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Record W4205855701 · doi:10.1186/s13089-021-00250-6

Empowering the willing: the feasibility of tele-mentored self-performed pleural ultrasound assessment for the surveillance of lung health

2022· article· en· W4205855701 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Ultrasound Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsFoothills Medical CentreUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsMedicineLung ultrasoundUltrasoundInterventional radiologyRadiologyAsymptomaticEconomic shortageCoronavirus disease 2019 (COVID-19)LungMedical physicsDiseaseSurgeryPathologyInternal medicineGovernment (linguistics)

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.410
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it