Quality-of-Life Outcomes in Graves Disease Patients after Total Thyroidectomy
Bibliographic record
Abstract
Historically, research into surgical treatment of Graves disease has assessed subtotal rather than total thyroidectomy. Most clinicians now recommend total thyroidectomy, but little information is available regarding quality-of-life (QOL) outcomes for this procedure. Our aim was to assess QOL after total thyroidectomy. This is a retrospective, pilot study of patients with Graves disease who underwent total thyroidectomy from 1991 to 2007 at a high-volume tertiary referral center in Toronto, Canada. Questionnaires addressing disease-specific symptoms and global QOL concerns were sent to 54 patients. Analyses included parametric and nonparametric tests to assess the differences between perception of symptoms and global QOL before and after surgery. Forty patients responded (response rate: 74%) at a median of 4.8 years postoperatively. On a 10-point scale, overall wellness improved from 4.1 preoperatively to 8.7 postoperatively (p < 0.001). Patients recalled missing less work or school after surgery (7.8 vs. 1.1 days/year; p = 0.001). Overall satisfaction with the procedure was high. On average, symptoms improved within 32 days of surgery, and all symptoms showed substantial improvement. This is the first North American study to assess QOL outcomes of patients with Graves disease after total thyroidectomy. Patients experienced marked and rapid improvement in QOL postoperatively. These findings suggest that total thyroidectomy is a safe and effective treatment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".