Comparative Mortality–Predictability Using Alkaline Phosphatase and Parathyroid Hormone in Patients on Peritoneal Dialysis and Hemodialysis
Bibliographic record
Abstract
BACKGROUND: In hemodialysis (HD) patients, serum alkaline phosphatase (ALP) and parathyroid hormone (PTH) derangements are associated with mortality, but outcome-predictability using ALP and PTH in peritoneal dialysis (PD) patients remains uncertain. METHODS: In a cohort of 9244 adult PD patients from a large national dialysis organization (entry period 2001 - 2006, with follow-up through 2009), we used multivariable Cox models adjusted for case-mix and laboratory covariates to examine the associations of time-averaged ALP and PTH with all-cause mortality. We then compared mortality-predictability using ALP and PTH in 9244 PD and 99 323 HD patients. RESULTS: In PD patients, ALP concentrations exceeding 150 U/L were associated with increased mortality (reference ALP: 70 to <90 U/L). Hazard ratios (HRs) and 95% confidence intervals (CIs) were 1.18 (1.03 to 1.36), 1.27 (1.08 to 1.50), 1.49 (1.23 to 1.79), and 1.35 (1.19 to 1.53) for ALP concentrations of 150 to <170 U/L, 170 to <190 U/L, 190 to <210 U/L, and ≥210 U/L respectively. In contrast, we observed a U-shaped association between PTH concentration and death risk in PD patients, with PTH concentrations of less than 200 pg/mL and 700 pg/mL or more associated with increased mortality (reference PTH: 200 to <300 pg/mL). Hazard ratios and 95% CIs were 1.25 (1.12 to 1.41), 1.12 (1.02 to 1.23), 1.06 (0.96 to 1.18), 1.09 (0.97 to 1.24), 1.12 (0.97 to 1.29), 1.18 (0.99 to 1.40), and 1.23 (1.09 to 1.38) for PTH concentrations of <100 pg/mL, 100 to <200 pg/mL, 300 to <400 pg/mL, 400 to <500 pg/mL, 500 to <600 pg/mL, 600 to <700 pg/mL, and ≥700 pg/mL respectively. Compared with PD patients having serum concentrations of ALP and PTH within reference ranges, patients on HD experienced increased mortality across all ALP and PTH concentrations, particularly those in the lowest and highest categories. CONCLUSIONS: In summary, higher ALP concentrations are associated with increased mortality, and lower and higher PTH concentrations are both associated with death risk in PD patients. The utility of ALP in the management of chronic kidney disease mineral bone disorders in PD patients warrants further 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".