Optimizing renin angiotensin inhibitor use in peritoneal dialysis: A single-center Canadian quality improvement study
Bibliographic record
Abstract
BackgroundRenin-angiotensin system inhibitors (RASi) offer important benefits for patients on peritoneal dialysis (PD), particularly in preserving residual kidney function and peritoneal membrane integrity. Despite these benefits, concerns about hyperkalemia and hypotension often limit clinical practice utilization.ObjectivesTo achieve a 20% increase in RASi utilization among eligible patients on PD at an academic hospital in Toronto, Canada through a quality improvement initiative.MethodsWe conducted a pre-intervention analysis through retrospective chart review from July 2022 to September 2023. We implemented a "PD Passport," a clinical documentation tool used by clinic staff in each visit to highlight missed RASi prescription opportunities. The primary outcome measure was RASi utilization at 6-month post-implementation. Process measures included PD passport completion rates, while balancing measures tracked rates of symptomatic hypotension and hyperkalemia.ResultsAmong 63 patients on PD (mean age 58.7 years, 55.6% male), baseline RASi utilization was 41%. Following implementation, RASi utilization increased to 59% by October 2024, representing a 17% increase but falling short of the 20% target. There were no significant differences in mean systolic blood pressure (125.71 ± 4.19, 125.64 ± 7.02 mmHg; p = 0.653), mean serum potassium (4.34 mmol/L, 4.31 mmol/L; p = 0.662), and mean urine output (915.2 mL, 921.8 mL; p = 0.881) before and after the intervention.ConclusionsThe PD Passport initiative substantially increased RASi utilization by 17% without compromising patient safety, as evidenced by stable blood pressure and potassium levels. While falling slightly short of our 20% target, this structured documentation approach effectively bridges the gap between evidence and practice, demonstrating the value of targeted tools in enhancing guideline-concordant care for PD patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".