Quality of Life in Patients Undergoing Thyroid Surgery
Bibliographic record
Abstract
OBJECTIVE: The extent of thyroidectomy in the management of low-risk, well-differentiated thyroid carcinoma (WDTC) has been debated extensively. Our objective was to determine if hemithyroidectomy has a less detrimental effect on quality of life (QOL) than total thyroidectomy. DESIGN: Prospective, nonblinded, nonrandomized, cohort study. SETTING: Tertiary care academic otolaryngology-head and neck surgery practice. METHODS: Using both disease-specific and global QOL instruments, patients treated with either hemi- or total thyroidectomy were prospectively followed. QOL was assessed preoperatively and for 12 months postoperatively. MAIN OUTCOME MEASURES: Scores on the two QOL instruments throughout a 12-month postoperative period. RESULTS: Patients with cancer experienced a greater drop in QOL during the first 6 months following surgery when compared with patients with benign disease (p < .03). Additionally, patients treated with total thyroidectomy did not have a significantly different QOL than patients treated with hemithyroidectomy (p > .2). CONCLUSION: These results suggest that QOL is not significantly impacted by the extent of surgery and that QOL should not be a factor in the decision-making process for the treatment of low-risk WDTC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".