Free flap monitoring using an implantable Doppler probe
Bibliographic record
Abstract
Although clinical observation is the gold standard, the ideal free flap monitoring device has not been identified. The purpose of the present study was to review the first 14 months of experience using an implantable 20-MHz ultrasonic Doppler probe to monitor the microvascular anastamoses of free tissue transfers. Twenty-five flaps in 23 patients, with an average age of 51 years (age range 18 to 81 years), were performed. Probes were secured downstream of the venous anastamosis using a silicone-poly fluorotetraethylene sleeve. Doppler sounds were transduced before the flap was inset. Monitoring by nursing staff included conventional techniques (temperature, colour, capillary refill) and continuous Doppler flow monitoring. Dynamic diagnostic testing for anastomotic patency was facilitated by applying manual pressure on the flap to increase venous flow (the audible ‘whoosh’ sign) and valsalva manoeuvre to impede venous return momentarily (the ‘heave’ sign). Intraoperative vessel kinking, hematoma formation occluding venous outflow, and venous thrombosis were detected in four cases before concluding the procedure and corrected. Rapid, immediate cessation of audible flow was detected postoperatively in three of 25 flaps. Re-exploration (re-exploration rate 12%) led to salvage of all three flaps (salvage rate 100%). It was concluded from this study that flap re-exploration was prevented in four cases (16%) because of intraoperative use of the implantable Doppler probe. Earlier detection of flap compromise perioperatively is thought to have contributed to the 100% salvage rate and to the 100% flap survival rate in the first 25 cases in which the implantable Doppler probe was used.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".