Additive prognostic value of blood eosinophils and exhaled nitric oxide (FeNO) to predict asthma attacks in the ORACLE patient-level meta-analysis
Bibliographic record
Abstract
Tionale: In asthma, type-2 biomarkers blood eosinophil cells (BEC) and exhaled nitric oxide (FeNO) identify a higher risk and anti-inflammatory responsive phenotype. Their combined prognostic value is unclear. Aim: To assess the independent and combined prognostic relationship of BEC and FeNO with severe asthma attacks Methods: We included 6,516 participants from control arms of 22 randomised controlled trials spanning mild to severe asthma (6-12 months follow-up, the OxfoRd Asthma attaCk risk scaLE (ORACLE) patient-level meta-analysis). Baseline predictors included BEC, FeNO, Asthma Control Questionnaire-5, FEV1%, and attack history in the past 12 m. Statistical interaction between BEC and FeNO was tested continuously and categorically. Results: The multivariable rate ratio [95% CI] for the interaction term log10(BEC)×log10(FeNO) was 1.39 [1.01-1.91], indicating that BEC and FeNO have additive prognostic value (Fig. 1A). The very type-2 inflammatory status (BEC ≥ 0.3×109/L & FeNO ≥ 50 ppb) was the most predictive modifiable risk factor across asthma severities (Fig. 1B). Conclusion: Type-2 biomarkers BEC and FeNO are independent and additive risk factors for asthma attacks. ORACLE shows potential for a prediction model centred on biomarkers to support clinical decision-making. Prospero: CRD42021245337; Funding: NIHR, QRHRN, FRQS, APQ, SAB, LUF erj;64/suppl_68/PA1205/F1 F1 F1
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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 | 0.018 | 0.027 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.057 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".