Optimal Control of Phosphatemia by Short Daily Hemodialysis
Bibliographic record
Abstract
Hyperphosphatemia is a major risk factor in maintenance of hemodialysis patients, not only in the pathogenesis of secondary hyperparathyroidism but also in the progressive calcic vascular disease. Phosphorus is present in all nutrients rich in proteins and we can’t remove completely phosphorus intake by diet restriction or phosphate binders. Better nutritional status with higher protein intake appears with short daily hemodialysis (SDHD). Does SDHD allow a better phosphorus elimination than SHD? Ten patients mean age 52.3 ± 6.4 yrs treated on standard hemodialysis (SHD) from 11.2 ± 4.3 yrs 4 to 5 h × 3/week were switched to SDHD 2 to 2.5 h × 6/week. We have compared in the same patient phosphatemia (P), weekly phosphates removal (WPR), daily phosphates intake (DPI), and phosphates binders in SHD and in SDHD at the third month (SDHD1) and at long term (SDHD2). Results were expressed as mean ± SD and statistical analysis between SHD and SDHD were studied using Students paired t-test. SHD SDHD1 SDHD2 P (mmol/l) 2.3 ± 0.7 1.9 ± 0.5** 1.8 ± 0.4** WPR (mmol) 99.8 ± 20.8 113.5 ± 25.8* 128.2 ± 45.8* DPI (mg) 968 ± 192 1149 ± 223** 1535 ± 701* P binders +++ ++ ++ * p < 0.05 ** p < 0.001 P was significantly lower in SDHD despite a reduction in phosphates binders and high phosphates intake with better nutritional status as seen usually with SDHD. There were no significant differences between either P and DPI in the two periods on SDHD. We have confirmed these results by kinetics studies showing that 60% of phosphate elimination take place mainly during the first 2 h of dialysis sessions; so the overall WPR is higher with SDHD. We conclude that increased sessions frequency increases phosphates elimination and decreases the risk of hyperphosphatemia.
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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) | 0.000 | 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".