Trends in the Management of Patients With Kidney Failure in Alberta, Canada (2004-2013)
Bibliographic record
Abstract
Background: Based on clinical practice guidelines, specific quality indicators are examined to assess the performance of a health care system for patients with end-stage renal disease (ESRD). We examined trends in the proportion of patients with ESRD referred late to nephrology, timing of dialysis initiation in those with chronic kidney disease, and proportion of patients with ESRD treated with pre-emptive kidney transplantation or peritoneal dialysis (PD). Design: This was a retrospective cohort study. Setting: The study was conducted in Alberta, Canada. Patients: Alberta residents aged 18 years or older with incident ESRD requiring renal replacement therapy between 2004 and 2013 were included. Measurements: Descriptive statistics, and log binomial and linear regression models were used for analysis. Methods: We determined the proportion of patients with ESRD who did not see a nephrologist within 90 days prior to starting dialysis (late referrals) and those who were receiving PD 90 days after dialysis initiation. Among those who had been seen by a nephrologist for at least 90 days, we also assessed the proportion who initiated dialysis with estimated glomerular filtration rate (eGFR) higher than or equal to 10.5 mL/min/1.73 m 2 , and underwent a pre-emptive transplant. Results: Our cohort included 5343 patients (mean age 61.8 years, 61.2% male). Over a 10-year period, there was a decrease in the proportion of late referrals (26.4% to 21.1%, P = .001). We also noted a decrease in the proportion of dialysis initiation with eGFR higher than or equal to 10.5 mL/min/1.73 m 2 (21.2% to 14.7%, P < .001), with a significant increase in the proportion of patients initiating dialysis as an inpatient (38.8% to 45.2%, P = .001). There was a non-significant decrease in both the proportion of patients treated with a pre-emptive transplant and PD at 90 days over the 10-year period. Limitations: The use of administrative data restricted the availability of clinical data regarding underlying circumstances of each quality indicator, including patient symptoms, indications for dialysis initiation, and PD eligibility. Conclusions: We noted improvement in late referrals and early dialysis initiation over time. However, we also noted low and stable use of pre-emptive kidney transplantation and PD at 90 days, which warrants further exploration. These findings support the need for quality improvement initiatives designed to address these gaps in care and improve outcomes for patients with kidney failure.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".