Electrolyte Imbalance Among Patients With and With No ST-Elevation Myocardial Infarction

Abstract

Electrolytes imbalances are highly prevalent and have shown a high impact on mortality in patients with acute myocardial infarction. These electrolytes imbalance have prognostic value in predicting mortality in patients with acute myocardial infarction. The purpose of this study was to assess the prognostic value of electrolyte imbalances in predicting 1-month mortality among patients with myocardial infarction with and with no ST-elevation. This cohort study was conducted in a referral hospital in the West Bank, Palestine. All patients with confirmed medical diagnosis of acute myocardial infarction and admitted to the medical coronary care unit in the hospital were eligible participants. A convenience sample of 186 participants was obtained. These participants were followed up for 1 month to assess their survival (alive or dead). Demographic and clinical data were recorded by reviewing their health records. The derived data were analyzed using SPSS version 19. About 36% of all patients were found to be hyponatremic, 15% of them have hypokalemia, and 9% of patients had hypocalcemia. There was a significant difference between STEMI and non-STEMI in sodium (t = 4.7, P < .001). A multivariate logistic regression analysis was performed to predict 1-month mortality for patients with myocardial infarction with and with no ST-elevation. The predictors that were found to be significant are sodium (odds ratio [OR] = 0.789, P = .010), calcium (OR = 0.221, P = .014), diastolic blood pressure (OR = 0.933, P = .047), and blood urea nitrogen (OR = 0.821, P = .005). Electrolyte imbalance was highly prevalent among patients with acute myocardial infarction. Hyponatremia and hypocalcemia were present and associated significantly with predicting 1-month mortality. Health care providers should take into consideration the electrolytes of patients with acute myocardial infarction from the first moment of admission and correct them early to maximize the clinical outcomes and survival for patients.