Association of single and serial measures of serum phosphorus with adverse outcomes in patients on peritoneal dialysis: results from the international PDOPPS
Bibliographic record
Abstract
BACKGROUND: While high serum phosphorus levels have been related to adverse outcomes in hemodialysis patients, further investigation is warranted in persons receiving peritoneal dialysis (PD). METHODS: Longitudinal data (2014-17) from the Peritoneal Dialysis Outcomes and Practice Patterns Study (PDOPPS), a prospective cohort study, were used to examine associations of serum phosphorus with all-cause mortality and major adverse cardiovascular events via Cox regression adjusted for confounders. Serum phosphorus levels were parameterized by four methods: (i) baseline serum phosphorus; (ii) mean 6-month serum phosphorus; (iii) number of months with serum phosphorus >4.5 mg/dL; and (iv) mean area-under-the-curve of 6-month serum phosphorus control. RESULTS: The study included 5847 PD patients from seven countries; 9% of patients had baseline serum phosphorus <3.5 mg/dL, 24% had serum phosphorus ≥3.5 to ≤4.5 mg/dL, 30% had serum phosphorus >4.5 to <5.5 mg/dL, 20% had serum phosphorus ≥5.5 to <6.5 mg/dL, and 17% had serum phosphorus ≥6.5 mg/dL. Compared with patients with baseline serum phosphorus ≥3.5 to ≤4.5 mg/dL, the adjusted all-cause mortality hazard ratio (HR) was 1.19 (0.92,1.53) for patients with baseline serum phosphorus ≥5.5 to <6.5 mg/dL and HR was 1.53 (1.14,2.05) for serum phosphorus ≥6.5 mg/dL. Associations between serum phosphorus measurements over 6 months and clinical outcomes were even stronger than for a single measurement. CONCLUSIONS: Serum phosphorus >5.5 mg/dL was highly prevalent (37%) in PD patients, and higher serum phosphorus levels were a strong predictor of morbidity and death, particularly when considering serial phosphorus measurements. This highlights the need for improved treatment strategies in this population. Serial serum phosphorus measurements should be considered when assessing patients' risks of adverse outcomes.
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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 | 0.003 | 0.005 |
| 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 | 0.001 |
| 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".