Use of 3‐hour daily hemodialysis and paricalcitol in patients with severe secondary hyperparathyroidism: A case series
Bibliographic record
Abstract
Patients with poor metabolic control receiving conventional hemodialysis are at risk for developing severe secondary hyperparathyroidism. We postulated that daily hemodialysis may be effective at controlling parathyroid hormone (PTH) in the setting of severe secondary hyperparathyroidism by improving the control of hyperphosphatemia and allowing increased use of vitamin D analogs. We present 5 patients with severe secondary hyperparathyroidism (median iPTH=1783 pg/mL) who were treated with 3-hour daily hemodialysis (3 hours x 6 times a week). Daily hemodialysis, at 1 year, was associated with a 70.4% reduction in median PTH (1783 pg/mL [interquartile range: 1321-1983]-472 pg/mL [334, 704], P<0.001). Additionally, there was an increase in paricalcitol dose from 0 mcg/d to 10.8 (2.00, 11.7) mcg/d, a 39% reduction in calcium x phosphorus product (80.3 +/- 26.8-48.9 +/- 14.0, P<0.01), a 52% reduction in serum phosphorus (9.90 +/- 2.34-4.75 +/- 0.79 mg/dL, P<0.0001), and a 17.6% increase in serum calcium (8.18 +/- 2.04-9.62 +/- 0.93 mg/dL, P<0.01). Three-hour daily hemodialysis with the use of high-dose paricalcitol is associated with improved control of severe secondary hyperparathyroidism.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".