Changes in serum albumin concentrations during transition to dialysis and subsequent risk of peritonitis after peritoneal dialysis initiation: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Evidence shows that lower serum albumin concentrations are associated with the risk of peritoneal dialysis (PD)-related peritonitis. However, little is known regarding its relationship and magnitude of change before PD initiation and peritonitis risk. METHODS: We performed a multicenter retrospective cohort study on 1169 adult cases of PD in Thailand. The associations of serum albumin at concentration (< 2.5, 2.5-3.5, > 3.5 [reference] g/dL) and changes (unchanged + 0.1 to - 0.1 [reference], decrease or increase > 0.1 g/dL) over 3- and 6-month before PD initiation with PD-related peritonitis were examined. Time-to-first and longitudinal rates of peritonitis were examined using the multivariable Cox proportional hazards model and Poisson regression analyses, respectively. RESULTS: At baseline PD initiation, patients with serum albumin concentration < 2.5 and 2.5-3.5 g/dL had an adjusted hazard ratio (HR) of 1.69 and 2.0 times higher peritonitis (vs. > 3.5 g/dL), respectively. Compared to the unchanged group, patients with a decrease and increase in serum albumin concentrations during transitioning to dialysis were significantly associated with higher and lower risk of peritonitis, adjusted HR of 2.25 (95% confidence interval [CI] 1.85-2.75) and 0.53 (95% CI 0.42-0.68) over three-month, and 1.43 (95% CI 1.15-1.79) and 0.64 (95% CI 0.52-0.79) over six-month, respectively. Similar trends of longitudinal rates of serum albumin concentrations and peritonitis risk were observed. CONCLUSIONS: Serum albumin concentrations at PD initiation and its magnitude of change during the transition to dialysis are strongly associated with subsequent risk of peritonitis. Further studies are required on strategies modifying serum albumin concentration during the transition to PD.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".