Evidence map›Paper›PMID 36249944›Full record

ArticleSaudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society2022

Hospital admission profile related to poisoning by, adverse effect of and underdosing of psychotropic drugs in England and Wales: An ecological study.

Tamara Al-Daghastani, Abdallah Y Naser

Abstract read
In one paragraph

Article in Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Tamara Al-DaghastaniDepartment of Medical Allied Sciences, Al-Balqa Applied University, Al-Salt, Jordan.
Abdallah Y NaserDepartment of Applied Pharmaceutical Sciences and Clinical Pharmacy, Faculty of Pharmacy, Isra University, Amman, Jordan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Drug poisoning is considered as one of the main principal reasons for acute care hospitals admissions, and it places a significant burden on emergency medical services resources. The aim of this study is to examine the trend of hospital admission due to poisoning by psychotropic drugs and prescriptions of psychotropic medications in England and Wales in the past 21 years. Method: Hospital admission data from the Hospital Episode Statistics database in England and the Patient Episode Database in Wales were used in this ecological study. For the period from April 1999 to March 2020, hospital admissions data relating to poisoning by, classified by adverse effects of, and underdosing of psychiatric medications were extracted. Data on CNS drug prescriptions was collected for the time period 2004-2020. Results: During the study period, hospital admission rate increased by19.9% [from 39.94 (95% CI 39.40-40.48) in 1999 to 47.90 (95% CI 47.34-48.45) in 2020 per 100,000 persons, trend test, p < 0.05]. The most common reason of poisoning by psychotropic drugs that lead to hospital admissions was unspecified poisoning by antidepressants (accidental (unintentional), intentional self-harm, assault, as adverse effect, and under-dosing), which accounted for 48.9% of the total number of admissions. CNS medications prescription rates increased by 56.4% [from 247629.78 (95% CI 247593.18-247666.39) in 2004 to 387372.48 (95% CI 387333.41-387411.55) in 2020 prescriptions per 100,000 persons, trend test, p < 0.001]. The most commonly prescribed CNS medications prescriptions were analgesics, antidepressant, antiepileptic, and hypnotics and anxiolytics, which accounted for: 35.0%, 28.7%, 10.0%, and 9.5%, respectively. During the study.period between 2004 and 2020, the overall medications prescribing rate showed to be very strongly and positively correlating the hospital admissions rate with the overall poisoning by psychotropic drugs (r = 0.799; p ≤ 0.001). Conclusion: Over the last two decades, there has been a parallel increase in the hospitalization rate for psychotropic drug poisoning and the prescription rate for CNS medications. Future research should focus on identifying high-risk populations who are more prone to psychotropic drug poisoning.

Indexed as

AdmissionAdverse effectEnglandHospitalisationPoisoningPsychotropicWales

Identifiers

PMID36249944
PMCPMC9561178

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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.