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Record W6910401660 · doi:10.48350/151066

Extreme heat and paediatric emergency department visits in Southwestern Ontario.

2020· article· en· W6910401660 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Access CRIS of the University of Bern · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsEmergency departmentExtreme heatExtreme weatherPercentileIncidence (geometry)Names of the days of the weekRelative riskPublic health

Abstract

fetched live from OpenAlex

Objective The risk of adverse health events is expected to increase with hotter temperatures, particularly among the most vulnerable groups such as elderly persons and children. The objective of this study was to assess the association between extreme heat and daily emergency department visits among children (0 to 17 years) in Southwestern Ontario. Methods We examined the average maximum temperature, relative humidity, and daily paediatric emergency department visits in June through August of 2002 to 2019. We reviewed emergency department visits from two academic hospitals. Daily meteorological data from the local weather station were obtained from Environment and Climate Change Canada. Results Extreme heat, defined as the 99th percentile of the maximum temperature distribution, occurred at 33.1°C and was associated with an overall 22% increase in emergency department visits, compared to the reference temperature of 21°C. This association was mostly found between the second and fifth day after the exposure, suggesting a slightly delayed effect. The results of the sub-group analysis indicate that the risk of an emergency department visit due to infectious disease increases by 35% and the most pronounced association was noted in children aged 1 to 12 years. Conclusions Extreme heat is associated with an increased incidence of emergency department visits in children. As temperatures continue to increase, strategies to mitigate heat-related health risks among children should be developed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.102
GPT teacher head0.305
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

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