Indications and Rationale for Use of Vascularized Fibula Bone Flaps in Cervical Spine Arthrodeses
Bibliographic record
Abstract
BACKGROUND: Anterior cervical spine arthrodesis for large defects using autograft or allograft fibula for anterior structural support is a widely accepted procedure. In unique demand situations, a vascularized fibular flap is regarded as an "improvement" to the standard procedure. While a vascularized flap does deliver living tissue to the region, it does so with added potential morbidity and increased technical demand. The indications in the literature for this procedure have not been clearly defined. In this article, the authors review specific high-demand situations where they believe a vascularized flap is indicated. They also review patient outcomes after this procedure. METHODS: Fibular free flaps were used in six patients with failed previous cervical spine arthrodeses. Three of the six patients had preoperative radiation therapy, and one received postoperative radiation treatment. All six patients had tumor and/or osteomyelitis present. RESULTS: One patient died of intraoperative hypotension 3 days after a successful free flap transfer during an elective posterior spine instrumentation procedure. One flap was lost from a venous thrombosis, and the patient was then treated successfully with a second fibular free flap. Clinical and radio-graphic evidence of fusion was obtained at 3 months in the five surviving patients, and neurologic function remained stable or improved. CONCLUSIONS: Analyzing their results and the literature, the authors propose that fibular free flaps are indeed a useful adjunct in difficult cervical spine stabilization procedures. Indications for this flap include combinations of the following situations: failed prior attempts at fusion, anterior cervical arthrodeses of three or more vertebral levels, osteomyelitis of the spine, and tumor cases when the spine has been or will be radiated.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".