Day-time variation of serum periostin in asthmatic adults treated with ICS/LABA and adults without asthma
Bibliographic record
Abstract
Abstract Background We aimed to determine the effect of sampling time during the day on serum periostin levels in adult participants with and without asthma. Methods Serum periostin was measured at 2-h intervals from 0800 to 1800 h in 16 adult participants with stable asthma prescribed inhaled corticosteroid and long-acting beta-agonist therapy, and in 16 otherwise healthy participants without asthma. Mixed linear models were used to compare time zero (08:00 h) with subsequent measurement time for serum periostin for both groups. Results In both asthma and non-asthma, the mean (SD) serum periostin levels continuously reduced during the day from 53.5 (13.6) ng/mL at 0800 h to 50.9 (13.4) ng/mL at 1800 h (difference log periostin −0.05, P ≤ 0.001) and 50.5 (13.0) ng/mL at 0800 h to 46.2 (11.5) ng/mL at 1800 h (difference log periostin −0.08, P ≤ 0.001) respectively. Conclusions Periostin values are higher in the morning compared with the afternoon in asthmatic and non-asthmatic adults. The small magnitude of the variation in serum periostin levels suggests that the time of day in which the serum periostin measurements are made is unlikely to influence treatment decisions if a specific serum periostin level is used to predict treatment responsiveness. Trial registration Australia New Zealand Trials Registry (ACTRN12614000072617)
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".