Clinical parameters before and after the transition to dialysis
Bibliographic record
Abstract
INTRODUCTION: The transition from pre-dialysis chronic kidney disease (CKD) to post-dialysis start is a critical period associated with high patient mortality and increased hospital admissions. Little is known about the trends of key clinical and laboratory parameters through this time of transition to start dialysis. METHODS: De-identified data including demographics, vital signs, lab results, and eGFR from the Fresenius Medical Care-CKD Registry were analyzed to determine trends in clinical and laboratory parameters through the time of transition from 12 months pre-dialysis start to 12 months post-dialysis start. Trends in key clinical and laboratory parameters associated with cardiovascular, nutritional, mineral metabolism and inflammatory domains were examined in association with the transition to dialysis start and first year dialysis survival. FINDINGS: All parameters show divergence for patients who survive vs. do not survive the first year of dialysis. Of note, during pre-dialysis CKD the absolute systolic blood pressure (SBP) level is lower and the slope for SBP decline is significantly steeper for patients who do not survive the first year on dialysis. DISCUSSION: This study uniquely demonstrates the trajectories of key parameters though the transition from pre-dialysis to post-dialysis start. Significant differences are noted in the pre-dialysis period for patients who survive vs. those who do not survive the first year of dialysis. Early recognition of adverse trends in the pre-dialysis period may create opportunity to intervene to improve early dialysis 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".