Oral Abstracts
Bibliographic record
Abstract
Aim A population based study was undertaken in Delhi to evaluate the gender differences in the prevalence of bronchial asthma. Methods A standardized and validated questionnaire based on IUATLD asthma prevalence questionnaire was used for the study. A two stage stratified (urban/rural) sampling procedure was adopted where villages/urban localities in Delhi formed the first stage units and the households the second stage units. A house to house survey was done in a random manner by the field team and the adult members of over 15 years of age in the family were interviewed. The field supervisor made visits to 10% of the randomly selected households for verifications. The questionnaire was re-administered to randomly selected 500 respondents to calculate the kappa index of agreement. The diagnosis of asthma was based on the following criteria: wheezing or whistling sound from chest in the past 12 months, or chest tightness or breathlessness in the morning and having suffered from asthma or having an attack of asthma in the past 12 months, or using inhaled or oral bronchodilators. Computer programme using the software Epi info (version 6) and the SPSS (version 10.0) was used for analysis. Multiple logistic regression modeling was used to evaluate the gender differences. Results A total of 15642 individuals were studied. There were 7966 (50.9%) males and 7676 (49.1%) females. The prevalence of bronchial asthma in Delhi was 1.69%. The prevalence was 1.84% in females and 1.54% in males. The odd ratio for development of bronchial asthma in females was significantly higher compared to males (OR 1.604, 95% CI 1.087-2.366, p = 0.017). Conclusions The prevalence of bronchial asthma in Delhi is 1.69% and the odds for development of bronchial asthma in females were significantly higher compared to males in Delhi.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".