Management of Primary Hyperparathyroidism
Bibliographic record
Abstract
Since the last international guidelines were published in 2014 on the evaluation and management of primary hyperparathyroidism (PHPT), new information has become available with regard to evaluation, diagnosis, epidemiology, genetics, classical and nonclassical manifestations, surgical and nonsurgical approaches, and natural history. To provide the most current summary of these developments, an international group, consisting of over 50 experts in these various aspects of PHPT, was convened. This paper provides the results of the task force that was assigned to review the information on the management of PHPT. For this task force on the management of PHPT, two questions were the subject of systematic reviews using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) methodology. The full report addressing surgical and nonsurgical management of PHPT, utilizing the GRADE methodology, is published separately in this series. In this report, we summarize the results of that methodological review and expand them to encompass a much larger body of new knowledge that did not specifically fit the criteria of the GRADE methodology. Together, both the systematic and narrative reviews of the literature, summarized in this paper, give the most complete information available to date. A panel of experts then considered the last set of international guidelines in light of the newer data and assessed the need for their revision. This report provides the evidentiary background to the guidelines report. In that report, evidence from all task forces is synthesized into a summary statement and revised guidelines for the evaluation and management of PHPT. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".