Thyroidectomy for Graves’ Disease Predicts Postoperative Neck Hematoma and Hypocalcemia: A North American cohort study
Bibliographic record
Abstract
OBJECTIVE: Examine the association of Graves' disease with the development of postoperative neck hematoma. DESIGN: A cohort of patients participating in the Thyroid Procedure-Targeted Database of the National Surgical Quality Improvement Program from January 1, 2016 to December 31, 2018. SETTING: A North American surgical cohort study. METHODS: 17 906 patients who underwent thyroidectomy were included. Propensity score matching was performed to adjust for differences in baseline covariates. Multivariate logistic regression was used to ascertain the association between thyroidectomy for Graves' disease and risk of postoperative adverse events within 30 days of surgery. The primary outcome was postoperative hematoma. Secondary outcomes were postoperative hypocalcemia and recurrent laryngeal nerve injury. RESULTS: One-to-three propensity score matching yielded 1207 patients with mean age (SD) of 42.6 (14.9) years and 1017 (84.3%) female in the group with Graves' disease and 3621 patients with mean age (SD) of 46.7 (15.0%) years and 2998 (82.8%) female in the group with indications other than Graves' disease for thyroidectomy. The cumulative 30-day incidence of postoperative hematoma was 3.1% (38/1207) in the Graves' disease group and 1.9% (70/3621) in other patients. The matched cohort showed that Graves' disease was associated with higher odds of postoperative hematoma (OR 1.65, 95% CI 1.10-2.46) and hypocalcemia (OR 2.04, 95% CI 1.66-2.50) compared with other indications for thyroid surgery. There was no difference in recurrent laryngeal nerve injury among the 2 groups. CONCLUSIONS: Patients with Graves' disease undergoing thyroidectomy are more likely to suffer from postoperative hematoma and hypocalcemia compared to patients undergoing surgery for other indications.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".