بررسی عوامل مؤثر بر کیفیت و کمیت خواب شبانه بیماران پس از جراحی پیوند عروق کرونر

Introduction: Sleep disturbance is common in patients undergoing Coronary Artery Bypass Graft surgery and has been recognized for more than 30 years. New literature suggests the importance of sleep and rest for restoration, protection and promotion of function and wellbeing of these patients. Because of the importance of the role of nurses in diagnosis and treatment of sleep disorders, this study was conducted to determine possible effective factors on sleep quality and sleep quantity of patients after CABG. Methods: This longitudinal, descriptive and correlational study was conducted on 91 patients admitted to Imam Reza Hospital in Mashad City in 2005-2006. Subjects were selected according to inclusion and exclusion criteria. Data was collected by interview in three stages: 24 hours before surgery, as well as 6 weeks and 10 weeks after surgery. Subjective sleep quality was measured with PSQI and sleep quantity was measured with sleep log. The first two interviews were done at the hospital clinic and the last via telephone. Data was analyzed in SPSS using student T test, Pearson correlation coefficient and General Linear Model. Results: According to Univariable analysis, variables such as age (p=0.03), aorta clamp time (p=0.003), mechanical ventilation time (p=0.01), staying time in hospital (p=0.04) can affect sleep quantity 10 weeks after surgery. Previous history of sleep disorder (p=0.005), diabetes (p=0.02), use of diuretic drugs before surgery (p=0.04) and ACEI drugs after surgery (p=0.01) can affect sleep quality 10 weeks after surgery. Conclusion: Sleep disorder history (p=0.01), use of diuretic drugs before surgery (p=0.04) and sleep quantity 6 weeks after surgery (p=0.01) have been the most effective factors on sleep quality 10 weeks after surgery, whereas quality of life 10 weeks after surgery (p=0.04) has been the most effective factor on sleep quantity 10 weeks after surgery. There is therefore a necessity for presenting approaches in order to eliminate and minimize modifiable factors.