Clinicopathologic and therapeutic risk factors for perioperative complications and prolonged hospital stay in free flap reconstruction of the head and neck
Bibliographic record
Abstract
BACKGROUND: We aimed to determine predictors of morbidity in patients undergoing microvascular free flap reconstruction of the head and neck. METHODS: We prospectively evaluated 796 cases between 1999 and 2007 using univariate and multivariate analysis to determine predictors of morbidity and prolonged hospital stay. RESULTS: Two hundred thirty-nine patients (30%) developed major complications. Age, body mass index (BMI), American Society of Anesthesiology (ASA) score, Kaplan Feinstein comorbidity index (KFI) score, preoperative hemoglobin, and tracheostomy were independent predictors of major complication. Predictors of prolonged hospital stay included age, recent weight loss, alcohol excess, ASA, KFI, preoperative hemoglobin, mucosal surgery, anesthesia duration, and crystalloid replacement volume. CONCLUSION: Several variables are associated with an increased risk of development of major complications following free flap reconstruction of the head and neck. Although many of these variables are irreversible, they aid risk stratification of patients undergoing free flap reconstruction, and assist clinicians in making treatment decisions, consenting, and providing patients with realistic expectations regarding their perioperative course.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".