A pilot study of surgical telementoring for leg fasciotomy
Bibliographic record
Abstract
INTRODUCTION: Acute extremity compartment syndrome requires rapid decompression. In remote locations, distance, weather and logistics may delay the evacuation of patients with extremity trauma beyond the desired timeline for compartment release. The aim of this study was to establish the feasibility of performing telementored surgery for leg compartment release and to identify methodological issues relevant for future research. METHODS: Three anaethetists and one critical care physician were recruited as operators. They were directed to perform a two-incision leg fasciotomy on a Thiel-embalmed cadaver under the guidance of a remotely located orthopaedic surgeon. The operating physician and the surgeon (mentor) were connected through software that allows for real-time supervision and the use of a virtual pointer overlaid onto the surgical field. Two experienced orthopaedic traumatologists independently assessed the adequacy of compartment decompression and the presence of iatrogenic complications. RESULTS: 14 of 16 compartments (in four leg specimens) were felt to have been completely released. The first evaluator considered that the deep posterior compartment was incompletely released in two specimens. The second evaluator considered that the superficial posterior compartment was incompletely released in two specimens. The only complication was a large laceration of the soleus muscle that occurred during a period of blurred video signal attributed to a drop in bandwidth. CONCLUSIONS: This study suggests that surgical telementoring may enable physicians to safely perform two-incision leg fasciotomy in remote environments. This could improve the chances of limb salvage when compartment syndrome occurs far from surgical care. We found interobserver variation in the assessment of compartment release, which should be considered in the design of future research protocols.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".