2b or not 2b? Shoulder function after level 2b neck dissection: A double‐blind randomized controlled clinical trial
Bibliographic record
Abstract
BACKGROUND: Selective neck dissection (SND) is a mainstay of head and neck cancer treatment. A common sequela is shoulder syndrome from spinal accessory nerve (SAN) trauma. Extensive dissection in neck levels 2 and 5 leads to SAN dysfunction. However, it is not known whether limited level 2 dissection reduces SAN injury. The purpose of this double-blind randomized controlled trial was to determine whether omitting level 2b dissection would improve shoulder-related quality of life and function. METHODS: Patients with head and neck cancers undergoing surgery were randomized 1:1 to SND without level 2b dissection (group 1) or with it (group 2) on their dominant-hand side. Patients, caregivers, and assessors were blinded. The primary outcome was the change in the Neck Dissection Impairment Index (NDII) score after 6 months. An a priori calculation of the minimally important clinical difference in the NDII score was determined to establish a sample size of 15 patients per group (power = 0.8). Secondary outcomes included shoulder strength and range of motion (ROM) and SAN nerve conduction. The trial was registered at ClinicalTrials.gov (NCT00765791). RESULTS: Forty patients were enrolled, and 30 were included (15 per group). Six months after the surgery, group 2 demonstrated a significant median decrease in the NDII from the baseline (30 points) and in comparison with group 1, whose NDII dropped 17.5 points (P = .02). Shoulder ROM and SAN conduction demonstrated significant declines in group 2 (P ≤ .05). No adverse events occurred. CONCLUSIONS: Level 2b should be omitted in SND when this is oncologically safe and feasible. This allows for an optimal balance between function and cancer cure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".