Risk factors of transient and permanent hypoparathyroidism after thyroidectomy: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Postoperative hypoparathyroidism (hypoPT) is a common complication following thyroid surgery. However, current research findings on the risk factors for post-thyroid surgery hypoPT are not entirely consistent, and the same risk factors may have different impacts on transient and permanent hypoPT. Therefore, there is a need for a comprehensive study to summarize and explore the risk factors for both transient and permanent hypoPT after thyroid surgery. MATERIALS AND METHODS: Two databases (PubMed and Embase) were searched from inception to 2024. The Newcastle-Ottawa Scale was used to rate study quality. Pooled odds ratios were used to calculate the relationship of each risk factor with transient and permanent hypoPT. Subgroup analyses were conducted for hypoPT with different definition-time (6 or 12 months). Publication bias was assessed using Begg's test and Egger's test. RESULTS: A total of 19 risk factors from the 93 studies were included in the analysis. Among them, sex and parathyroid autotransplantation were the most frequently reported risk factors. Meta-analysis demonstrated that sex (female vs. male), cN stage, central neck dissection, lateral neck dissection, extent of central neck dissection (bilateral vs. unilateral), surgery [total thyroidectomy (TT) vs. lobectomy], surgery type (TT vs. sub-TT), incidental parathyroidectomy, and pathology (cancer vs. benign) were significantly associated with transient and permanent hypoPT. Preoperative calcium and parathyroid autotransplantation were only identified as risk factors for transient hypoPT, while preoperative PTH was a protective factor. Additionally, node metastasis and parathyroid in specimen were associated with permanent hypoPT. CONCLUSION: The highest risk of hypoPT occurs in female thyroid cancer patients with lymph node metastasis undergoing TT combined with neck dissection. The key to preventing postoperative hypoPT lies in the selection of surgical approach and intraoperative protection.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.022 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".