Surgery for Asymptomatic Primary Hyperparathyroidism: Proceedings of the Third International Workshop
Bibliographic record
Abstract
CONTEXT: An international workshop on primary hyperparathyroidism (PHPT) was convened on May 13, 2008, to review and update the previous summary statement on the management of asymptomatic PHPT published in 2002. EVIDENCE ACQUISITION: Electronic literature sources were systematically reviewed, addressing critical aspects of the surgical issues pertaining to the indications, imaging, surgical treatment, and cost-effective management of patients with PHPT. EVIDENCE SYNTHESIS: The surgical group concluded that many patients with "asymptomatic" PHPT have neurocognitive symptoms that may be unmasked after successful parathyroidectomy. Furthermore, reduced bone density and increased fracture risk can be improved with parathyroidectomy. When PHPT is symptomatic, it may be associated with nephrolithiasis, increased cardiovascular disease, and decreased survival. Preoperative imaging studies should only be performed to help plan the operation, and negative imaging should never preclude surgical referral. Noninvasive localization studies including ultrasound and sestamibi scans are often employed, especially in anticipation of focused explorations. Invasive localization studies should be reserved for remedial explorations where noninvasive imaging has been unsuccessful. CONCLUSIONS: When performed by expert parathyroid surgeons, parathyroid surgery is safe, cost-effective, and associated with very low perioperative morbidity. Minimally invasive approaches to parathyroid surgery appear to be as effective as the classic bilateral cervical exploration approach.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.006 | 0.002 |
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".