Suboptimal asthma control: prevalence, detection and consequences in general practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Telephone surveys describing suboptimal asthma control may be biased by low response rates. In order to obtain an unbiased assessment of asthma control and assess its impact in primary care, primary care physicians used a 1-page control questionnaire in 50 consecutive asthma patients. Of the 10,428 patients assessed by 354 physicians, 59% were uncontrolled, 19% well-controlled and 23% totally controlled. Physicians overestimated control, regarding only 42% of patients as uncontrolled. Physicians were more likely to report plans to alter the regimens of uncontrolled patients than controlled patients (1.29 versus 0.20 medication changes per patient) doing so in a fashion consistent with guideline recommendations. Of the uncontrolled patients, 59% required one or more urgent care or specialist visits versus 26 and 15% of well-controlled or totally controlled patients, respectively. Patients were more likely to report short-term symptom control when they had not required urgent or specialist care (odds ratio 5.68; 95% confidence interval 4.91-6.58). The majority of asthma patients treated in general practice are uncontrolled. Lack of control can be recognised by physicians who are likely to consider appropriate changes to therapy. A lack of short-term symptom control of asthma is associated with excess healthcare utilisation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it