Improving the Efficiency of Respiratory Drug Delivery: A Review of Current Treatment Trends and Future Strategies for Asthma and Chronic Obstructive Pulmonary Disease
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
Asthma and chronic obstructive pulmonary disease (COPD) are heterogeneous airway diseases associated with significant morbidity and mortality. Pharmacological treatment is delivered primarily through the inhalation route using various devices. Optimal disease control is highly dependent upon patient adherence. Both patients with asthma and COPD are prone to exacerbations leading to hospitalization, which can significantly impact quality of life. Poor adherence is a complex and multifactorial problem that does not have one simple solution. However, it is the biggest risk factor for exacerbations and consequently high healthcare utilization. This review discusses the complex and multifactorial obstacles that impact patient adherence as well as the effect on overall treatment outcomes and healthcare utilization. We also critically examined and compared relatively recent improvements in breath-activated pressurized metered dose inhalers, dry powder inhalers, and e-technology in asthma and COPD. Finally, future treatment strategies for better patient compliance such as personalized medicine and the importance of decision-making between patients and physicians were highlighted.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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