Empowering the willing: the feasibility of tele-mentored self-performed pleural ultrasound assessment for the surveillance of lung health
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: SARS-CoV-2 infection, manifesting as COVID-19 pneumonia, constitutes a global pandemic that is disrupting health-care systems. Most patients who are infected are asymptomatic/pauci-symptomatic can safely self-isolate at home. However, even previously healthy individuals can deteriorate rapidly with life-threatening respiratory failure characterized by disproportionate hypoxemic failure compared to symptoms. Ultrasound findings have been proposed as an early indicator of progression to severe disease. Furthermore, ultrasound is a safe imaging modality that can be performed by novice users remotely guided by experts. We thus examined the feasibility of utilizing common household informatic-technologies to facilitate self-performed lung ultrasound. METHODS: A lung ultrasound expert remotely mentored and guided participants to image their own chests with a hand-held ultrasound transducer. The results were evaluated in real time by the mentor, and independently scored by three independent experts [planned a priori]. The primary outcomes were feasibility in obtaining good-quality interpretable images from each anatomic location recommended for COVID-19 diagnosis. RESULTS: Twenty-seven adults volunteered. All could be guided to obtain images of the pleura of the 8 anterior and lateral lung zones (216/216 attempts). These images were rated as interpretable by the 3 experts in 99.8% (647/648) of reviews. Fully imaging one's posterior region was harder; only 108/162 (66%) of image acquisitions was possible. Of these, 99.3% of images were interpretable in blinded evaluations. However, 52/54 (96%) of participants could image their lower posterior lung bases, where COVID-19 is most common, with 99.3% rated as interpretable. CONCLUSIONS: Ultrasound-novice adults at risk for COVID-19 deterioration can be successfully mentored using freely available software and low-cost ultrasound devices to provide meaningful lung ultrasound surveillance of themselves that could potentially stratify asymptomatic/paucisymptomatic patients with early risk factors for serious disease. Further studies examining practical logistics should be conducted. TRIAL REGISTRATION: ID ISRCTN/77929274 on 07/03/2015.
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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 | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it