Mineral and bone disorders and survival in hemodialysis patients with and without polycystic kidney disease
Bibliographic record
Abstract
BACKGROUND: Maintenance hemodialysis (MHD) patients with polycystic kidney disease (PKD) have better survival than non-PKD patients. Mineral and bone disorders (MBD) are associated with accelerated atherosclerosis and cardiovascular death in MHD patients. It is unknown whether the different MBD mortality association between MHD populations with and without PKD can explain the survival differential. METHODS: Survival models were examined to assess the association between different laboratory markers of MBD [such as serum phosphorous, parathyroid hormone (PTH), calcium and alkaline phosphatase] and mortality in a 6-year cohort of 60,089 non-PKD and 1501 PKD MHD patients. RESULTS: PKD and non-PKD patients were 57±13 and 62±15 years old and included 46 and 45% women and 14 and 32% Blacks, respectively. Whereas PKD individuals with PTH 150 to <300 pg/mL (reference) had the lowest risk for mortality, the death risk was higher in patients with PTH<150 [hazard ratio (HR): 2.16 (95% confidence interval 1.53-3.06)], 300 to <600 [HR: 1.30 (0.97-1.74)] and ≥600 pg/mL [HR: 1.46 (1.02-2.08)], respectively. Similar patterns were found in non-PKD patients. Fully adjusted death HRs of time-averaged serum phosphorous increments<3.5, 5.5 to <7.5 and ≥7.5 mg/dL (reference: 3.5 to <5.5 mg/dL) for PKD patients were 2.82 (1.50-5.29), 1.40 (1.12-1.75) and 2.25 (1.57-3.22). The associations of alkaline phosphatase and calcium with mortality were similar in PKD and non-PKD patients. CONCLUSION: Bone-mineral disorder markers exhibit similar mortality trends between PKD and non-PKD MHD patients, although some differences are observed in particular in low PTH and phosphorus ranges.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".