Review of dialysate calcium concentration in hemodialysis
Bibliographic record
Abstract
The dialysate calcium (Ca) concentration for hemodialysis (HD) patients can be adjusted to manage more optimally the body's Ca and phosphate balance, and thus improve bone metabolism as well as reduce accelerated arteriosclerosis and cardiovascular mortality. The appropriate dialysate Ca concentration allowing this balance should be prescribed to each individual patient depending on a multitude of variable factors relating to Ca load. A lower dialysate Ca concentration of 1.25 to 1.3 mmol/L will permit the use of vitamin D supplements and Ca-based phosphate binders in clinical practice, with much less risk of Ca loading and resultant hypercalcemia and calcification. Low Ca baths are useful in the setting of adynamic bone disease where an increase in bone turnover is required. However, low Ca levels in the dialysate may also predispose to cardiac arrhythmias and hemodynamically unstable dialysis sessions with intradialytic hypotension. Higher Ca dialysate is useful to sustain normal serum Ca levels where patients are not taking Ca-based binders or if Ca supplements are not able to normalize serum levels. Suppression of hyperparathyroidism is also effective with dialysate Ca of 1.75 mmol/L, but hypercalcemia, metastatic calcification, and oversuppression of parathyroid hormone are risks. Dialysate Ca of 1.5 mmol/L may be a compromise between bone protection and reduction in cardiovascular risk for conventional HD and is a common concentration used throughout the world. The increase in longer, more frequent dialysis such as short-daily and nocturnal HD, however, provides another challenge with regard to optimal dialysate Ca levels and higher levels of 1.75 mmol/L are probably indicated in this setting. Difficulties in determining the ideal dialysate Ca occur because of the complex pathophysiology of bone and mineral metabolism in HD patients and there needs to be a balance between dialysis prescription and other treatment modalities. To optimize management of the abnormal Ca balance, other aspects of this disorder need to be more fully clarified and, with evolving medications for phosphate control and treatment of secondary hyperparathyroidism, as well as the emergence of a multitude of different HD regimes, further studies are required to make definitive recommendations. At present, we need to maintain flexibility with HD treatments and so dialysate Ca needs to be individualized to meet the specific requirements of patients by optimizing management of renal bone disease and simultaneously reducing metastatic calcification and cardiovascular disease.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".