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Record W2120094825 · doi:10.2478/v10001-009-0006-7

Ambient sulphur dioxide exposure and emergency department visits for migraine in Vancouver, Canada

2009· article· en· W2120094825 on OpenAlexafffundabout
Mieczysław Szyszkowicz, Brian H. Rowe, Gilaad G. Kaplan

Bibliographic record

VenueInternational Journal of Occupational Medicine and Environmental Health · 2009
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsHealth Canada
FundersHealth CanadaCanada Research Chairs
KeywordsMigraineInterquartile rangeEmergency departmentMedicineHeadachesAir pollutionAir pollutantsNames of the days of the weekRelative humidityPediatricsAnesthesiaInternal medicineMeteorologySurgeryGeographyChemistry

Abstract

fetched live from OpenAlex

OBJECTIVES: Ambient exposure to sulphur dioxide (SO2) has been previously associated with emergency department (ED) visits for migraine headaches. In the present study, the objective was to examine the relationship between ED visits for migraine and ambient sulphur dioxide concentrations. DESIGN AND METHODS: This was a time-series study of 1059 ED visits for migraine (ICD-9: 346) recorded at a Vancouver hospital between 1999 and 2003 (1 520 days). Air pollution levels of SO2 were measured by fixed-site monitoring stations. The generalized linear mixed models technique was applied to regress daily counts of ED visits for migraine on the levels of the pollutant after adjusting for meteorological conditions: temperature and relative humidity. The analysis was stratified by season and gender. RESULTS: Positive and statistically significant correlations were observed for SO2 exposure and ED visits for migraine for females during colder months (October-March). The percentage increase in daily visits was 16.8% (95% CI: 1.2-34.8) for a 4-day average (of daily mean concentrations) SO2 level, for an interquartile range (IQR) increase of 1.9 ppb. CONCLUSIONS: Our findings provide additional support for a consistent correlation between migraine headache and air pollution (SO2).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.951

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 communication0.0000.000
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 head0.025
GPT teacher head0.335
Teacher spread0.311 · 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

Citations34
Published2009
Admission routes3
Has abstractyes

Explore more

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