BMC Nephrology (Jan 2019)

The value of maintaining normokalaemia and enabling RAASi therapy in chronic kidney disease

  • Marc Evans,
  • Eirini Palaka,
  • Hans Furuland,
  • Hayley Bennett,
  • Cecilia Linde,
  • Lei Qin,
  • Phil McEwan,
  • Ameet Bakhai

DOI
https://doi.org/10.1186/s12882-019-1228-y
Journal volume & issue
Vol. 20, no. 1
pp. 1 – 11

Abstract

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Abstract Background People with chronic kidney disease (CKD) are at an increased risk of developing hyperkalaemia due to their declining kidney function. In addition, these patients are often required to reduce or discontinue guideline-recommended renin-angiotensin-aldosterone system inhibitor (RAASi) therapy due to increased risk of hyperkalaemia. This original research developed a model to quantify the health and economic benefits of maintaining normokalaemia and enabling optimal RAASi therapy in patients with CKD. Methods A patient-level simulation model was designed to fully characterise the natural history of CKD over a lifetime horizon, and predict the associations between serum potassium levels, RAASi use and long-term outcomes based on published literature. The clinical and economic benefits of maintaining sustained potassium levels and therefore avoiding RAASi discontinuation in CKD patients were demonstrated using illustrative, sensitivity and scenario analyses. Results Internal and external validation exercises confirmed the predictive capability of the model. Sustained potassium management and ongoing RAASi therapy were associated with longer life expectancy (+ 2.36 years), delayed onset of end stage renal disease (+ 5.4 years), quality-adjusted life-year gains (+ 1.02 QALYs), cost savings (£3135) and associated net monetary benefit (£23,446 at £20,000 per QALY gained) compared to an absence of RAASi to prevent hyperkalaemia. Conclusion This model represents a novel approach to predicting the long-term benefits of maintaining normokalaemia and enabling optimal RAASi therapy in patients with CKD, irrespective of the strategy used to achieve this target, which may support decision making in healthcare.

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