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Record W3193767351 · doi:10.1289/isee.2021.o-to-022

Long-term impacts of Atlantic hurricanes on asthma exacerbations among children with asthma in the eastern United States

2021· article· en· W3193767351 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueISEE Conference Abstracts · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAsthmaMedicineExacerbationAsthma exacerbationsStormDemographyPopulationEnvironmental healthPediatricsMeteorologyGeographyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND AIM: Tropical cyclones (TCs) are associated with substantial, acute increases in mortality and morbidity. Relatively few studies have examined the longer-term health consequences of such storms. We assessed whether TCs increased the frequency of symptom exacerbation among children with a diagnosis of asthma in the 12 months following storms in counties in the eastern United States (US), 2000-2018. METHODS: We defined exposure to TCs as maximum sustained windspeed at the county center 21 meters/second, and matched each exposed county to one or more unexposed counties on sociodemographic variables, climate, and distance from the coast. Within each exposed and matched unexposed county, we used data from the OptumLabs Data Warehouse, a longitudinal, real-world data asset with de-identified administrative claims and electronic health record (EHR) data, to estimate monthly rates of asthma exacerbations requiring medical attention among children aged 5-17 with a prior diagnosis of asthma. Finally, we used a difference-in-differences approach implemented via a log-linear fixed effects model with an offset for eligible population size to compare the rate of asthma exacerbations occurring in exposed versus unexposed counties, in the 12 months before versus 12 months after each storm. RESULTS:Our analysis encompasses 43 TCs that affected at least one county during the study period. Overall, across these storms, we did not observe evidence of an increase in symptom exacerbation in the 12 months following the storm (random effects meta-analytic summary estimate: RR: 1.03 [95% CI: 0.96, 1.10], I2 = 19%). However, we did find evidence of an increase in symptom exacerbation following specific storms, such as Hurricane Sandy. CONCLUSIONS:These findings suggest that some TCs may be detrimental to the respiratory health of children, but that tropical cyclones are not in aggregate substantially associated with long-term exacerbation of asthma among a population of children with health insurance. KEYWORDS: Climate change, Tropical cyclones, Asthma

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.283
Teacher spread0.262 · 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