Development of a novel device for objective respiratory rate measurement in low-resource settings
Bibliographic record
Abstract
Objective To evaluate a novel device (Respimometer) for objective measurement of respiratory rate (RR) in low-resource settings. Design Description of prototype development, with proof-of-concept pilot field study at four paediatric healthcare facilities in Butembo, Democratic Republic of the Congo (DRC). The instrument was tested in healthy adult volunteers (n=10) and Congolese children (n=42) and compared with timed breaths (adults) or by reference comparator capnography (children). Correlation and Bland-Altman plots were generated for paired measurements. Results The Respimometer is shaped like an oral thermometer and is placed in the mouth of the participants. RR is measured by thermistors positioned at the nasal outlet, which detect the temperature change between inhaled and exhaled breaths. In adult volunteers, the correlation coefficient between the delivered RR and the Respimometer measurement was median 0.992 (IQR 0.980–0.999). Measurement bias was −0.50 min−1 (95% CI −1.1 to +0.07, p=0.093), with upper and lower limits of agreement of −5.2 min−1 and 4.2 min−1, respectively. Among Congolese children, there was no evidence of bias: mean difference in RR +1.0 min−1 (95% CI −2.1 to +4.1, p=0.52). The upper and lower limits of agreement were −18 and +20 min−1, respectively. Conclusion The Respimometer can accurately measure the RR in healthy adults and children in DRC. A simple and accurate instrument could facilitate the diagnosis of pneumonia by community health workers in low-income and middle-income countries, leading to reduced pneumonia-related deaths.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".