Arteriovenous fistulas for microvascular head and neck reconstruction
Bibliographic record
Abstract
Background In head and neck cancer patients, multiple surgeries and radiation can leave the neck depleted of recipient vessels appropriate for microvascular reconstruction. The creation of temporary arteriovenous fistulas using venous interposition for subsequent microvascular reconstruction has rarely been reported in the head and neck. The authors report the largest series of temporary arteriovenous loops for head and neck reconstruction in vessel-depleted necks. Methods The authors performed a case series of major head and neck reconstructions using temporary arteriovenous fistulas with a saphenous vein graft. A subclavian surgical approach was used. All reconstructions were performed at least two weeks after the creation of the initial fistula. Results The authors have performed nine reconstructive cases for malignancy using five different free flaps. The subclavian and transerve cervical arteries were used, and the subclavian, internal jugular and cephalic veins were used for microanastomosis. Two cases of flap hematoma and one case of venous pedicle compression were recorded. No cases of flap failure were reported. Conclusions Reconstruction using temporary arteriovenous fistulas is a reliable technique that can be used in the vessel-depleted neck, with excellent outcomes in experienced hands.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".