Determinants of Hyperkalemia Progression Among Patients with Mild Hyperkalemia

Real-World Application of a Quantitative Systems Pharmacology (QSP) Model to Predict Potassium Concentrations from Electronic Health Records: A Pilot Case towards Prescribing Monitoring of Spironolactone

Quantitative systems pharmacology (QSP) models are rarely applied prospectively for decision-making in clinical practice. We therefore aimed to operationalize a QSP model for potas-sium homeostasis to predict potassium trajectories based on spironolactone administrations. For this purpose, we proposed a general workflow that was applied to electronic health records (EHR) from patients treated in a German tertiary care hospital. The workflow steps included model exploration, local and global sensitivity analyses (SA), identifiability analysis (IA) of model parameters, and specification of their inter-individual variability (IIV). Patient covariates, selected parameters, and IIV then defined prior information for the Bayesian a posteriori prediction of individual potassium trajectories of the following day. Following these steps, the successfully operationalized QSP model was interactively explored via a Shiny app. SA and IA yielded five influential and estimable parameters (extracellular fluid volume, hyperaldosteronism, mineral corticoid receptor abundance, potassium intake, sodium intake) for Bayesian prediction. The operationalized model was validated in nine pilot patients and showed satisfactory performance based on the (absolute) average fold error. This provides proof-of-principle for a Prescribing Monitoring of potassium concentrations in a hospital system, which could suggest preemptive clinical measures and therefore potentially avoid dangerous hyperkalemia or hypokalemia.

A quantitative systems pharmacology model of plasma potassium regulation by the kidney and aldosterone

Plasma potassium regulation within a narrow range is vital for life. The risk for hyperkalemia increases when kidney function is impaired and with therapeutic interventions such as mineralocorticoid receptor antagonists (MRAs). The kidney maintains potassium homeostasis by matching potassium intake and excretion, in part through the action of aldosterone. A mechanistic mathematical model was developed and used to investigate the effect of renal impairment and MRAs on plasma potassium levels. The model describes renal potassium filtration, reabsorption, and secretion along the nephron; potassium-aldosterone regulatory feedbacks; whole body potassium balance; and the pharmacologic effects of MRAs. The model was calibrated by fitting (1) the plasma potassium and aldosterone response to potassium infusion in humans on high/low potassium diets, and (2) the acute potassium excretion response to spironolactone. The model was validated by predicting steady-state plasma potassium with sustained spironolactone treatment in hyperaldosteronism patients. The model was then used to demonstrate that (1) declining renal function alone has a small effect on plasma potassium for GFR > 30 ml/min, but an increasing effect as GFR approaches end stage renal disease (GFR ~ 15 ml/min) (2) the effect of increasing potassium intake has minimal effect at normal GFRs but increasing effect on plasma potassium as GFR declines, and 3) MRAs have a minor effect on plasma potassium when GFR is normal, but cause larger increases as GFR falls below 60 ml/min. This model provides a quantitative framework for investigating integrated impacts of diseases and therapies in this complex system.