International Variations in Serum PTH and Calcium Levels and Their Mortality Associations in Peritoneal Dialysis Patients: Results from PDOPPS
Bibliographic record
Abstract
Background: Mineral bone disorder (MBD) in chronic kidney disease (CKD) is associated with high symptom burden, fractures, vascular calcification, cardiovascular disease, and increased morbidity and mortality. CKD-MBD studies have been limited in peritoneal dialysis (PD) patients. Here, we describe calcium and parathyroid hormone (PTH) control, and mortality associations in PD patients. Methods: We used data from 8 countries [Australia and New Zealand (A/NZ), Canada, Japan, Thailand, South Korea, United Kingdom, United States (US)] participating in the Peritoneal Dialysis Outcomes and Practice Patterns Study (PDOPPS; 2014-2022) among patients receiving PD for >3 months. We analyzed the association of baseline PTH and albumin-adjusted calcium (calciumAlb) with all-cause mortality using Cox regression, adjusted for potential confounders. Results: Mean age ranged from 54.6 yrs in South Korea to 63.5 yrs in Japan. PTH and serum calciumAlb were measured at baseline in 12,642 and 14,244 patients, respectively. Median PTH ranged from 161 (Japan) to 363 pg/mL (US); mean calciumAlb ranged from 9.1 (South Korea, US) to 9.8 mg/dL (A/NZ). The PTH/mortality relationship was U-shaped with lowest risk at PTH 300-599 pg/mL. Mortality was nearly 20% higher at serum calciumAlb 9.6+ mg/dL vs 8.4-<9.6 mg/dL. Conclusions: A large proportion of PD patients in this multi-national study have Ca and/or PTH levels in ranges associated with substantially higher mortality. These observations point to the need to substantially improve MBD management in PD to optimize patient outcomes. Funding: Commercial Support - Global support for the ongoing DOPPS Programs is provided without restriction on publications by a variety of funders. For details see https://www.dopps.org/AboutUs/Support.aspx.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".