Severe Hyperparathyroidism Despite Paricalcitol (Zemplar) Therapy: One Year Follow-up
Bibliographic record
Abstract
Paricalcitol, a new Vit. D analogue is thought to be more potent than Calcitriol and has also been reported to cause less hypercalcemia. We report one-year follow-up on patients (N = 74) from one inner city dialysis unit. Patients were stratified in groups A, B, C, D depending on intact Paratharmone (iPTH) levels i.e., < 100, 100–300, 300–600, > 600 respectively. Serum Ca, PO4, alkaline phosphatase (ALK), albumin (ALB), hemoglobin (Hb) was measured monthly and serum iPTH was checked quarterly. The results are as follows: Group # PTH Ca PO4 ZPR Hb EPO pg/dl mg/dl mg/dl mcg/hd g/dl U/kg/hd A 6 56.83* 9.74 5.32 0 11.72 255.8† B 22 197.01** 9.04 5.53 2.48¶ 12.12 137.55 C 29 422.89** 9.4 5.73 4.54¶¶ 11.86 128.87 D 17 1253.4** 9.88 7.21 12.51¶¶ 12.1 74.35†† PTH: p < 0.05 = *vs**, ZPR(zemplar): p < 0.05¶ vs¶¶, mcg: microgram EPO(erythropoietin): p < 0.05 = † vs††, Mean age, weight, URR, ALB., ALK. and iron indices were not statistically different in all groups. Mean duration of hemodialysis (HD) was 34, 30, 57 & 65 months in groups A, B, C, D respectively. None of these patients had symptomatic bone disease. Seven patients were changed to low Ca (1.0 meq/L) bath secondary to hypercalcemia (Ca > 11.5) & severe hyperparathyroidism (HPT). This data suggest that severe HPT is frequent despite aggressive Paricalcitol therapy in the inner city HD population. More effective noncalcium phosphate binders and/or calcimimetic agents may be needed in addition to dietary and medication compliance in group D to control severe HPT. Interestingly patients with low PTH (< 100) showed relative epogen resistance while patients in group D required smaller epogen doses. There was inverse relationship between ZPR & EPO dosage. The effect of ZPR on EPO responsiveness needs to be confirmed in larger study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".