Severe Hypokalemia Masquerading Myocardial Ischemia

Abstract

An advanced degree of body potassium deficit may produce striking changes in the electrocardiogram (ECG). These changes can result in incidental findings on the 12-lead ECG or precipitate potentially life-threatening dysrhythmias. Although usually readily recognized, at times these abnormalities may be confused with myocardial ischemia. The object was to report a case of severe hypokalemia mimicking myocardial ischemia. A 33-year-old, previously healthy man, presented to the Emergency Department (ED) with a progressive weakness and chest discomfort. The electrocardiogram showed a marked ST-segment depression in leads II, III, aVF, V1-V6. The initial diagnosis was non ST-elevation myocardial infarction. Echocardiography was normal and troponin levels were within normal limits. A more detailed history revealed that the patient had an episode of acute gastroenteritis with diarrhea and vomiting. Serum chemistries were notable for a potassium concentration of 1,8 mmol per liter. With aggressive electrolyte correction, the ECG abnormalities reverted as potassium levels normalized. Hypokalemia induced ST-segment depression may simulate myocardial ischemia. The differential diagnosis might be difficult, especially in the cases when ST changes are accompanied with chest discomfort.

Detecting and Reversing Myocardial Ischemia Using an Artificially Intelligent Bioelectronic Medicine

“…Importantly, biomarker features of myocardial ischemia can be variable within and across subjects (Patel et al, 1996; Celermajer et al, 1994; Deanfield & Spiegelhalter, 1990; Tzivoni et al, 1987). Furthermore, seemingly separate cardiovascular states can exhibit highly correlated biomarkers and thus statistically overlap (Sharma & Gedeon, 2012; Michaelides et al, 2010; Petrov et al, 2012; Sapin et al, 1991; Gutterman, 2009). Therefore, both biomarker variability and correlation across states should be attributes of a myocardial ischemia model.…”

“…Events of myocardial ischemia are physiologically variable, within and across subjects (Patel et al, 1996; Celermajer et al, 1994; Deanfield & Spiegelhalter, 1990; Tzivoni et al, 1987). Furthermore, non-ischemic states have electrophysiological characteristics similar to myocardial ischemia (e.g., cardiac valve dysfunction, repolarization abnormalities, or an electrolyte imbalance; Michaelides et al, 2010; Sapin et al, 1991; Petrov et al, 2012; Gutterman, 2009). Therefore, detecting myocardial ischemia is complicated by significant biomarker variability and off-target states.…”

Large negative U waves associated with hypokalemia

“…A large upright U wave is a risk factor for early afterdepolarization-induced triggered activity which can initiate torsade de pointes ventricular tachycardia and ventricular fibrillation [20,21] . Severe hypokalemia can masquerade as myocardial ischemia in the ECG, but troponin levels usually remain negative [22] .…”

Dynamic detection and reversal of myocardial ischemia using an artificially intelligent bioelectronic medicine

“…Physiological features of myocardial ischemia can be variable within and across individuals (e.g., consistency of episodes and overall electrocardiographic feature variability) (18,19). Furthermore, seemingly separate cardiovascular states can exhibit highly correlated physiological features and thus statistically overlap (8,(20)(21)(22)45). Therefore, both physiological variability and correlation across states should be attributes of a myocardial ischemia model.…”

“…Events of myocardial ischemia are physiologically variable, within and across subjects (8,18,19). Furthermore, nonischemic states have electrophysiological characteristics similar to myocardial ischemia (e.g., cardiac valve dysfunction, repolarization abnormalities, or an electrolyte imbalance) (8,(20)(21)(22). Therefore, detecting myocardial ischemia is complicated by significant physiological feature variability and off-target states.…”