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. 2015 Jan 6;19(1):4.
doi: 10.1186/s13054-014-0720-9.

The relationship between serum potassium, potassium variability and in-hospital mortality in critically ill patients and a before-after analysis on the impact of computer-assisted potassium control

Affiliations

The relationship between serum potassium, potassium variability and in-hospital mortality in critically ill patients and a before-after analysis on the impact of computer-assisted potassium control

Lara Hessels et al. Crit Care. .

Abstract

Introduction: The relationship between potassium regulation and outcome is not known. Our first aim in the present study was to determine the relationship between potassium level and variability in (ICU) stay and outcome. The second aim was to evaluate the impact of a computer-assisted potassium regulation protocol.

Methods: We performed a retrospective before-after study including all patients >15 years of age admitted for more than 24 hours to the ICU of our university teaching hospital between 2002 and 2011. Potassium control was fully integrated with computerized glucose control (glucose and potassium regulation program for intensive care patients (GRIP-II)). The potassium metrics that we determined included mean potassium, potassium variability (defined as the standard deviation of all potassium levels) and percentage of ICU time below and above the reference range (3.5 through 5.0 mmol/L). These metrics were determined for the first ICU day (early phase) and the subsequent ICU days (late phase; that is, day 2 to day 7). We also compared potassium metrics and in-hospital mortality before and after GRIP-II was implemented in 2006.

Results: Of all 22,347 ICU admissions, 10,451 (47%) patients were included. A total of 206,987 potassium measurements were performed in these patients. Glucose was regulated by GRIP-II in 4,664 (45%) patients. The overall in-hospital mortality was 22%. There was a U-shaped relationship between the potassium level and in-hospital mortality (P <0.001). Moreover, potassium variability was independently associated with outcome. After implementation of GRIP-II, in the late phase the time below 3.5 mmol/L decreased from 9.2% to 3.9% and the time above 5.0 mmol/L decreased from 6.1% to 5.2%, and potassium variability decreased from 0.31 to 0.26 mmol/L (all P <0.001). The overall decrease in in-hospital mortality from 23.3% before introduction of GRIP-II to 19.9% afterward (P <0.001) was not related to a specific potassium subgroup.

Conclusions: Hypokalemia, hyperkalemia and potassium variability were independently associated with increased mortality. Computerized potassium control clearly resulted in improved potassium metrics.

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Figures

Figure 1
Figure 1
Lowest and highest potassium levels and outcomes in the early and late phases of intensive care unit admission. Relationship between abnormal potassium levels and mortality during the first 24 hours of intensive care unit (ICU) admission (early phase; upper panel) and days 2 through 7 (late phase; lower panel) of ICU admission. This distinction was made because the initial derangements often cannot be influenced by ICU treatment. Both the lowest and the highest potassium levels measured during the relevant episode were used. Lower and higher potassium levels were both associated with a marked increase in mortality risk. The incidences are indicated above the x-axis. Thus, 59% and 60% of the patients had neither hypokalemia nor hyperkalemia in the early and late phases, respectively. Because some patients are represented in both a hypokalemic and a hyperkalemic category, the percentages add up to more than 100%.
Figure 2
Figure 2
Relationship of mean potassium level and potassium variability with mortality. The relationship between mean potassium and mortality is depicted for five quintiles (black curve). For each mean potassium quintile, quartiles of potassium variability (colored bars) are shown.
Figure 3
Figure 3
Relationship between lowest and highest potassium level and outcome during before and after glucose and potassium regulation program for intensive care patients (GRIP-II). Analogously to Figure 1, here mortality is depicted as a function of abnormal potassium values observed during the early phase (upper panel) and the late phase (lower panel). Patients treated before GRIP-II are shown in black and with GRIP-II in red. Note that, in contrast to the early phase, mortality in the late phase is either comparable or lower in the GRIP-II group across the potassium range.

References

    1. Kraft MD, Btaiche IF, Sacks GS, Kudsk KA. Treatment of electrolyte disorders in adult patients in the intensive care unit. Am J Health Syst Pharm. 2005;62:1663–1682. doi: 10.2146/ajhp040300. - DOI - PubMed
    1. Halperin ML, Kamel KS. Potassium. Lancet. 1998;352:135–140. doi: 10.1016/S0140-6736(98)85044-7. - DOI - PubMed
    1. Gennari FJ. Hypokalemia. N Engl J Med. 1998;339:451–458. doi: 10.1056/NEJM199808133390707. - DOI - PubMed
    1. Gennari FJ. Disorders of potassium homeostasis: hypokalemia and hyperkalemia. Crit Care Clin. 2002;18:273–288. doi: 10.1016/S0749-0704(01)00009-4. - DOI - PubMed
    1. McMahon GM, Mendu ML, Gibbons FK, Christopher KB. Association between hyperkalemia at critical care initiation and mortality. Intensive Care Med. 2012;38:1834–1842. doi: 10.1007/s00134-012-2636-7. - DOI - PubMed