The Clinical and Technical Evaluation of a Remote Telementored Telesonography System During the Acute Resuscitation and Transfer of the Injured Patient
Bibliographic record
Abstract
BACKGROUND: Ultrasound (US) has an ever increasing scope in the evaluation of trauma, but relies greatly on operator experience. NASA has refined telesongraphy (TS) protocols for traumatic injury, especially in reference to mentoring inexperienced users. We hypothesized that such TS might benefit remote terrestrial caregivers. We thus explored using real-time US and video communication between a remote (Banff) and central (Calgary) site during acute trauma resuscitations. METHODS: A existing internet link, allowing bidirectional videoconferencing and unidirectional US transmission was used between the Banff and Calgary ERs. Protocols to direct or observe an extended focused assessment with sonography for trauma (EFAST) were adapted from NASA algorithms. A call rota was established. Technical feasibility was ascertained through review of completed checklists. Involved personnel were interviewed with a semistructured interview. RESULTS: In addition to three normal volunteers, 20 acute clinical examinations were completed. Technical challenges requiring solution included initiating US; audio and video communications; image freezing; and US transmission delays. FAST exams were completed in all cases and EFASTs in 14. The critical anatomic features of a diagnostic examination were identified in 98% of all FAST exams and a 100% of all EFASTs that were attempted. Enhancement of clinical care included confirmation of five cases of hemoperitoneum and two pneumothoraces (PTXs), as well as educational benefits. Remote personnel were appreciative of the remote direction particularly when instructions were given sequentially in simple, nontechnical language. CONCLUSIONS: The remote real-time guidance or observation of an EFAST using TS appears feasible. Most technical problems were quickly overcome. Further evaluation of this approach and technology is warranted in more remote settings with less experienced personnel.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".