There is a lack of evidence for clear recommendations on potassium management in critically ill patients. We observed lowest mortality (3.7%) in ICU patients with a mean potassium range between > 3.5 and 4.0 mmol/l and low potassium variability. In-hospital mortality increased significantly for lower and higher potassium ranges including the normokalaemic range (3.5–5.0 mmol/l). More obvious, an increased potassium variability indicated by increased potassium concentration standard deviation or coefficient of variation during hospital stay is associated with an increased in-hospital mortality. In addition, we found an increased in-hospital mortality risk in ICU patients receiving potassium supplementation.
Our findings are in line with results of a recent systematic review, investigating the association of potassium concentration with mortality and occurrence of ventricular arrhythmias in patients after myocardial infarction in 12 studies. In those cardiac risk patients, they found an increased mortality risk when potassium concentrations were above 4.5 mmol/l [12]. In agreement, in patients with atrial fibrillation, we observed the lowest mortality when mean potassium was > 3.5–4.0 mmol/l. The few previous studies investigated the association between potassium ranges, variability and mortality in ICU patients reported a J- and U-shaped association between potassium and mortality [5, 13]. However, their classification lacked to define a tight potassium range with the lowest mortality. Our findings are in line with results reported by Hessels et al. and Uijtendaal et al. who showed that potassium variability was independently associated with outcome [5, 13]. McMahon et al. [6] investigated potassium concentrations at initiation of critical care in a comparable large ICU patient cohort. They stressed the importance of tight potassium regulation, as potassium concentrations between 4.5 and 5.5 mmol/l were associated with an increase in mortality risk. Unfortunately, they excluded patients with serum potassium concentrations < 4.0 mmol/l, which was in our analysis identified as the group with the lowest mortality. Unexpectedly, in our patient cohort, in-hospital mortality was significantly lower even in patients with mild hypokalaemic concentrations (3.0–3.5 mmol/l) as compared to 4.0–4.5 mmol/l. Contrary, in patients after myocardial infarction, potassium concentrations < 3.5 mmol/l were associated with an increased risk of ventricular arrhythmias [12].
Potassium supplementation in critically ill patients is usually performed intravenously with a high risk for causing severe hyperkalaemia [3, 14]. It may be an issue that potassium substitution is guided according to extracellular potassium measurements, which may not necessarily correlate with the intracellular potassium pool. In our cohort, mean potassium concentrations were slightly higher in patients receiving potassium supplementation. In addition, potassium substitution may increase potassium variability. We showed a significantly higher potassium variability in patients receiving potassium supplementation. Due to the lack of standardised protocols, decisions on when to start potassium supplementation are variable [15]. In our cohort, it was performed frequently, but was not associated with mortality reduction. Contrary, there was a tendency for an increased in-hospital mortality risk in patients who received potassium supplementation in each potassium group.
pH value is known as one strong confounding factor of potassium as metabolic acidosis causes a potassium shift from the intracellular to the extracellular space [16]. In our data, pH has a major impact on in-hospital mortality. After adjusting for age, sex and pH value in model 1 mean potassium levels and variability were independently associated with mortality. When evaluating multiple confounding factors in model 2, the results were not that clearly after adding pH value. Complex interactions in between the confounding factors may be responsible for a bias. Interestingly, when calculating the regression model divided by pH groups < 7.36, 7.36–7.44, > 7.44, low mean potassium levels (3.5–4.0 mmol/l) were confirmed as beneficial for the acidosis group (< 7.36). This indicates that especially in those patients, a mean potassium range > 3.5–4.0 mmol/l seems to be beneficial. This may be due to prevention of hyperkalaemia. A low potassium variability is associated with improved outcome after adjusting for multiple confounders including pH.
Interestingly, similar to our results, an association between mortality and mean glucose concentrations as well as glycaemic variability has been described by Krinsley [17,18,19]. In addition, hypoglycaemia is a risk factor for death in ICU patients [20]. However, the regression model 2 showed that our results are independent of mean, minimum or maximum glucose concentrations, as well as glycaemic variability, as risk factors for death [17,18,19,20]. Thus, the association between potassium categories and variability can be discussed in context of glucose control by insulin therapy, which is beneficial for critically ill patients with stress-induced hyperglycaemia [21,22,23]. In human physiology, the activation of Na+K+-ATPase by insulin is essential for the immediate potassium uptake to avoid hyperkalaemia for example after ingestion [24]. Insulin leads as a GLUT 4-independent effect to the activation of the Na+/K+-ATPase and reduction of potassium concentrations [25, 26]. Therefore, it may have underestimated positive effects on potassium concentrations as it may favour lower normokalaemic mean potassium concentrations, which were in our study associated with lower mortality. However, it remains unclear if glucose-independent insulin effects contribute to benefits of insulin therapy in ICU patients [27]. In critically ill rabbits, normoglycaemia in combination with elevated insulin concentrations improved myocardial contractility [27]. In the Leuven insulin trial, there were 6% more potassium measurements below 4.0 mmol/l, whilst hypokalaemia < 3.5 mmol/l was successfully avoided in the group targeting tight glucose concentrations 80–110 mg/dl [28]. Accordingly, the number of potassium measurements in the range of 3.5–4.0 mmol/l was slightly higher in the group with better survival.
Furthermore, insulin therapy may influence potassium variability. A recent trial, investigating potassium concentrations before and after implementing tight glycaemic control in the ICU, found a reduced potassium variability after implementation of tight glycaemic control [13]. Since glucose control by insulin goes along with changes in potassium concentrations, close monitoring of both, potassium and glucose, is of importance. A previous prospective study showed a reduction of hyper- and hypokalaemia in ICU patients using a computer-guided potassium regulation program [29]. For the future, a continuous monitoring system for both glucose and potassium in combination with an adequate protocol could be an interesting approach to target optimal glucose and potassium concentrations with a minimum variability.