Utility of the Harmonic Scalpel in Selective Neck Dissection
Bibliographic record
Abstract
1) Evaluate the role of the harmonic scalpel in selective neck dissection (levels I - IV) 2) Determine the effect of the harmonic scalpel on intraoperative blood loss and operative time Twenty-seven adult head and neck cancer patients requiring a selective neck dissection (either alone or as part of a larger oncologic resection) located at a single academic tertiary care centre from January 2009 to January 2010 were enrolled in a prospective, randomized controlled trial. Exclusion criteria were previous treatment for head and neck cancer, age <18 and if the patient was unwilling/ unable to provide informed consent. To ensure sufficient familiarity with the harmonic scalpel, both surgeons in this study were required to perform 10 neck dissections with the instrument prior to enrolling patients to the protocol. Primary outcomes of interest were: intraoperative blood loss (mL) and operative time (minutes). Secondary outcomes of interest were: intraoperative complications, postoperative complications (48-hour, 1-week and 1-month intervals), postoperative drain outputs (48-hour and 1-week intervals) and length of hospital admission after surgery. There was no significant difference between experimental and control groups for either operative time (p = 0.3) or intraoperative blood loss (p = 0.07). No significant difference between groups was observed for 48-hour (p = 0.1) and 1-week (p = 0.8) postoperative surgical drain outputs. Nor was there any difference in the duration of hospital admission between groups (p = 0.3). There were no intraoperative complications reported. In level I - IV neck dissection, the harmonic scalpel does not reduce operative time or blood loss when compared to conventional surgical techniques.
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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 | 0.000 |
| 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".