Recent Changes in Therapeutic Approaches and Association with Outcomes among Patients with Secondary Hyperparathyroidism on Chronic Hemodialysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Elevated parathyroid hormone levels may be associated with adverse clinical outcomes in patients on dialysis. After the introduction of practice guidelines suggesting higher parathyroid hormone targets than those previously recommended, changes in parathyroid hormone levels and treatment regimens over time have not been well documented. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Using data from the international Dialysis Outcomes and Practice Patterns Study, trends in parathyroid hormone levels and secondary hyperparathyroidism therapies over the past 15 years and the associations between parathyroid hormone and clinical outcomes are reported; 35,655 participants from the Dialysis Outcomes and Practice Patterns Study phases 1-4 (1996-2011) were included. RESULTS: Median parathyroid hormone increased from phase 1 to phase 4 in all regions except for Japan, where it remained stable. Prescriptions of intravenous vitamin D analogs and cinacalcet increased and parathyroidectomy rates decreased in all regions over time. Compared with 150-300 pg/ml, in adjusted models, all-cause mortality risk was higher for parathyroid hormone=301-450 (hazard ratio, 1.09; 95% confidence interval, 1.01 to 1.18) and >600 pg/ml (hazard ratio, 1.23; 95% confidence interval, 1.12 to 1.34). Parathyroid hormone >600 pg/ml was also associated with higher risk of cardiovascular mortality as well as all-cause and cardiovascular hospitalizations. In a subgroup analysis of 5387 patients not receiving vitamin D analogs or cinacalcet and with no prior parathyroidectomy, very low parathyroid hormone (<50 pg/ml) was associated with mortality (hazard ratio, 1.25; 95% confidence interval, 1.04 to 1.51). CONCLUSIONS: In a large international sample of patients on hemodialysis, parathyroid hormone levels increased in most countries, and secondary hyperparathyroidism treatments changed over time. Very low and very high parathyroid hormone levels were associated with adverse outcomes. In the absence of definitive evidence in support of a specific parathyroid hormone target, there is an urgent need for additional research to inform clinical practice.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".