Female Gender as a Risk Factor for Transient Post‐Thyroidectomy Hypocalcemia
Bibliographic record
Abstract
OBJECTIVES: Transient post-thyroidectomy hypocalcemia is a common complication following thyroid surgery. Studies have identified risk factors and possible ways to help predict post-thyroidectomy hypocalcemia with the intent of ultimately limiting its incidence. This study evaluates the role of patient gender as a potential risk factor. STUDY DESIGN: A retrospective case series with chart review of 270 consecutive total thyroidectomy patients was conducted. SETTING: Jewish General Hospital, a McGill University-affiliated hospital in Montreal, Canada. SUBJECTS AND METHODS: 219 women and 51 men were included. Postoperative hypocalcemia was defined as any 1 of the following: total serum calcium 1.90 mmol/L or less, or signs and symptoms of hypocalcemia. The following were evaluated as potential confounding factors in the study: age, menopause, preoperative calcium, parathyroid hormone, magnesium and phosphate levels, presence of carcinoma in the surgical specimen, number of parathyroid glands preserved in situ, thyroid gland volume, and nodule size. RESULTS: Female patients experienced transient postoperative hypocalcemia in 24.7% (54/219) of cases, which was significantly greater than the 11.8% (6/51) incidence detected in men (P < .05). This represents a female/male relative risk ratio of 2.1 (confidence interval, 1.0-4.6). There was no significant difference in rates of hypocalcemia between premenopausal and postmenopausal women (22.7% vs 26.6%). CONCLUSION: These findings suggest that being female is likely a risk factor for transient post-thyroidectomy hypocalcemia. Although this association is statistically significant, its magnitude and clinical relevance are uncertain and may be trivial. Additional research is needed to ascertain the physiologic mechanisms underlying this gender difference.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".