Trends in using intraoperative parathyroid hormone monitoring during parathyroidectomy: Protocol and rationale for a cross-sectional survey study of North American surgeons
Bibliographic record
Abstract
Hyperparathyroidism is a common endocrine disorder that occurs secondary to abnormal parathyroid gland functioning. Depending on the type of hyperparathyroidism, surgical extirpation of hyperfunctioning parathyroid glands can be considered for disease cure. Intraoperative parathyroid hormone (IOPTH) monitoring improves outcomes in patients undergoing surgery for primary hyperparathyroidism, but studies are needed to characterize its institutional adoption and its role in surgery for secondary and tertiary hyperparathyroidism, as these entities can be difficult to cure. Hence, we will perform a cross-sectional survey study of surgeon rationale, operational details, and barriers associated with IOPTH monitoring adoption across North America. We will utilize a convenience sampling technique to distribute an online survey to head and neck surgeons and endocrine surgeons across North America. This survey will be distributed via email to three North American professional societies (i.e., Canadian Society for Otolaryngologists-Head and Neck Surgeons, American Head and Neck Society, and American Association of Endocrine Surgeons). The survey will consist of 30 multiple choice questions that are divided into three concepts: (1) participant demographics and training details, (2) details of surgical adjuncts during parathyroidectomy, and (3) barriers to adoption of IOPTH. Descriptive analyses and multiple logistic regression will be used to evaluate the impact of demographic, institutional, and training variables on the use of IOPTH monitoring in surgery for all types of hyperparathyroidism and barriers to IOPTH monitoring adoption. Ethics approval was obtained by the Hamilton Integrated Research Ethics Board (2024-17173-GRA). These findings will characterize surgeon and institutional practices with regards to IOPTH monitoring during parathyroid surgery and will inform future trials aimed to optimize the use of IOPTH monitoring in secondary and tertiary hyperparathyroidism.
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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 | 0.029 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".