Evidence map›Paper›PMID 40499277›Full record

ArticleEBioMedicine2025

Exploring the relationship between medications and heat-related community deaths during the 2021 heat dome: a hybrid approach using machine learning.

Jeremie Boudreault, Kathleen E McLean, Sarah B Henderson

Abstract read
In one paragraph

Article in EBioMedicine, 2025. 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.

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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. Review
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

3 authors.

Jeremie BoudreaultEnvironmental Health Services, British Columbia Centre for Disease Control, 655 West 12th Ave, Vancouver, BC, V5Z 4R4, Canada; Centre Eau Terre Environnement, Institut national de la recherche scientifique, 490 de la Couronne, Québec, QC, G1K 9A9, Canada. Electronic address: jeremie.boudreault@inrs.ca.
Kathleen E McLeanEnvironmental Health Services, British Columbia Centre for Disease Control, 655 West 12th Ave, Vancouver, BC, V5Z 4R4, Canada.
Sarah B HendersonEnvironmental Health Services, British Columbia Centre for Disease Control, 655 West 12th Ave, Vancouver, BC, V5Z 4R4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExtreme heat events (EHEs) are a growing threat to health worldwide. To date, only a limited number of studies have evaluated medications as risk or protective factors for mortality during EHEs.

methodsWe explored the relationship between dispensed pharmaceuticals and heat-related community deaths using linked administrative health data and both logistic regression (LR) and machine learning (ML) models. We conducted a case-control study during the 2021 EHE in British Columbia, Canada, including 504 community deaths from heat exposure as cases and 2520 similar controls who survived the EHE. We used medications dispensed 30, 60 and 90 days prior to death (or 30, 60 and 90 days before the end of the EHE for controls) as predictors, grouped by Anatomical Therapeutic Chemical (ATC) classification at level 2 for LR (28 classes) and level 4 for ML (270 subclasses). Models were adjusted for multiple covariates, including common chronic diseases.

findingsResults from LR showed increased odds of mortality associated with dispensations of antiepileptics, anti-Parkinson drugs, psycholeptics, diuretics, drugs for diabetes, beta blocking agents, analgesics, urologicals and drugs for treatment of bone diseases. We observed a protective association with dispensations of calcium channel blockers and ophthalmologicals. Results varied by sex, age, and other covariates. The ML model highlighted the most computationally important subclasses of medications within each of the ATC level 2 classes.

interpretationThis study leveraged both LR and ML to generate insights about medications and mortality during EHEs. The results add to the existing evidence on pharmaceutical risks during EHEs and provide new avenues for further research. They can be used to help develop more targeted messages to inform individuals whose medications put them at greater risk during EHEs.

fundingBC Centre for Disease Control and Ministère de l'Enseignement supérieur du Québec.

Indexed as

Extreme HeatMachine LearningAdultAgedAged, 80 and overBritish ColumbiaCase-Control StudiesFemaleHumansLogistic ModelsMaleMiddle AgedRisk FactorsClimate changeExtreme heatLight gradient boostingMachine learningMortalityPharmaceuticals

Identifiers

PMID40499277
PMCPMC12182803

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.