Biochemical Effects of High Dialysate Calcium in Hemodialysis Patients with Hyperparathyroidism: A 10 Month Study
Bibliographic record
Abstract
In the past 15 years, there has been a trend to decrease dialysate calcium concentrations to prevent hypercalcemia. However, low dialysate calcium can provoke hyperparathyroidism. The time course of the effect of increasing dialysate calcium is not well characterized, and the effect on calcium-phosphate product is unclear. Therefore, we studied the effect of increasing dialysate calcium from 1.5 to 1.75 mM in 21 stable patients on hemodialysis who had serum phosphate of less than 2 mM and serum calcium of less than 2.4 mM. Over 10 months, parathyroid hormone levels fell from 39.6 to 16.6 pM (p < 0.0001), whereas serum calcium increased from 2.27 to 2.41 mM. There were no significant changes in serum phosphate or the calcium-phosphate product. Three patients became hypercalcemic when their parathyroid hormone levels were suppressed to less than 10 pM. We conclude that in carefully selected patients, increasing dialysate calcium can safely treat hyperparathyroidism with minimal risk of complications. This treatment has the advantage over the use of vitamin D therapy of being less expensive, independent of patient compliance, and less likely to cause increases in serum phosphate or calcium-phosphate product.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".