An <i>In Vitro</i> Examination of the Effects of Altitude on Dry Powder Inhaler Performance
Bibliographic record
Abstract
BACKGROUND: The effects of altitude on dry powder inhaler (DPI) performance remain understudied. As existing standardized testing methodologies do not consider altitude, inhalation devices may be used in environments in which their performance has not been sufficiently characterized. METHODS: Six DPIs spanning a range of device resistances were examined in vitro in an environmental chamber mimicking a high-altitude environment equivalent to an altitude of 4200 m, with controls established at an altitude of 700 m. Deposition and size distribution data were quantified by using an Alberta Idealized Throat coupled to a Next-Generation Impactor, operated by using a square inhalation profile. Controls were established for two cases, one with a standard pressure drop and the other with a minimal efficacious flowrate. Experiments at simulated altitude were performed first by using a matched volumetric flowrate and second with a matched pressure drop, corresponding to values obtained in the controls. In vitro results were input into a lung deposition model to examine the relationship between particle-size distributions, inhalation flowrates, and regional deposition in the respiratory tract. RESULTS AND CONCLUSIONS: Simulated altitude caused statistically significant effects in some DPIs, but effects were variable, device dependent, and relatively minor. Medium-high resistance devices were more affected by the flowrate used to establish the control than by any effects of altitude. Patients able to generate sufficient inspiratory efforts can expect relatively consistent device performance at altitudes up to 4200 m for the devices examined here.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".