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Record W4389477068 · doi:10.29390/001c.90653

A cross-sectional survey on the effects of ambient temperature and humidity on health outcomes in individuals with chronic respiratory disease

2023· article· en· W4389477068 on OpenAlexaffvenueabout
Samantha Mekhuri, Shirley Quach, Caroline Barakat, Winnie Sun, Mika Nonoyama

Bibliographic record

VenueCanadian Journal of Respiratory Therapy · 2023
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMcMaster UniversitySickKids FoundationOntario Shores Centre for Mental Health SciencesHospital for Sick ChildrenOntario Tech University
Fundersnot available
KeywordsMedicineCOPDAsthmaCross-sectional studyDiseaseInternal medicinePathology

Abstract

fetched live from OpenAlex

Rationale Extremes of temperature and humidity are associated with adverse respiratory symptoms, reduced lung function, and increased exacerbations among individuals living with chronic obstructive pulmonary disease (COPD). Objectives To describe the reported effects of temperature and humidity extremes on the health outcomes, health status and physical activity (PA) in individuals living with COPD. Methods A cross-sectional self-reported survey collected the effects on health status (COPD Assessment Test [CAT]), PA, and health outcomes in 1) moderate/ideal (14 to 21°C, 30 to 50% relative humidity [RH]), 2) hot and humid (≥ 25°C, > 50% RH) and 3) cold and dry (≤ 5°C, < 30% RH) weather conditions. Participants were ≥ 40 years old with COPD or related chronic respiratory diseases (e.g., asthma, sleep apnea, interstitial lung disease, lung cancer) and residing in Canada for ≥ 1 year. Negative responders to weather extremes were a priori defined as having a change of ≥ 2 points in the CAT. Main Results Thirty-six participants responded; the mean age (SD) was 65 (11) years, and 23 (64%) were females. Compared to ideal conditions, 23 (66%) and 24 (69%) were negatively affected by cold/dry and hot/humid weather, respectively. Health status was significantly lower, and PA amount and difficulty level were reduced in hot/humid and cold/dry conditions compared with ideal conditions. The number of exacerbations in hot/humid was significantly higher compared to ideal conditions. Conclusions More participants were negatively affected by extremes of weather: health status worsened, PA decreased, and frequency of exacerbations was higher compared to ideal. Future prospective studies should directly and objectively investigate different combinations of extreme temperature and humidity levels on symptoms and PA to understand their long-term health outcomes.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.338
Teacher spread0.294 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations18
Published2023
Admission routes3
Has abstractyes

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