National asthma observational survey of severe asthmatics in Israel: the no-air study
Bibliographic record
Abstract
BACKGROUND: Asthma is considered a global public health issue requiring a significant medical expenditure as a result of its high prevalence and the low rate of disease control. OBJECTIVE: This is the first nationwide survey of severe asthma patients carried out in Israel. In this study we aimed to assess health resources utilization, compliance with treatment and disease-control in a subgroup of patients with severe asthma in Israel. MATERIAL AND METHOD: One hundred and twenty-three patients with a diagnosis of asthma for more then one year, as well as a hospitalization during the last 12 months due to asthma exacerbation or maintenance systemic steroids therapy, were included in this non-interventional observational study. RESULTS: Asthma was uncontrolled in 43.9%, partly controlled in 50.4% and well controlled in only 5.7%. The majority of the patients (83%) were compliant with drug treatment. CONCLUSION: The fact that 83% of the asthma patients included in this study were compliant with their asthma therapy was not manifested in asthma control. Therefore concrete tools are required for achieving and maintaining asthma control, especially in the treatment of the most severe asthmatic patients.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".