Quantification and classification of potassium and calcium disorders with the electrocardiogram: What do clinical studies, modeling, and reconstruction tell us?

Diseases caused by alterations of ionic concentrations are frequently observed challenges and play an important role in clinical practice. The clinically established method for the diagnosis of electrolyte concentration imbalance is blood tests. A rapid and non-invasive point-of-care method is yet needed. The electrocardiogram (ECG) could meet this need and becomes an established diagnostic tool allowing home monitoring of the electrolyte concentration also by wearable devices. In this review, we present the current state of potassium and calcium concentration monitoring using the ECG and summarize results from previous work. Selected clinical studies are presented, supporting or questioning the use of the ECG for the monitoring of electrolyte concentration imbalances. Differences in the findings from automatic monitoring studies are discussed, and current studies utilizing machine learning are presented demonstrating the potential of the deep learning approach. Furthermore, we demonstrate the potential of computational modeling approaches to gain insight into the mechanisms of relevant clinical findings and as a tool to obtain synthetic data for methodical improvements in monitoring approaches.

Optimal EPO dosing in hemodialysis patients using a non-linear model predictive control approach

Anemia management with erythropoiesis stimulating agents is a challenging task in hemodialysis patients since their response to treatment varies highly. In general, it is difficult to achieve and maintain the predefined hemoglobin (Hgb) target levels in clinical practice. The aim of this study is to develop a fully personalizable controller scheme to stabilize Hgb levels within a narrow target window while keeping drug doses low to mitigate side effects. First in-silico results of this framework are presented in this paper. Based on a model of erythropoiesis we formulate a non-linear model predictive control (NMPC) algorithm for the individualized optimization of epoetin alfa (EPO) doses. Previous to this work, model parameters were estimated for individual patients using clinical data. The optimal control problem is formulated for a continuous drug administration. This is currently a hypothetical form of drug administration for EPO as it would require a programmable EPO pump similar to insulin pumps used to treat patients with diabetes mellitus. In each step of the NMPC method the open-loop problem is solved with a projected quasi-Newton method. The controller is successfully tested in-silico on several patient parameter sets. An appropriate control is feasible in the tested patients under the assumption that the controlled quantity is measured regularly and that continuous EPO administration is adjusted on a daily, weekly or monthly basis. Further, the controller satisfactorily handles the following challenging problems in simulations: bleedings, missed administrations and dosing errors.

The Impact of Visceral Mass on Survival in Chronic Hemodialysis Patients

In chronic hemodialysis, patient survival is positively correlated with body weight and body mass index (BMI). This relationship extends even to obese patients with a BMI >30 kg/m. We have put forward the hypothesis that this survival benefit may be due to a lower average synthesis rate of uremic toxins (expressed as amount per time per unit of body weight) in larger patients, because the relative contribution of the high metabolic rate organs (HMRO) to body weight in these patients is lower and HMRO are most likely to be the prime source of uremic toxins. In addition, the average uremic toxin concentration in larger patients may be lower because of the larger distribution volume. Based on these assumptions, a better survival in patients with a lower HMRO to body weight fraction (HMRO%BW) can be predicted.

To test this hypothesis we estimated gender- and race-specific HMRO mass by means of recently published regression models in 2,004 incident hemodialysis patients. Cox proportional hazards models were used to assess the association between age, serum albumin concentration, eKt/V, and HMRO%BW and mortality. High HMRO%BW was significantly associated with increased mortality (hazard ratio 1.323 [95% CI: 1.186 to 1.477]). Mean survival time was longest in the low HMRO%BW tertile (1,031 days [95%CI: 974 to 1,087]), 935 days [95%CI: 886 to 984] in the middle, and 876 days [95%CI: 825 to 926] in the high HMRO%BW tertile (p<0.0001; log rank test).

These results support the hypothesis predicting that a low HMRO mass per unit of weight confers a beneficial effect on survival.