Evaluation of Preference and Utility Measures for Transoral Thyroidectomy
Bibliographic record
Abstract
BACKGROUND: Traditional, trans-cervical thyroidectomy results in the presence of a neck scar, which has been shown to correlate with lower quality of life and lower patient satisfaction. Transoral thyroid surgery (TOTS) has been utilized as an alternative approach to avoid a cutaneous incision and scar by accessing the neck and thyroid through the oral cavity. This study was designed to evaluate patient preference through health-state utility scores for TOTS as compared to conventional trans-cervical thyroidectomy. METHODS: In this cross-sectional study, patient preferences were elicited for TOTS and trans-cervical thyroidectomy with the use of an online survey. Respondents were asked to consider 4 hypothetical health scenarios involving thyroid surgery with varying approaches. Health-state utility scores were elicited using visual analog scale and standard gamble exercises. RESULTS: Overall, 516 respondents completed the survey, of whom 261 (50.6%) were included for analysis, with a mean age of 41.5 years (SD 14.9 years), including 171 (65.5%) females. Health utility scores were similar for TOTS and conventional transcervical techniques. Statistically significant differences in the standard gamble utility score were noted for gender and ethnicity across all scenarios. Comparisons of visual analog score utilities were not statistically significant based on respondent demographics. CONCLUSION: Preferences for TOTS and trans-cervical thyroidectomy did not significantly differ in the current study. Females and white ethnicity indicated stronger preference for a TOTs approach compared to males and other ethnicities, respectively. Some literature suggests certain types of patients who might prefer minimally invasive thyroidectomy more so than other patients-in keeping with the current findings of this study.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".