How a Novel Portable Spacer Benefits Patients with Respiratory Disease, the Healthcare System, and the Environment
Bibliographic record
Abstract
Spacers or valved holding chambers added to pressurised metered dose inhalers (pMDI) reduce errors in inhaler technique and improve delivery of fine dose particles to patients with obstructive airway diseases. However, despite the established benefits of spacers, patients frequently do not use them beyond the home setting due to inconvenience regarding their relatively large size and appearance. Notably, not using the spacer (i.e., nonadherence) could have negative consequences for more than just the patients themselves. Alan Kaplan, Physician and Chairperson of the Family Physician Airways Group of Canada, Markham, Ontario, Canada; and Job F.M. Van Boven, Associate Professor of Cost-Effective & Sustainable Respiratory Drug Use, University Medical Center Groningen, the Netherlands, explored the intricate relationships between adherence to prescribed treatments with spacers, symptom control and management, the carbon footprint, and economic burden on the healthcare system. They also introduced a novel, portable spacer that was designed to be used while on the go. Specifically, they discussed the performance of the portable spacer compared to the gold standard traditional spacer, pMDIs alone, and dry powder inhalers (DPI). Finally, summarising patient feedback and adherence data about the new portable spacer.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".