Derivation and Internal Validation of a Clinical Risk Prediction Tool for Hyperkalemia-Related Emergency Department Encounters Among Hemodialysis Patients

• Published in: Canadian journal of kidney health and disease Vol. 7; p. 2054358120953287
• Main Authors: Ronksley, Paul E., Wick, James P., Elliott, Meghan J., Weaver, Robert G., Hemmelgarn, Brenda R., McRae, Andrew, James, Matthew T., Harrison, Tyrone G., MacRae, Jennifer M.
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01-01-2020; Sage Publications Ltd; SAGE Publishing
• Subjects: Calibration; Hemodialysis; Hyperkalemia; Laboratories; Original Clinical Research Quantitative; Patients; hemodialysis; emergency department use; risk prediction; hyperkalemia
• ISSN: 2054-3581; 2054-3581
• DOI: 10.1177/2054358120953287

Background:
Approximately 10% of emergency department (ED) visits among dialysis patients are for conditions that could potentially be managed in outpatient settings, such as hyperkalemia.
Objective:
Using population-based data, we derived and internally validated a risk score to identify hemodialysis patients at increased risk of hyperkalemia-related ED events.
Design:
Retrospective cohort study.
Setting:
Ten in-center hemodialysis sites in southern Alberta, Canada.
Patients:
All maintenance hemodialysis patients (≥18 years) between March 2009 and March 2017.
Measurements:
Predictors of hyperkalemia-related ED events included patient demographics, comorbidities, health-system use, laboratory measurements, and dialysis information. The outcome of interest (hyperkalemia-related ED events) was defined by International Classification of Diseases (10th Revision; ICD-10) codes and/or serum potassium [K+] ≥6 mmol/L.
Methods:
Bootstrapped logistic regression was used to derive and internally validate a model of important predictors of hyperkalemia-related ED events. A point system was created based on regression coefficients. Model discrimination was assessed by an optimism-adjusted C-statistic and calibration by deciles of risk and calibration slope.
Results:
Of the 1533 maintenance hemodialysis patients in our cohort, 331 (21.6%) presented to the ED with 615 hyperkalemia-related ED events. A 9-point scale for risk of a hyperkalemia-related ED event was created with points assigned to 5 strong predictors based on their regression coefficients: ≥1 laboratory measurement of serum K+ ≥6 mmol/L in the prior 6 months (3 points); ≥1 Hemoglobin A1C [HbA1C] measurement ≥8% in the prior 12 months (1 point); mean ultrafiltration of ≥10 mL/kg/h over the preceding 2 weeks (2 points); ≥25 hours of cumulative time dialyzing over the preceding 2 weeks (1 point); and dialysis vintage of ≥2 years (2 points). Model discrimination (C-statistic: 0.75) and calibration were good.
Limitations:
Measures related to health behaviors, social determinants of health, and residual kidney function were not available for inclusion as potential predictors.
Conclusions:
While this tool requires external validation, it may help identify high-risk patients and allow for preventative strategies to avoid unnecessary ED visits and improve patient quality of life.
Trial registration:
Not applicable—observational study design.