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Assessing the relationship between serum potassium variability and the risk of hyperkalaemia and adverse clinical outcomes

Session Risk Factors and Prevention ePosters

Speaker Professor Phil Mc Ewan

Event : ESC Congress 2020

  • Topic : preventive cardiology
  • Sub-topic : Epidemiology
  • Session type : e-posters

Authors : P Mc Ewan (Cardiff,GB), K Badora (Cardiff,GB), D Sugrue (Cardiff,GB), G James (Cambridge,GB), M Hurst (Cardiff,GB), L Hoskin (Cardiff,GB), E Tafesse (Gaithersburg,US)

P Mc Ewan1 , K Badora1 , D Sugrue1 , G James2 , M Hurst1 , L Hoskin1 , E Tafesse3 , 1Health Economics and Outcomes Research Ltd - Cardiff - United Kingdom of Great Britain & Northern Ireland , 2AstraZeneca, Global Medical Affairs - Cambridge - United Kingdom of Great Britain & Northern Ireland , 3AstraZeneca, Global Health Economics - Gaithersburg - United States of America ,

Risk Factors and Prevention – Epidemiology

Background: Serum potassium (SK+) is a vital electrolyte, which level is maintained by adjusting renal K+ excretion. Variability in SK+ has been linked to increased risk of mortality and other adverse clinical events in patients in intensive care and/or receiving haemodialysis, prompting a similar investigation in cardiovascular patients.

Purpose: To examine the effect of SK+ variability on all-cause mortality (ACM) and the incidence of major adverse cardiovascular events (MACE), comprising arrhythmia, [subsequent records of] HF, myocardial infarction, or stroke, in patients with heart failure (HF) or resistant hypertension (RHTN).

Methods: Patients aged =18 years with HF or RHTN were identified from the UK Clinical Practice Research Datalink (CPRD, primary care data) and linked Hospital Episode Statistics (HES, secondary care data). HF and RHTN were defined through READ codes recorded during the study period (2008-June 2018) or the five-year look-back period (2003–2007). Index date was set to 1st January 2008 or initial diagnosis; whichever occurred later. Mean SK+ and variability of measurements (quantified as standard deviation [SD] and each patient categorised as low or highly variable based on the median SD of the cohort), and crude incidence rates of ACM and MACE were estimated over a follow-up period from index date to event or end of follow-up (death, loss to follow-up or end of study, whichever was earlier).

Results: The eligible population included 317,135 RHTN patients and 84,210 HF patients with a mean follow-up of 6.37 (SD 3.06) and 5.01 (SD 3.20) years, respectively. In both cohorts, higher mean SK+ = 5.0 mmol/L was associated with increased rates of ACM and MACE relative to a mean SK+ of 3.5–5 mmol/L (Table 1). High SK+ variability was associated with increased incidence of adverse outcomes, with rates consistently higher in the high SK+ variability group compared to low-variability patients with the same diagnosis and mean SK+ category (Table 1); all comparisons were statistically significant except for ACM in HF patients with mean SK+ =5 mmol/L.

Conclusion: Independently of mean SK+, increased variability in SK+ levels was associated with an increased rate of mortality and MACE in patients with RHTN or HF. Careful SK+ monitoring and management to maintain SK+ concentrations may improve the outcomes of patients with RHTN and HF.

Cohort Mean SK+

SK+ Variability


Crude incidence rate per 1,000 patient-years

(95% CI)

Crude incidence rate per 1,000 patient-years

(95% CI)

3.5-5 mmol/L

≥ 5.0 mmol/L









95.03 (93.14-96.95)

116.07 (114.04-118.13)

136.04 (129.38-142.95)

143.38 (136.94-150.05





340.27 (336.68-343.88)

450.84 (446.82-454.88)

354.7 (343.9-365.76)

432.77 (421.52-444.25)


3.5-5 mmol/L

≥ 5.0 mmol/L









24.52 (24.17-24.88)

34.25 (33.85-34.65)

51.62 (49.7-53.58)

59.56 (57.59-61.58)





61.12 (60.56-61.68)

101.66 (100.97-102.35)

85.53 (83.06-88.05)

119.69 (116.89-122.53)

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