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Browsing by Author "Selim, Bernardo J."
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Item The Association between Nocturnal Cardiac Arrhythmias and Sleep-Disordered Breathing: The DREAM Study(American Academy of Sleep Medicine, 2016-06-15) Selim, Bernardo J.; Koo, Brian B.; Qin, Li; Jeon, Sangchoon; Won, Christine; Redeker, Nancy S.; Lampert, Rachel J.; Concato, John P.; Bravata, Dawn M.; Ferguson, Jared; Strohl, Kingman; Bennett, Adam; Zinchuk, Andrey; Yaggi, Henry K.; Department of Medicine, IU School of MedicineSTUDY OBJECTIVES: To determine whether sleep-disordered breathing (SDB) is associated with cardiac arrhythmia in a clinic-based population with multiple cardiovascular comorbidities and severe SDB. METHODS: This was a cross-sectional analysis of 697 veterans who underwent polysomnography for suspected SDB. SDB was categorized according to the apnea-hypopnea index (AHI): none (AHI < 5), mild (5 ≥ AHI < 15), and moderate-severe (AHI ≥ 15). Nocturnal cardiac arrhythmias consisted of: (1) complex ventricular ectopy, (CVE: non-sustained ventricular tachycardia, bigeminy, trigeminy, or quadrigeminy), (2) combined supraventricular tachycardia, (CST: atrial fibrillation or supraventricular tachycardia), (3) intraventricular conduction delay (ICD), (4) tachyarrhythmias (ventricular and supraventricular), and (5) any cardiac arrhythmia. Unadjusted, adjusted logistic regression, and Cochran-Armitage testing examined the association between SDB and cardiac arrhythmias. Linear regression models explored the association between hypoxia, arousals, and cardiac arrhythmias. RESULTS: Compared to those without SDB, patients with moderate-severe SDB had almost three-fold unadjusted odds of any cardiac arrhythmia (2.94; CI 95%, 2.01-4.30; p < 0.0001), two-fold odds of tachyarrhythmias (2.16; CI 95%,1.47-3.18; p = 0.0011), two-fold odds of CVE (2.01; 1.36-2.96; p = 0.003), and two-fold odds of ICD (2.50; 1.58-3.95; p = 0.001). A linear trend was identified between SDB severity and all cardiac arrhythmia subtypes (p value linear trend < 0.0001). After adjusting for age, BMI, gender, and cardiovascular diseases, moderate-severe SDB patients had twice the odds of having nocturnal cardiac arrhythmias (2.24; 1.48-3.39; p = 0.004). Frequency of obstructive respiratory events and hypoxia were strong predictors of arrhythmia risk. CONCLUSIONS: SDB is independently associated with nocturnal cardiac arrhythmias. Increasing severity of SDB was associated with an increasing risk for any cardiac arrhythmia.Item The Determining Risk of Vascular Events by Apnea Monitoring (DREAM) Study: Design, Rationale and Methods(Springer, 2016-05) Koo, Brian B.; Won, Christine; Selim, Bernardo J.; Qin, Li; Jeon, Sangchoon; Redeker, Nancy S.; Bravata, Dawn M.; Strohl, Kingman P.; Concato, John; Yaggi, Henry K.; Department of Neurology, IU School of MedicinePurpose The goal of the Determining Risk of Vascular Events by Apnea Monitoring (DREAM) study is to develop a prognostic model for cardiovascular outcomes, based on physiologic variables—related to breathing, sleep architecture, and oxygenation—measured during polysomnography in US veterans. Methods The DREAM study is a multi-site, retrospective observational cohort study conducted at three Veterans Affairs (VA) centers (West Haven, CT; Indianapolis, IN; Cleveland, OH). Veterans undergoing polysomnography between January 1, 2000 and December 31, 2004 were included based on referral for evaluation of sleep-disordered breathing, documented history and physical prior to sleep testing, and ≥2-h sleep monitoring. Demographic, anthropomorphic, medical, medication, and social history factors were recorded. Measures to determine sleep apnea, sleep architecture, and oxygenation were recorded from polysomnography. VA Patient Treatment File, VA–Medicare Data, Vista Computerized Patient Record System, and VA Vital Status File were reviewed on dates subsequent to polysomnography, ranging from 0.06 to 8.8 years (5.5 ± 1.3 years; mean ± SD). Results The study population includes 1840 predominantly male, middle-aged veterans. As designed, the main primary outcome is the composite endpoint of acute coronary syndrome, stroke, transient ischemic attack, or death. Secondary outcomes include incidents of neoplasm, congestive heart failure, cardiac arrhythmia, diabetes, depression, and post-traumatic stress disorder. Laboratory outcomes include measures of glycemic control, cholesterol, and kidney function. (Actual results are pending.) Conclusions This manuscript provides the rationale for the inclusion of veterans in a study to determine the association between physiologic sleep measures and cardiovascular outcomes and specifically the development of a corresponding outcome-based prognostic model.