A novel method to assess airway eosinophilia using sputum plugs
Bibliographic record
Abstract
Background: Sputum cytology utilising routine dithiothreitol (DTT) processing is a well-established method to assess airway eosinophilia. However, the multi-step nature of this protocol requires substantial resources, thereby limiting its broader clinical applicability. To address this, we evaluated formalin-fixed, paraffin-embedded (FFPE) sputum plugs as a simplified method for measuring airway eosinophilia. Methods: Excess sputum plugs from 113 patients with complex airway disease and 16 asthma patients on corticosteroid or monoclonal antibodies were fixed in 10% formalin and embedded in paraffin (Sputum-Minimising Processing, Maximising Clinical Outcomes (SSIMPLE) method). FFPE blocks were sectioned, stained with haematoxylin and eosin, and assessed by four blinded observers, who performed a differential cell count on 400 total nonsquamous cells. Eosinophil proportions were then compared between matched FFPE and DTT-processed sputum slides. Airway eosinophilia was defined as ≥2.2% sputum eosinophils in DTT-processed samples. Results: Of the 113 FFPE slides, 96% were adequate for cellular analysis, with 90% having matched DTT-processed sputum slides. The SSIMPLE method demonstrated excellent interobserver reproducibility (consistency: 0.975; agreement: 0.976). Eosinophil proportions obtained from SSIMPLE and DTT processing were significantly correlated (ρ=0.9, p<0.0001) and showed agreement (Bland-Altman, -0.38±9.51). A cut-off of 2.6% detected airway eosinophilia with high sensitivity (85.4%) and specificity (93.0%) using the SSIMPLE method, showing strong agreement with the routine DTT method, as indicated by an area under the curve of 0.957. Additionally, the method effectively assessed treatment responsiveness to monoclonal antibody therapy. Conclusion: The SSIMPLE method is a reliable, noninferior approach to DTT processing for detecting airway eosinophilia in complex airway diseases, with high reproducibility and strong concordance in monitoring treatment responsiveness.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".