A systematic approach to the recurrent laryngeal nerve dissection at the cricothyroid junction
Bibliographic record
Abstract
BACKGROUND: To describe and evaluate a four step systematic approach to dissecting the recurrent laryngeal nerve (RLN) starting at the cricothyroid junction during thyroid surgery (subsequently referred to as the retrograde medial approach). METHODS: All thyroidectomies completed by the senior author between August 2014 and January 2016 were retrospectively reviewed. Patients were excluded if concurrent lateral or central neck dissection was performed. A follow up period of 1 year was included. RESULTS: Surgical photographs and illustrations demonstrate the four steps in the retrograde medial approach to dissection of the RLN in thyroid surgery. Three hundred forty-two consecutive thyroid surgeries were performed in 17 months, including 213 hemithyroidectomies, 91 total thyroidectomies, and 38 completion thyroidectomies. The rate of temporary and permanent hypocalcemia was 13% (95% confidence interval [CI]: 8-20%) and 3% (95% CI: 1-8%) respectively. The rate of temporary and permanent vocal cord palsy was 9% (95% CI: 6-12%) and 0.3% (95%CI: 0.01-2%) respectively. The median surgical times for hemithyroidectomy, total thyroidectomy, and completion thyroidectomy were 39 min (Interquartile range [IQR]: 33-47 min), 48 min (IQR: 40-60 min), and 40 min (IQR: 35-51 min) respectively. 1% of cases required conversion to an alternative surgical approach. CONCLUSION: In a tertiary endocrine head and neck practice, the routine use of the retrograde medial approach to RLN dissection is safe and results in a short operative time, and a low conversion rate to other RLN dissection approaches.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".