Short-term medical treatment of hypercalcaemia in primary hyperparathyroidism predicts symptomatic response after parathyroidectomy
Bibliographic record
Abstract
BACKGROUND: Primary hyperparathyroidism is often associated with non-disease-specific symptoms. The aim of this study was to evaluate whether normalization of hypercalcaemia with short-term medical treatment can be used to predict the effects of parathyroidectomy and guide in surgical decision-making. METHODS: This observational study included patients who received calcimimetic treatment for 4 weeks before parathyroidectomy (30-60 mg daily). A panel of tests was used to assess various aspects of quality of life (European Organisation and Treatment of Cancer QLQ-C30 core questionnaire, Hospital Anxiety and Depression Scale and Positive State of Mind questionnaire), cognitive function (Montreal Cognitive Assessment) and muscle strength (timed-stands test). The tests were carried out at baseline, after 4 weeks of calcimimetic treatment, and at 6 weeks and 6 months after parathyroidectomy. The predictive values of changes during calcimimetic treatment were determined for each test. RESULTS: The study included 110 patients of median age 62 years (91 women). Calcimimetic treatment resulted in normalization of calcium levels and improvements in quality-of-life parameters. The time spent on the timed-stands test was significantly shortened. Eleven of 38 participants with a baseline Montreal Cognitive Assessment score below 26, indicating mild cognitive impairment, reached scores of at least 26 during treatment with calcimimetic. Improvements during treatment with calcimimetic correlated well with postoperative outcomes (positive predictive values 74-96 per cent). CONCLUSION: The method described in this study may be used to aid surgical decision-making for patients with primary hyperparathyroidism and non-disease-specific symptoms by predicting the effects of normalization of hypercalcaemia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".