Neck extension during thyroidectomy: effects on early postoperative cognitive function and optic nerve sheath diameter- a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: During thyroidectomy, patients are commonly positioned with neck extension using a shoulder roll. Excessive extension may impair arterial and venous outflow, compromise cerebral perfusion, and elevate intracranial pressure, potentially leading to postoperative cognitive impairment. This study investigated the effect of shoulder-roll-assisted neck extension on cognitive outcomes and on optic nerve sheath diameter (ONSD). METHODS: After tracheal intubation, patients were randomly assigned to either a shoulder roll group or a control group without a roll. The primary outcome was the Montreal Cognitive Assessment (MoCA) score at 6 h postoperatively. Secondary outcomes included ONSD and the degree of neck extension. RESULTS: Postoperative MoCA scores were significantly lower in the shoulder roll group (20.56 ± 2.71) compared with the control group (23.57 ± 2.37; P < 0.001). ONSD increased over time in both groups (P < 0.001), but repeated-measures analysis showed no significant difference between groups (P = 0.333). Neck extension was greater in the shoulder roll group (126 ± 4.36°) than in the control group (116 ± 3.74°; P < 0.001). CONCLUSIONS: Shoulder roll positioning during thyroidectomy was associated with lower MoCA scores at 6 h, indicating mild postoperative cognitive decline. Although greater neck extension was observed, ONSD values did not significantly differ between groups. TRIAL REGISTRATION: Muğla Sıtkı Koçman University Clinical Research Ethics Committee (approval number T-XII, June 17, 2019). Australian New Zealand Clinical Trials Registry (registration number: ACTRN12619001066178, date of registration: July 31, 2019).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".