Effect of fibula free flap harvest on the gait of head and neck cancer patients: preliminary results.
Bibliographic record
Abstract
OBJECTIVE: To determine the impact of fibula free flaps (FFFs) on gait. DESIGN: Prospective trial. SETTING: FFF patients who gave consent were enrolled. METHODS: At preoperative and 3-month postoperative visits, patients walked 30 m with the Walkabout Portable Gait Monitor (WPGM), a portable device developed at Dalhousie University that records acceleration of the centre of mass. Gaitview software provided several outputs for analysis: vertical (VA) and forward (FA) asymmetry, horizontal to vertical power ratio (HVP), vertical to forward power ratio (VFP), velocity, and step length. Patients were compared pre- and postoperatively and to age-matched control data with a Student paired t-test. Patients completed a self-comorbidity questionnaire and a point evaluation system (PES) with subjective questions on gait. PES data were compared to a Mann-Whitney U test using SPSS, version 15.0.1. MAIN OUTCOME MEASURES: Gaitview output and PES questionnaire. RESULTS: From September 2008 to January 2010, 12 patients enrolled in the study. Eight provided 3-month postoperative data. The Gaitview analysis showed that none of the six parameters changed postoperatively. The VA and FA preoperatively and at 3 months postoperatively were 21.3 versus 24.2, p > .50, and 65.4 versus 74.9, p > .50, respectively. The HVP and VFP preoperatively and postoperatively were 133.4 versus 138.9, p > .50, and 129.6 versus 122.8, p > .50, respectively. The velocity and step length preoperatively and postoperatively were 125.9 versus 119.5 cm/s, p > .50, and 76.0 versus 74.9 cm, p > .50, respectively. The subjective PES questionnaire did not change significantly (p = .26). CONCLUSION: Preliminary findings confirm that the FFF is associated with little subjective or objective gait impairment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".