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Practice Patterns and Outcomes of Potassium Repletion Thresholds during Critical Illness
Nicholas A Bosch1, Emily A Vail2,3, Anica C Law1
1Section of Pulmonary, Allergy, Sleep, and Critical Care Medicine, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts.
None:
Rationale: Potassium repletion is common in critically ill patients. However, practice patterns and outcomes related to different intensive care unit (ICU) potassium repletion strategies are unclear. Objectives: 1) Describe potassium repletion practices in critically ill adults; 2) compare the effectiveness of potassium repletion strategies; and 3) compare effectiveness and safety of specific potassium repletion thresholds on patient outcomes. Methods: This was a retrospective analysis of the PINC AI Healthcare Database (2016-2022), including all critically ill adults admitted to an ICU on Hospital Day 1 and with a serum potassium concentration measured on Hospital Day 2. We determined the frequency of potassium repletion (any formulation) at each measured serum potassium concentration in each ICU, then classified ICUs as having threshold-based (a large increase in potassium repletion rates at a specific serum potassium concentration) or probabilistic (linear relationship between serum concentration and the repletion probability) patterns of repletion. Between patients in threshold-based and probabilistic repletion ICUs, we compared outcomes (primary outcome: potassium repletion frequency). We reported unadjusted percentages per exposure group and the adjusted odds ratios (from hierarchical regression models) for each outcome. Among patients in threshold-based ICUs with the most common repletion thresholds (3.5 mEq/L and 4.0 mEq/L), we conducted regression discontinuity analyses to examine the effectiveness of potassium repletion at each potassium threshold. Results: We included 190,490 patients in 88 ICUs; 35.0% received at least one dose of potassium on the same calendar day. Rates of potassium repletion were similar between 22 threshold-based strategy ICUs (33.5%) and 22 probabilistic strategy ICUs (36.4%). There was no difference in the adjusted risk of potassium repletion between patients admitted to threshold-based strategy ICUs versus probabilistic strategy ICUs (adjusted odds ratio, 1.09; 95% confidence interval [CI], 0.76-1.57). In regression discontinuity analysis, crossing the 3.5 mEq/L threshold from high to low potassium levels resulted in a 39.1% (95% CI, 23.7-42.4) absolute increase in potassium repletion but no change in other outcomes. Similarly, crossing the 4.0 mEq/L threshold resulted in a 36.4% (95% CI, 22.4-42.2) absolute increase in potassium repletion but no change in other outcomes. Conclusions: Potassium repletion is common in critically ill patients and occurs over a narrow range of "normal" potassium levels (3.5-4.0 mEq/L); use of a threshold-based repletion strategy to guide potassium repletion in ICU patients is not associated with clinically meaningful differences in outcomes.
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