Association Between Cold Exposure and Asthma: Systematic Review and meta-analysis, 1965-2015
Bibliographic record
Abstract
Objetivos: Realizar una revisión sistemática y meta-análisis de estudios observacionales y experimentales que exploren la relación entre asma y exposición al fríoMateriales y Métodos: Revisión sistemática de estudios experimentales y observacionales publicados hasta agosto de 2015 en Pubmed, Embase y Lilacs. Dos investigadores seleccionaron estudios midiendo la ocurrencia de asma tras la exposición a diferentes temperaturas ambientales. Usando un modelo de efectos aleatorios en RevMan 5.3, un meta-análisis calculó un resumen de Odds Ratio ponderado con intervalos de confianza de 95%. Un análisis de sensibilidad identificó la influencia de cada estudio. Análisis de subgrupo identificaron las medidas de resumen de acuerdo a tipo de exposición al frío y diseño de estudio. Finalmente, medimos heterogeneidad y riesgo de sesgos.Resultados: Encontramos 86 estudios explorando la relación entre la exposición al frío y el asma. Incluimos 11.6% (10/86) de los estudios en el meta-análisis y encontramos una asociación entre la exposición al frío y asma en todos los estudios (ORw 2.0 95%CI 1.28-3.14), en el subgrupo de estudios experimentales (ORw 3.8 IC95% 1.70-8.86), y aire frío ambiental (ORw 1.59 IC95% 1.10-2.30). Los estudios tienen alto riesgo de sesgos y heterogeneidad I2: 63.1% (27%-81.4%).Conclusiones: Los resultados apoyan la hipótesis de una asociación entre asma y exposición al frío. Este estudio invita a explorar los conceptos de la medicina tradicional para la prevención y cuidado de enfermedades respiratorias.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.030 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".