datasets collected from Malaysian residents aged 55 years and older in 2013-15 and 2020-22. Anticholinergic exposure was determined using the anticholinergic cognitive burden (ACB) tool. Drugs with ACB were categorised according to the Anatomical Therapeutic Chemical (ATC) classification.

resultsA total number of 5707 medications were recorded from the 1616 participants included in the 2013-15 dataset. A total number of 6175 medications were recorded from 2733 participants in 2020-22. Two hundred and ninety-three (18.1%) and 280 (10.2%) participants consumed

conclusionAlthough anticholinergic exposure has decreased over time, the use of medications with anticholinergic effects in the nervous system class has risen. This increase is attributable to antipsychotic use, which is of concern due to potential cardiovascular complications, and deserves further evaluation.

Indexed as

Cholinergic AntagonistsAgedAged, 80 and overDeveloping CountriesDrug UtilizationFemaleHumansLongitudinal StudiesMalaysiaMaleMiddle AgedCholinergic AntagonistsAnticholinergicsChangesComparisonLow- and Middle-income countryPatternPrescribingPrevalence

Identifiers

PMID39264491

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.