Potential Severe Asthma Hidden in UK Primary Care
Bibliographic record
Abstract
Background Severe asthma may be underrecognized in primary care. Objective Identify and quantify patients with potential severe asthma (PSA) in UK primary care, the proportion not referred, and compare primary care patients with PSA with patients with confirmed severe asthma from UK tertiary care. Methods This was a historical cohort study including patients from the Optimum Patient Care Research Database (aged ≥16 years, active asthma diagnosis pre-2014) and UK patients in the International Severe Asthma Registry (UK-ISAR aged ≥18 years, confirmed severe asthma in tertiary care). In the OPCRD, PSA was defined as Global INitiative for Asthma 2018 step 4 treatment and 2 or more exacerbations/y or at Global INitiative for Asthma step 5. The proportion of these patients and their referral status in the last year were quantified. Demographic and clinical characteristics of groups were compared. Results Of 207,557 Optimum Patient Care Research Database patients with asthma, 16,409 (8%) had PSA. Of these, 72% had no referral/specialist review in the past year. Referred patients with PSA tended to have greater prevalence of inhaled corticosteroid/long-acting β 2 -agonist add-ons (54.1 vs 39.8%), and experienced significantly ( P < .001) more exacerbations per year (median, 3 vs 2/y), worse asthma control, and worse lung function (% predicted postbronchodilator FEV 1 /forced vital capacity, 0.69 vs 0.72) versus nonreferred patients. Confirmed patients with severe asthma (ie, UK patients in the International Severe Asthma Registry) were younger (51 vs 65 years; P < .001), and significantly ( P < .001) more likely to have uncontrolled asthma (91.4% vs 62.5%), a higher exacerbation rate (4/y [initial assessment] vs 3/y), use inhaled corticosteroid/long-acting β 2 -agonist add-ons (67.7% vs 54.1%), and have nasal polyposis (24.2% vs 6.8) than referred patients with PSA. Conclusions Large numbers of patients with PSA in the United Kingdom are underrecognized in primary care. These patients would benefit from a more systematic assessment in primary care and possible specialist referral.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".