Delayed serum calcium biochemical response to successful parathyroidectomy in primary hyperparathyroidism
Bibliographic record
Abstract
BACKGROUND: Parathyroidectomy is considered the standard treatment for primary hyperparathyroidism, however, though the onset of biochemical response is variable and is different from one patient to the other. AIM: To evaluate the onset of systemic response and the biochemical normalization of serum calcium levels to a successful surgery. PATIENTS AND METHODS: In a retrospective fashion, we collected clinical data from 303 patients admitted to our hospital between 2005 and 2008, with a diagnosis of primary hyperparathyroidism after sestamibi localization. The pathology reports, parathyroidectomy results, the preoperative and postoperative parathormone (PTH) and serum calcium levels were reviewed. Response of each patient to the surgery was studied and all the data were analyzed to determine how fast the serum calcium levels drop. RESULTS: The majority of patients (72.9%, 221/303) showed a decrease in their serum calcium levels to normal values within 48 h. While in 40 patients it took 72 hours and 42 patients (13.8%) had a delayed normalization for more than 72 h. The pathology in the PH group was predominantly of a single adenoma 80.9% vs.19.1 with hyperplasia with a P of 0.03. Preoperative parathyroid hormone PTH elevation was not significantly deferent between the two groups (PH and EN) with a mean of 7.9±5.36 vs. 7.41±14.5 pmol/L respectively with a P of 0.43. CONCLUSION: The majority of patients with primary hyperparathyroidism (PHP) respond to parathyroidectomy in the form of normalization of their serum calcium levels and PTH within 48 h; however, a certain group of patients will need more than 3 days.
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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 | 0.001 |
| 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".