A Train-the-Trainer Point of Care Ultrasound (POCUS) Program for Pediatric Pneumonia in a Low-Resource Setting
Bibliographic record
Abstract
Background: Lung point of care ultrasound (POCUS) has the potential to transform pediatric pneumonia care in low resource settings. Prior studies of novice POCUS users in such settings showed high agreement with remote POCUS experts for diagnosing pediatric pneumonia, but use of remote experts may falsely inflate this agreement. Objectives: This study aimed to 1. Deliver a train-the-trainer program in Pakistan on lung POCUS for diagnosing pediatric pneumonia; 2. Determine inter-rater reliability between i) study-trained community health workers (CHWs) and a remote expert, with both interpreting POCUS examinations acquired by the CHWs, and ii) study-trained CHWs and local champions, with both interpreting examinations that they had acquired. Methods: Phase 1: Canadian pediatric POCUS experts developed and delivered a lung POCUS training program for two user groups in Pakistan. These groups included local champions (who had POCUS experience) and CHWs (who were POCUS novices). Phase 2: Children with suspected pneumonia underwent two lung POCUS examinations, one by a CHW and one by a local champion. Examinations were recorded and later reviewed by a remote expert for interpretation and quality assurance. Inter-rater reliability was determined. Results: Two local champions and three CHWs were successfully trained. An analysis of 231 recruited patients showed strong inter-rater reliability between study-trained CHWs and remote expert interpretations (κ = 0.83). In contrast, inter-rater reliability was moderate (κ = 0.66) between interpretations by novices and local champions when these users interpreted the examinations that they themselves had acquired. Conclusion: Our study showed that train-the-trainer programs are feasible and can be effective, while highlighting the importance of hands-on training and having local champions provide longitudinal support to novices.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".