Articol

Predicting electrolyte derangements in heart failure patients

Predicting electrolyte derangements in heart failure patients

Authors:

 

Brown CL1*, Fudim M2, Harrell F3, Wang L3, McPherson JA4 and Lindenfeld J4

 

1Department of Cardiology, Cedars-Sinai Heart Institute, California, USA

2Division of Cardiology, Department of Internal Medicine, Duke University Hospital, Durham, North Carolina, USA

3Department of Biostatistics, Vanderbilt University, Nashville, Tennessee, USA

4Division of Cardiology, Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA

 

Abstract
 

Acute Decompensated Heart Failure (ADHF) is one of the leading causes of hospitalization in the United States (US). It is also one of the leading causes of death in the US, contributing to 1 in 9 mortalities. One half of ADHF deaths are attributed to arrhythmia or SCD, with the primary driver of SCD being derangements in electrolytes. Here we describe the current literature regarding pathophysiology as well as clinical management of electrolytes with a focus on potassium homeostasis in ADHF.

 

Introduction


Physiology of electrolyte derangements

 

Multiple mechanisms drive the change in plasma potassium homeostasis in heart failure. Heart failure itself is defined as syndrome caused by cardiac dysfunction, generally resulting from myocardial muscle dysfunction or loss and is characterized by either LV dilation or hypertrophy or both [1,2]. Heart failure leads to neurohormonal and circulatory abnormalities which are a key driver of potassium dysregulation. A primary component of neurohormonal changes is hyperadrenergic tone which leads to potassium activation of beta- 2 receptors and transport of plasma potassium intracellularly [3,4]. Additionally, hyperadrenergic tone is a direct activator of the reninangiotensin- aldosterone system leading to increased reabsorption of sodium and increased excretion of potassium via sodium-potassiumchloride exchange in the loop of Henle. The aforementioned effects lead to total body potassium depletion unrelated to severity of heart failure, age, or renal function [5]. In addition to the natural physiologic mechanisms affecting plasma potassium and total body potassium homeostasis, iatrogenic etiologies are also a major contributor. The vast majority (90%) of heart failure hospitalizations are managed medically with diuretic therapy [6]. Adverse effects of diuretics are well established and include derangements in potassium as well as other electrolytes via potassium wasting [7]. Thus, further depleting total body potassium and plasma potassium stores.

 

Clinical management of hypokalemia

 

Despite Hypokalemia being a known risk factor for increased mortality in heart failure patients there is scant data on optimal levels or clinical risk factors for hypokalemia in ADHF [8,9]. Additionally, hyperkalemia is also associated with increased mortality in heart failure, especially when potassium elevations are acute [10]. Many small studies have evaluated risk factors for hyperkalemia and demonstrate an increased risk with the use of angiotensin converting enzyme inhibitors (ACE-I), angiotensin receptor blockers (ARB) and mineralocorticoid receptor antagonists. Larger studies evaluating risk factors for hyperkalemia have shown conflicting results [11,12]. Clinical guidelines for the management of heart failure do not make specific recommendations regarding the frequency of monitoring of electrolytes. Given the lack of data regarding clinical factors associated with hypokalemia and hyperkalemia in hospitalized ADHF patients we sought to evaluate factors contributing to potassium derangements and to create predictive modelling to suggest optimal timing for monitoring electrolytes in hospitalized heart failure patients.

 

Hypothesis

 

In this study, we hypothesized that clinical factors including renal function, diuretic dosing, urine output, medication use, and potassium repletion would affect the risk of electrolyte derangements in hospitalized HF patients undergoing diuresis and could be modelled to predict the risk for hypo and hyperkalemia.


Methods and Materials


We retrospectively analysed 2,263 patients admitted for ADHF at a tertiary academic medical centre from January 2012 to December 2014. Electronic medical records identified by ICD-9 primary diagnosis was used to extract data regarding medication administration and dosing, fluid intake and output, laboratory values, and echocardiographic data. Patients were included in the study if they received oral or intravenous (IV) diuretic therapy and had measurements of creatinine, potassium and ejection fraction. Patients were excluded if they were treated with a continuous diuretic drip during their hospitalization(s) or if no echocardiogram was performed within 12 months of hospitalization. Estimated GFR was calculated using Chronic Kidney Disease Epidemiology Collaboration [13]. We defined hypokalemia and hyperkalemia using normal limits from our laboratory of <3.5 mEq/L and >5.1 mEq/L respectively. We used proportional odds logistic models for each outcome separately, with urine output, diuretic regimen, creatinine, ejection fraction, potassium supplementation, ACE-I/ARB use, mineralocorticoid receptor antagonist (MRA) use, and hypokalemia (<3.5 mEq/L) on prior lab draw (same admission) as the independent variables. Since each patient had multiple assessments included in the data, we used a cluster sandwich covariance estimator with the patient ID as a cluster in order to adjust the variance in our model to account for these repeated measurements. We allowed all continuous variables including urine output, effective diuretic dose, creatinine, potassium supplementation and ejection fraction to have a nonlinear relationship with the outcomes using restricted cubic spline with 3 knots. All analyses were performed using statistical software R version 3.1.2 [12-14].


Results


Characteristics

 

A total of 913 patients meeting the study criteria (13,739 measurements of potassium during hospitalization) were analysed (full characteristics can be found in Table 1); 718 (78.6%) were white, 173 (18.9%) were African American and 22 (2.5%) were other. The mean age of participants was 65.4 years and 593 of the 913 (65%) patients were men.

 

Keywords: 

 

Heart failure; Diuresis; Electrolytes; Hyperkalemia; Hypokalemia; Potassium

 

Copyright: 

 

© 2019 Brown CL, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

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