Bibliographic record
Abstract
Introduction and objectives Increasing nocturnal cough is an accepted marker of worsening asthma, often used as justification for the escalation of treatment in clinical practice. A diurnal variation in pathophysiology including airway resistance and inflammation peaking at 4:00 am is well documented and is thought to manifest as increased asthma symptoms in the early morning hours. However, the diurnal variation in cough frequency lacks objective data. In addition, whether differences in characteristics exist between asthmatic individuals with and without nocturnal cough is unknown. Methods We analysed the VitaloJAK 24 hour cough monitor data to compare cough frequency between mild to moderate asthmatic (n=92, median age of 23 years (21–27 IQR), 58% female) and healthy individuals (n=44, median age of 38 years (29–51 IQR), 68% female), and studied asthmatic patient characteristic differences using a range of logistic regression models. This data was obtained from 2 previous studies and analysed using GraphPad prism and SPSS statistical analysis software. Results Asthmatic patients coughed more than healthy controls over 24 hours (median cough frequency of 27 (12–67 IQR) compared to 3.5 (1–19.75 IQR) respectively, p<0.0001). We identified a diurnal variation in cough frequency but in anti-phase to that which has been previously suggested. Asthmatic individuals cough the least at 4:00 am during the 2:00–5:59 block. In this group, those with nocturnal cough (defined as those with at least 1 cough between retiring to bed and waking) also coughed significantly more during all other 4 hour blocks than those without nocturnal cough (see figure 1). The greatest increase in cough was observed at a time when participants are expected to be waking up (from 2:00–5:59 to 6:00–9:59, p=0.0006). Furthermore, we identified that nocturnal cough is associated with increased use of ICS, higher doses of ICS and poorer asthma control (according to the GINA classification system). Conclusions The central suppressive effect of sleep on cough until waking and/or a delay in cough presentation after the accepted pathophysiological changes at 4:00 am in asthmatic individuals may explain the cough patterns observed and requires further study. Perhaps clinicians should place more emphasis on cough frequency on waking.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".