OBJECTIVE: The purpose of this study was to determine whether transient myocardial ischemia (TMI) is predictive of adverse in-hospital outcomes among patients admitted to a telemetry unit with acute coronary syndrome (ACS). DESIGN AND SETTING: The study was designed as a prospective clinical trial in a telemetry unit of a large, urban, university medical center. SAMPLE: The sample was comprised of adult patients admitted to the telemetry unit for treatment of acute myocardial infarction, unstable angina, or coronary artery disease warranting cardiac catheterization or percutaneous coronary intervention. METHODS: Continuous 12-lead electrocardiographic (ECG) ST-segment monitoring was initiated in patients admitted to the telemetry unit. TMI was defined as a change in ST amplitude of > or = 100 microV (elevation or depression) in > or = 1 ECG lead lasting > or = 60 seconds, comparing a baseline 12-lead ECG with an event ECG. Frequencies, measurements of central tendency, t test, chi(2) test, and logistic regression analysis were used for data analysis. A P value of <.05 was adopted as the critical value to determine statistical significance. RESULTS: In 237 telemetry unit patients, 39 patients (17%) had ischemia. Overall, 46% of the patients with ischemia had in-hospital complications compared with 10% of the group without ischemia (P <.001). After controlling for other predictors of adverse outcomes (eg, age, gender, Norris prognostic indicator), patients with TMI were 8.5 times more likely to have in-hospital complications (95% CI, 3.71 to 19.71). CONCLUSION: TMI is an independent predictor of in-hospital complications among patients with ACS treated in the telemetry unit setting. Continuous 12-lead ECG ST-segment monitoring provides prognostic information for risk stratification of patients admitted to the hospital for treatment of ACS.
OBJECTIVE: The purpose of this study was to determine whether transient myocardial ischemia (TMI) is predictive of adverse in-hospital outcomes among patients admitted to a telemetry unit with acute coronary syndrome (ACS). DESIGN AND SETTING: The study was designed as a prospective clinical trial in a telemetry unit of a large, urban, university medical center. SAMPLE: The sample was comprised of adult patients admitted to the telemetry unit for treatment of acute myocardial infarction, unstable angina, or coronary artery disease warranting cardiac catheterization or percutaneous coronary intervention. METHODS: Continuous 12-lead electrocardiographic (ECG) ST-segment monitoring was initiated in patients admitted to the telemetry unit. TMI was defined as a change in ST amplitude of > or = 100 microV (elevation or depression) in > or = 1 ECG lead lasting > or = 60 seconds, comparing a baseline 12-lead ECG with an event ECG. Frequencies, measurements of central tendency, t test, chi(2) test, and logistic regression analysis were used for data analysis. A P value of <.05 was adopted as the critical value to determine statistical significance. RESULTS: In 237 telemetry unit patients, 39 patients (17%) had ischemia. Overall, 46% of the patients with ischemia had in-hospital complications compared with 10% of the group without ischemia (P <.001). After controlling for other predictors of adverse outcomes (eg, age, gender, Norris prognostic indicator), patients with TMI were 8.5 times more likely to have in-hospital complications (95% CI, 3.71 to 19.71). CONCLUSION:TMI is an independent predictor of in-hospital complications among patients with ACS treated in the telemetry unit setting. Continuous 12-lead ECG ST-segment monitoring provides prognostic information for risk stratification of patients admitted to the hospital for treatment of ACS.
Authors: Pentti M Rautaharju; Zhu-ming Zhang; Richard E Gregg; Wesley K Haisty; Mara Z Vitolins; Anne B Curtis; James Warren; Milan B Horaĉek; Sophia H Zhou; Elsayed Z Soliman Journal: J Electrocardiol Date: 2013-07-01 Impact factor: 1.438
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Authors: Michele M Pelter; Denise L Loranger; Teri M Kozik; Anita Kedia; Richard P Ganchan; Deborah Ganchan; Xiao Hu; Mary G Carey Journal: J Cardiovasc Nurs Date: 2016 Jul-Aug Impact factor: 2.083
Authors: Ran Xiao; Yuan Xu; Michele M Pelter; Richard Fidler; Fabio Badilini; David W Mortara; Xiao Hu Journal: J Electrocardiol Date: 2018-08-01 Impact factor: 1.438