Post-thyroidectomy hematoma and hypocalcemia as separate complications: risk factors and management—a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Thyroidectomy is a common surgical procedure for various thyroid conditions, including benign nodules, multinodular goiters, hyperthyroidism, and malignancies. Despite its widespread use, it is associated with significant complications such as post-thyroidectomy hematoma and hypocalcemia. This systematic review aims to evaluate the risk factors and management strategies for these complications to enhance patient outcomes. Methods: This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive search was conducted across multiple electronic databases, including Scopus, Cochrane Library, Web of Science, PubMed, and ScienceDirect, using keywords related to post-thyroidectomy hematoma and hypocalcemia. Only studies published between 2010 and 2024 were considered. Studies were included if they focused on adult patients undergoing thyroidectomy and reported on the incidence or management of these complications. Studies were excluded if they were letters to the editor, case reports, opinion pieces, non-peer-reviewed articles or not in English. Pooled rates for hematoma and hypocalcemia were calculated using R software. A random-effects model was used to address study heterogeneity and calculate the pooled incidence estimate. The Newcastle-Ottawa Scale (NOS) was used to assess bias and select high-quality studies, improving the reliability of the results. Results: The present study identified 10 studies meeting the inclusion criteria (253,941 participants), with most scoring 9/9 on the NOS. The meta-analysis revealed that the pooled incidence of post-thyroidectomy hematoma is approximately 1.43% [95% confidence interval (CI): 1.07% to 1.80%, P<0.001], with significant heterogeneity across studies (I2=88.01%, P<0.001). Notable risk factors include older age, vitamin D deficiency, and thyroid malignancy. For hypocalcemia, the pooled incidence is around 23.14% (95% CI: 10.96% to 35.32%, P<0.001), also showing substantial heterogeneity (I2=99.97%, P<0.001). Risk factors included older age, female sex, malignancy, total thyroidectomy, and Graves’ disease. Effective management strategies for hematoma included reoperation and tracheostomy, while for hypocalcemia, calcium and vitamin D supplementation and intravenous calcium were critical. Conclusions: Post-thyroidectomy hematoma and hypocalcemia are major complications that affect patient outcomes and increase healthcare costs. Identifying risk factors and applying effective surgical and postoperative strategies can help reduce these risks.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".