Long-Term Potassium Monitoring and Dynamics in Heart Failure and Risk of Mortality

Background: The prognostic value of long-term potassium monitoring and dynamics in heart failure has not been characterized completely. We sought to determine the association between serum potassium values collected at follow-up with all-cause mortality in a prospective and consecutive cohort of patients discharged from a previous acute heart failure admission. Methods: Serum potassium was measured at every physician-patient encounter, including hospital admissions and ambulatory settings. The multivariable-adjusted association of serum potassium with mortality was assessed by using comprehensive state-of-the-art regression methods that can accommodate time-dependent exposure modeling. Results: The study sample included 2164 patients with a total of 16 116 potassium observations. Mean potassium at discharge was 4.3±0.48 mEq/L. Hypokalemia (<3.5 mEq/L), normokalemia (3.5–5.0 mEq/L), and hyperkalemia (>5 mEq/L) were observed at the index admission in 77 (3.6%), 1965 (90.8%), and 122 (5.6%) patients, respectively. At a median follow-up of 2.8 years (range, 0.03–12.8 years), 1090 patients died (50.4%). On a continuous scale, the multivariable-adjusted association of potassium values and mortality revealed a nonlinear association (U-shaped) with higher risk at both ends of its distribution (omnibus P=0.001). Likewise, the adjusted hazard ratios for hypokalemia and hyperkalemia, normokalemia as reference, were 2.35 (95% confidence interval, 1.40–3.93; P=0.001) and 1.55 (95% confidence interval, 1.11–2.16; P=0.011), respectively (omnibus P=0.0003). Furthermore, dynamic changes in potassium were independently associated with substantial differences in mortality risk. Potassium normalization was independently associated with lower mortality risk (P=0.001). Conclusions: Either modeled continuously or categorically, serum potassium levels during long-term monitoring were independently associated with mortality in patients with heart failure. Likewise, persistence of abnormal potassium levels was linked to a higher risk of death in comparison with patients who maintained or returned to normal values.

[1]  E. Núñez,et al.  Burden of Recurrent Hospitalizations Following an Admission for Acute Heart Failure: Preserved Versus Reduced Ejection Fraction. , 2017, Revista espanola de cardiologia.

[2]  P. Ponikowski,et al.  Serum Potassium Levels and Outcome in Acute Heart Failure (Data from the PROTECT and COACH Trials). , 2017, The American journal of cardiology.

[3]  C. Torp‐Pedersen,et al.  Short-term mortality risk of serum potassium levels in hypertension: a retrospective analysis of nationwide registry data , 2016, European heart journal.

[4]  A. Keren,et al.  Serum Potassium Levels and Outcome in Patients With Chronic Heart Failure. , 2016, The American journal of cardiology.

[5]  P. Ponikowski,et al.  [2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure]. , 2016, Kardiologia polska.

[6]  I. Piña,et al.  Hyperkalemia in Heart Failure. , 2016, Journal of the American College of Cardiology.

[7]  Volkmar Falk,et al.  2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure , 2016, Revista espanola de cardiologia.

[8]  Volkmar Falk,et al.  2016 ESC Guidelines for the Diagnosis and Treatment of Acute and Chronic Heart Failure. , 2016, Revista espanola de cardiologia.

[9]  Y. Pinto,et al.  Serum potassium decline during hospitalization for acute decompensated heart failure is a predictor of 6-month mortality, independent of N-terminal pro-B-type natriuretic peptide levels: An individual patient data analysis. , 2015, American heart journal.

[10]  Eric E. Smith,et al.  2014 ACC/AHA Key Data Elements and Definitions for Cardiovascular Endpoint Events in Clinical Trials: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Cardiovascular Endpoints Data Standards). , 2015, Circulation.

[11]  G. Caimi,et al.  Acid–base and electrolyte abnormalities in heart failure: pathophysiology and implications , 2015, Heart Failure Reviews.

[12]  K. Swedberg,et al.  Changes in serum potassium levels during hospitalization in patients with worsening heart failure and reduced ejection fraction (from the EVEREST trial). , 2015, The American journal of cardiology.

[13]  Adrian F. Hernandez,et al.  Transitions of care in heart failure: a scientific statement from the American Heart Association. , 2015, Circulation. Heart failure.

[14]  Piotr Ponikowski,et al.  Improving care for patients with acute heart failure: before, during and after hospitalization , 2014, ESC heart failure.

[15]  P. Ponikowski,et al.  Diuretic response in patients with acute decompensated heart failure: characteristics and clinical outcome—an analysis from RELAX-AHF , 2014, European journal of heart failure.

[16]  W. Levy,et al.  Heart failure risk prediction models: what have we learned? , 2014, JACC. Heart failure.

[17]  Akshay S. Desai,et al.  Incidence, Predictors, and Outcomes Related to Hypo- and Hyperkalemia in Patients With Severe Heart Failure Treated With a Mineralocorticoid Receptor Antagonist , 2014, Circulation. Heart failure.

[18]  Naoki Sato,et al.  The global health and economic burden of hospitalizations for heart failure: lessons learned from hospitalized heart failure registries. , 2014, Journal of the American College of Cardiology.

[19]  Piotr Ponikowski,et al.  EURObservational Research Programme: regional differences and 1‐year follow‐up results of the Heart Failure Pilot Survey (ESC‐HF Pilot) , 2013, European journal of heart failure.

[20]  M. Banach,et al.  The meaning of hypokalemia in heart failure. , 2012, International journal of cardiology.

[21]  G. Van den Berghe,et al.  Serum potassium levels and mortality in acute myocardial infarction. , 2012, JAMA.

[22]  Dimitris Rizopoulos,et al.  Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time‐to‐Event Data , 2011, Biometrics.

[23]  Christopher H. Jackson,et al.  Multi-State Models for Panel Data: The msm Package for R , 2011 .

[24]  G. Bakris,et al.  Mild hyperkalemia and outcomes in chronic heart failure: a propensity matched study. , 2010, International journal of cardiology.

[25]  G. Bakris,et al.  Hypokalemia and Outcomes in Patients With Chronic Heart Failure and Chronic Kidney Disease: Findings From Propensity-Matched Studies , 2010, Circulation. Heart failure.

[26]  G. Bakris,et al.  A propensity-matched study of low serum potassium and mortality in older adults with chronic heart failure. , 2009, International journal of cardiology.

[27]  Patrick Royston,et al.  Multivariable Model-Building: A Pragmatic Approach to Regression Analysis based on Fractional Polynomials for Modelling Continuous Variables , 2008 .

[28]  M. Gheorghiade,et al.  A propensity-matched study of the association of low serum potassium levels and mortality in chronic heart failure. , 2007, European heart journal.

[29]  L. Gettes Electrolyte abnormalities underlying lethal and ventricular arrhythmias. , 1992, Circulation.