Marked improvement in bone metabolism parameters after increasing the dialysate calcium concentration from 2.5 to 3 mEq/L in nonhypercalcemic hemodialysis patients
Bibliographic record
Abstract
The optimal dialysate calcium (Ca) concentration for hemodialysis (HD) patients is set at 2.5 mEq/L according to Kidney Disease Outcomes Quality Initiative (K-DOQI) guidelines. This recommendation is opinion-based and could negatively affect secondary hyperparathyroidism. Studies have suggested that a dialysate Ca of 3.0 mEq/L is a compromise between bone protection and cardiovascular risk. The aim of our study was to investigate the effect on bone metabolism parameters after increasing the dialysate Ca concentration from 2.5 to 3.0 mEq/L. The dialysate Ca concentration in our patients was increased from 2.5 to 3.0 mEq/L. Patients with hypercalcemia, normal-high Ca levels with a high Ca-Phosphorus product (Ca x P), excessively suppressed parathyroid hormone (PTH), or a past medical history of calciphylaxis were excluded. Twenty-two patients were studied over 20 weeks. Parathyroid hormone levels decreased significantly (442 +/- 254 vs. 255 +/- 226 pg/mL; p=0.000), without significant changes in serum Ca, P, and Ca x P levels at any sampling point. Better control of secondary hyperparathyroidism allowed us to decrease the paracalcitol dosage in 6 of the 12 patients who had been treated with this drug at the beginning of the study. Other potential factors involved in PTH secretion were not modified. A significant improvement in the rate of patients with 3 or more K-DOQI parameters within the target ranges (8 [36%] vs. 12 [55%]; p=0.026) was observed. In the absence of hypercalcemia or excessively suppressed PTH, an increase from 2.5 mEq to 3.0 mEq/L in dialysate Ca concentration resulted in better control of secondary hyperparathyroidism without affecting Ca, P, and Ca x P levels, thus enabling us to reduce the dosage of vitamin D metabolites.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".