Chronic Obstructive Pulmonary Disease (COPD) by 2015 approximately 3.17 million deaths worldwide and prevalence of COPD in Indonesia by 3.7% 2. One of the complications that can be experienced by patients with COPD is nocturnal hypoxemia is the lack of oxygen intake at night. This situation will be more aggravated if the patient is also suffering from COPD sleep disorder in the form of Obstructive Sleep Apnea (OSA). OSA is a sleep disorder caused by a blocked airway and a temporary pause when the breath is at least 10 seconds4. When COPD and OSA occur at the same time it can create double the uncomfortable condition of breathing. The purpose of this study is to determine the risk prediction model of OSA occurrence in COPD patients based on factors influencing the risk of OSA occurrence in Cipto Mangunkusumo Hospital (RSCM). The data used in this study is the primary data of COPD patients at RSCM by interviewed using the Berlin questionnaire. The selected sample uses non-probability sampling with purposive sampling method. The sample in this study was 93 patients of COPD patients. In this study, we proposed binary logistic regression method to predict the risk model for OSA occurrence in COPD patients.
Of 93 COPD patients there were 47 (50.54%) COPD patients at risk of OSA and from risk factors such as age, sex, body mass index, smoking history, neck circumference, abdominal circumference and using two questionnaires i.e. mMRC questionnaire. It is a CAT questionnaire to assess the severity of COPD symptoms. The results obtained for factors that affect the risk of OSA in COPD patients are age, sex and CAT in COCs of severe degree then the OSA risk prediction model in COPD patients based on influencing factors suggests that COPD patients with male and female sex the risk of OSA occurrence is 0.26 times greater, patients’age with COP with ≤ 30 years have an OSA risk of 1.04 times greater and patients with severe COP are at greater risk of having OSA of 5.16 greater than mild or moderate COPD patients . This result is in accordance with research conducted abroad. This means that this study shows that the characteristics of COPD patients at risk of OSA Overseas patients are similar to those of COPD patients at risk of OSA in Indonesia. The accuracy of the model was calculated using the classification table at cut point 0.5, obtained by the classification accuracy of 73.1%.