Bench Tests of Simple, Handy Ventilators for Pandemics: Performance, Autonomy, and Ergonomy
Bibliographic record
Abstract
BACKGROUND: It has been pointed out that in the wake of a virulent flu strain, patients with survivable illness will die from lack of resources unless more ventilators are made available. Numerous disaster-type ventilators are available, but few evaluations have been performed. OBJECTIVE: To compare simple, lightweight, and handy ventilators that could be used in the initial care of patients with respiratory distress. METHODS: We bench-tested 4 volume-cycled ventilators (Carevent ALS, EPV100, Pneupac VR1, and Medumat Easy) and 2 pressure-cycled ventilators (Oxylator EMX and VAR-Plus). We studied their general physical characteristics, sonometry, gas consumption, technical performance, ergonomy, and user-friendliness. With a test lung we assessed performance at F(IO(2)) of 0.50 and 1.0, set compliance of 30, 70, and 120 mL/cm H(2)O, and set resistance of 5, 10, and 20 cm H(2)O/L/s. To study user-friendliness and ergonomy we conducted, in randomized order, 7 or 8 objective, quantitative tests and 2 subjective tests. RESULTS: Compliance and resistance strongly affected tidal volume with the pressure-cycled ventilators (from 418 ± 49 mL to 1,377 ± 444 mL with the VAR-Plus, at the lowest pressure level), whereas the volume-cycled ventilators provided a consistent tidal volume in the face of changing test lung characteristics. CONCLUSIONS: We are concerned that the pressure-cycled ventilators did not provide a consistent tidal volume, and under certain conditions the volume delivered would be unsafe (too large or too small). Most of the volume-cycled ventilators proved to be technically efficient and reliable. Their reliability, portability, and ease of use could make them valuable in natural disasters and mass-casualty events.
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 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) | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".