Intraoperative Parathyroid Hormone is a Valuable Indicator of Long Term Cure in Primary Hyperparathyroidism
Bibliographic record
Abstract
Background: The use of intraoperative parathyroid hormone (ioPTH) during surgery for primary hyperparathyroidism (PHPT) has become widely available as a tool to monitor the success of the procedure. The aim of our study was to correlate the decrease of ioPTH with long term outcome in patients with PHPT. Methods: During a 10 year period, in 137 consecutive patients with PHPT, serum PTH was measured during surgery at baseline and 5, 10 and 20 minutes after excision of the suspected parathyroid gland. Surgery was considered successful if a 50% drop in ioPTH was observed after 10 minutes. Two groups were defined - with normal (I) and above normal (II) PTH after 10 minutes. Calcium and PTH were monitored at 1.5, 3, 6 and 12 months of follow-up. Results: Group I had significantly lower median weight of glands (1.4 vs 3.0 g), maximum pre-operative calcium (11.1 vs 11.7 mg/dL) and ioPTH at 10 minutes (30.1 vs 124.9 pg/mL) than group II - P < 0.05. Serum PTH levels at 3 and 6 months of follow-up were also significantly lower in group I than group II (55.0 vs 124.5 pg/mL and 55.9 vs 83.1 pg/mL, respectively) - P < 0.05. At 6 months, 74.3% of the patients in group I presented normal calcium and PTH, whereas in group II normal calcium and high PTH was the predominant pattern (59.1%) - P = 0.01. Conclusions: Obtaining normalization of ioPTH during surgery is important in addition to the classic criterion of 50% decrease from baseline to predict cure of PHPT. doi: http://dx.doi.org/10.4021/jem189w
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".