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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.

canadian journal of kidney health and disease

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