Factors Associated with Initiation of Chronic Renal Replacement Therapy for Patients with Kidney Failure
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Patients with kidney failure sometimes do not receive chronic renal replacement therapy (RRT), even though this may reduce their life expectancy. This study aimed to identify factors associated with initiation of chronic RRT. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This cohort study was conducted with Albertans aged >18 years between May 2002 and March 2009, using linked data from the provincial renal programs, clinical laboratories, and provincial health ministry. This study focused on those who developed kidney failure, defined by an estimated GFR (eGFR) <15 ml/min per 1.73 m(2) at last measurement during follow-up, together with prior CKD (eGFR <60 ml/min per 1.73 m(2) at least 90 days earlier). Multivariable Cox proportional hazards models were used to determine factors significantly associated with initiation of chronic RRT. RESULTS: In total, 7901 participants had eGFR <15 ml/min per 1.73 m(2) at last measurement. After adjustment, older participants were less likely to initiate chronic RRT. Remote residence location, dementia, and metastatic cancer also decreased the likelihood of initiating RRT. The cumulative probability of initiating RRT during follow-up was 76.8% for urban-dwelling men aged <50 years without comorbidity, but was only 3.2% among remote-dwelling women aged ≥70 years with dementia and metastatic cancer. In contrast, patients with diabetes and heavy/severe proteinuria were more likely to initiate chronic RRT. CONCLUSIONS: There is substantial variability in the likelihood of RRT initiation for patients with eGFR <15 ml/min per 1.73 m(2). Further studies are needed to delineate factors that influence this outcome.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".