1388Risk factors for chronic cough in adults: A systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Despite the challenges of diagnosing and managing adult patients with chronic cough, a systematic synthesis of evidence on aetiological risk factor is lacking. Methods We systematically searched PUBMED and EMBASE to synthesize the current evidence for longitudinal associations between various risk factors and chronic cough in the general adult population, following the meta-analysis of observation studies in epidemiology (MOOSE) guidelines. The Newcastle-Ottawa scale was used to assess the quality of the included studies. Fixed-effect meta-analysis was conducted where appropriate. Results Of 26 eligible articles, 16 domains of risk factors were assessed. There was consistent evidence that asthma (pooled adjusted OR (aOR) = 3.01; 95%CI: 2.33-3.70; I2=0%, number of articles (N)=3) and low education levels/socioeconomic status (SES) (pooled aOR=1.46; 95%CI: 1.20-1.72; I2=0%; N = 3) were associated with an increased risk of chronic cough after adjusting for smoking and other confounders. While continuous smoking was associated chronic cough (aOR =1.81; 95%CI: 1.36,2.26; I2=57%; N = 3), there was too little evidence to draw conclusions for occupational exposures, outdoor air pollution, early-life exposures, diet, snoring and other chronic conditions. Conclusions Asthma, persistent smoking and lower education/SES were associated with increased risk of chronic cough. Longitudinal associations between other factors frequently mentioned empirically need further investigation. Key messages Our systematic review found asthma, smoking and lower education to be associated with adult chronic cough. More longitudinal studies are needed to understand other potential risk factors for adult chronic cough.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.035 |
| Bibliometrics | 0.008 | 0.008 |
| 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) | 0.006 | 0.000 |
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.
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".