A Systematic Review of Tools to Measure Respiratory Rate in Order to Identify Childhood Pneumonia
Bibliographic record
Abstract
Pneumonia is the leading infectious cause of death in children worldwide, with most deaths occurring in developing countries. Measuring respiratory rate is critical to the World Health Organization's guidelines for diagnosing childhood pneumonia in low-resource settings, yet it is difficult to accurately measure. We conducted a systematic review to landscape existing respiratory rate measurement technologies. We searched PubMed, Embase, and Compendex for studies published through September 2017 assessing the accuracy of respiratory rate measurement technologies in children. We identified 16 studies: 2 describing manual devices and 14 describing automated devices. Although both studies describing manual devices took place in low-resource settings, all studies describing automated devices were conducted in well-resourced settings. Direct comparison between studies was complicated by small sample size, absence of a consistent reference standard, and variations in comparison methodology. There is an urgent need for affordable and appropriate innovations that can reliably measure a child's respiratory rate in low-resource settings. Accelerating development or scale-up of these technologies could have the potential to advance childhood pneumonia diagnosis worldwide.
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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 | 0.008 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".