Eosinophil count testing in patients with asthma varies by healthcare provider type in the US: a retrospective study
Bibliographic record
Abstract
BACKGROUND: Patients with asthma with an eosinophilic phenotype may be eligible for additional treatment options to improve disease control; however, the prevalence and frequency of eosinophil testing is unknown. This study assessed blood eosinophil count testing prevalence in patients with asthma by exacerbation frequency and healthcare provider (HCP) type. METHODS: Universe electronic health records database. Eligible patients had ≥ 2 asthma diagnostic codes (January 2016-December 2018) (Index date: first asthma diagnosis). Outcomes included patient demographics and clinical characteristics (12 months pre-index [baseline]), and prevalence of blood eosinophil count testing, stratified by exacerbation frequency (infrequent exacerbations [< 2]) or frequent exacerbations [≥ 2] or primary HCP (Allergist/Pulmonologist, a primary care physician [PCP] or other HCP) during the 12 months post-index (follow-up). RESULTS: Of 400,254 patients included (mean age: 51.2 years; 70.8% female), the most common provider type at baseline was a PCP (76.8%). A higher proportion of patients with frequent exacerbations had blood eosinophil count tests at baseline (55.4-69.5%) and follow-up (67.9-75.1%), compared with patients with infrequent exacerbations (55.5-63.7%, 62.4-67.3%). Significantly more patients in the Allergist/Pulmonologist subgroup had ≥ 1 blood eosinophil count test result compared with patients in the PCP subgroup at both baseline (59.9% vs. 50.7%; p < 0.001) and follow-up (59.0% vs. 56.2%; p < 0.001). In the total population, the mean (SD) number of tests ordered was 3.4 (5.3) and 4.1 (6.4) during the baseline and follow-up periods, respectively. A greater mean number of tests were ordered for patients with frequent exacerbations, most apparently in the Allergist/Pulmonologist subgroup during baseline and follow-up (7.4 vs. 4.9). For patients with frequent exacerbations and blood eosinophil count test results, the mean (SD) number of tests ranged from 3.1 (4.6) to 5.8 (8.3) at baseline and 5.1 (8.5) to 7.4 (10.6) during follow-up. CONCLUSIONS: The prevalence of blood eosinophil count testing in patients with asthma remains suboptimal. Routine blood eosinophil count testing should be considered by HCPs for patients with asthma to increase identification of the eosinophilic asthma phenotype, which may inform the decision to advance to targeted biologic therapy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".