Association between asthma hospital admission and weather temperature in St. John's, Newfoundland and Labrador, Canada
Notice bibliographique
Résumé
While temperature changes are associated with increased ER visit and hospitalization for asthma, geography and climate are important moderating factors of this association. To our knowledge, no study has assessed the temperature-asthma hospitalization link in Newfoundland and Labrador (NL). St. John’s weather is governed by a marine climate, with vast temperature variations and high winds. We conducted four studies to investigate the association between temperature and asthma hospitalizations among adult asthma patients in St. John’s, NL. Study 1 was a systematic review of the effects of meteorological variables on asthma hospitalization and emergency department (ED) visits in adults. There were 3877 articles identified on initial search. After removing duplicates and irrelevant studies, 19 studies were included. A significant association between temperature and hospitalization among patients with asthma was reported in six studies (31%). In addition, nearly 37% of the studies found that both temperature and relative humidity were associated with asthma hospital admission. Our review suggests that temperature variation can have both a positive (6 studies) or negative correlation (2 studies) with number of asthma related hospital admissions, depending on the season and geographic area. The temperature measurement and the threshold for temperature varied from one study to another. Study 2, a time series analysis to examined the daily minimum temperature threshold and its delayed effect on number of daily hospital admission among adult asthma patients. The results of distributed lag non-linear model (DLNM) analyses show the risk of hospitalizations among adult asthma patients increased when the minimum temperature declined below -4°C (RR=1.10; 95% CI: 1.01-1.16) and/or exceeded 14°C (RR= 1.03; 95% CI: 1.01-1.18) on the same day and/or the day after these ranges. Study 3 was a nested case-control study to assess the effects of extreme temperature on epidemics of hospitalization among adults with asthma. I identified number of hospital admission per day. Cases defined as epidemic days. Epidemic days introduced as days where the observed number of hospital admissions exceeded four standard deviation from the average frequency of distribution daily counts of hospital admissions, and the controls as days within one standard deviation from the average daily hospital admissions. Multivariate logistic regressions showed an epidemic of hospital admission is happening when Daily Minimum Temperature (DMT) exceeds 14.0C (OR= 1.79; 95% CI: 1.08- 1.86) and declines below -4.0°C (OR= 5.81; 95% CI: 1.12-7.61) within the same day and/or the following day. Then, to control for individual risk factors, we performed a case-crossover study (Study 4) where study subjects were selected from patients who were admitted to the hospital during epidemic days. These patients served as their own controls. The results show extreme warm (DMT > 14.°C) and cold temperatures (DMT < -4.°C) are associated with hospital admission among patients with asthma (OR= 1.33; 95% CI: 1.14-1.57 and OR= 1.12; 95% CI: 1.03- 1.23, respectively). These findings may provide a basis for health authorities to anticipate patient volumes and healthcare demands using weather forecasts to prepare resources and hospital infrastructure accordingly.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,004 |
| Bibliométrie | 0,006 | 0,012 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».