An Evaluation of the Prevalence of Hypokalemia and Hypomagnesemia in the VGH and BC Wide PeritonealDialysis Population and Frequency and Cost of Prescription of Potassium and Magnesium Supplements
Bibliographic record
Abstract
Background: Potassium and magnesium are minerals essential in the functioning of the human body, and low levels of either may adversely affect normal neuromuscular, cardiovascular, and metabolic processes. Peritoneal dialysis (PD) patients are at increased risk for hypokalemia and hypomagnesemia due to continuous loss of these minerals via dialysate dwells. There is no current funding for potassium or magnesium supplements through the BC Provincial Renal Agency (BC PRA); thus, expanding BC PRA formulary coverage to include these supplements may increase accessibility and affordability, and improve PD patient outcomes.Objectives:To determine the one-year prevalence rate of hypokalemia and hypomagnesemia, and to assess the one-year frequency and cost of prescription of potassium and magnesium supplements in the Vancouver General Hospital (VGH) and BC wide PD patient population. Methods:This was a multi-center, retrospective review utilizing the Patient Records and Outcome Management Information System (PROMIS) database. All BC patients on PD at any point between May 1, 2017 to April 30, 2018 were included. Hypokalemia was defined as K < 3.5 mmol/L and hypomagnesemia was defined as Mg < 0.7 mmol/L. Yearly cost estimates of potassium and magnesium supplementation were based on unit costs and dispensing fees provided by MacDonaldu2019s Renal Pharmacy and Laurel Prescriptions.Results:For all PD patients in BC (n=1217), 97.5% of patients had serum potassium levels checked at least every 3 months; however, the frequency of serum magnesium level monitoring was much lower at 58.3% of patients. The prevalence of hypokalemia was 45.6% with 25.5% of patients on potassium supplements, and the prevalence of hypomagnesemia was 27.5% with 4.1% of patients on magnesium supplements. The one-year cost estimates for potassium and magnesium supplementation for all BC PD patients were $15,110 and $2,209, respectively. The prevalence of hypokalemia and hypomagnesemia were higher than the actual prescription of potassium and magnesium supplements, respectively. Cost may present as a barrier, even in patients with private health insurance. Compared to other nutritional supplements and hyperkalemia exchange resins listed on the BC PRA formulary, potassium and magnesium supplements have similar or lower costs. Conclusion:We would propose that potassium and magnesium supplements be added to the BC Provincial Renal Agency dialysis formulary for improved PD patient outcomes.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.008 |
| Open science | 0.002 | 0.002 |
| 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 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".