The Effect of Long Nocturnal Dialysis on Ca/Ph and Bone Status
Bibliographic record
Abstract
Objective: Long nocturnal dialysis (LND) has been advocated as a way to improve dialysis outcomes by improving adequacy. The effect of long dialysis on calcium phosphorus balance and bone mineralism has not been studied. On one hand, a better removal of phosphorus would potentially lead to better control of Ca/Ph balance, but at the other hand, a negative calcium balance might be present during the long dialysis. This study wanted to evaluate the evolution of Ca/Ph, PTH and bone density in a LND program. Methods: Retrospective analysis of prospectively collected data on 12 patients in a LND program. Patientswere dialyzed 3*/week during 8 hours, at a Qb of 175–200 and a Qd of 500, with a dialysate calcium concentraion of 1.5 mmol/l. Serum levels of calcium, phosphorus and iPTH were determined predialysis just before patients started the LND program, and after one year. Dual photon absorption bone densitometry was performed, and measurements expressed as T-values to correct for the natural evolution in the general population. Results: Serum calcium and phosphorus remained stable during LND (4.59 ± 0.47 to 4.73 ± 0.72 mEq/l, p = 0.13 and 4.99 ± 2.05 to 5.35 ± 1.37 mg/dl, p = 0.64, respectively). There was also no difference in iPTh levels (318 ± 312 to 219 ± 135 pg/ml, p = 0.37) or in T-scores of BMD (− 2.35 ± 0.78 to − 1.39 ± 1.41, p = 0.42). Discussion: LND has been advocated as a method to improve dialysis adequacy. The impact on Ca/Ph balance and bone mineralism has however not been studied. In our patient group, there was no evidence for enhanced bone loss during the LND program. Neither was there a tendency for deterioration of the secundary hyperparathyroidism. There was an acceptable control of the phosphorlevels. In conclusion, LND using a 1.5 mmol/l Calcium dialysate does not negatively impact on Ca/Ph balance or on bone density.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".