Chronic Obstructive Pulmonary Disease (COPD) is a worldwide health problem. COPD has a tendency for exacerbations. Exacerbations are worsening of acute respiratory symptoms resulting in additional therapy. Exacerbations in COPD increase the risk of death. The objective of this study is to determine the prediction model of exacerbations in patients with COPD based on factors affecting exacerbations in patients with COPD at RSCM (Rumah Sakit Cipto Mangunkusumo). The data used in this study is secondary data from the medical records of patients with COPD in RSCM. The sample was chosen using purposive sampling technique. The samples in this study are 107 patients with COPD. The method used is binary logistic regression analysis. The results of this study indicate that the factors that significantly influence the exacerbations of COPD are breathlessness, history of ICS use, and history of antibiotics use. Appropriate logistic regression model has been obtained. The result indicates that patients with COPD who have breathlessness, have history of ICS use, and have history of antibiotics use are more at risk of exacerbations than those who don't. Accuracy test has been conducted with classification table at cut point 0.5. The prediction model has an accuracy rate of 74.77 %.
|Journal||Journal of Physics: Conference Series|
|Publication status||Published - 12 Jan 2021|
|Event||2nd Basic and Applied Sciences Interdisciplinary Conference 2018, BASIC 2018 - Depok, Indonesia|
Duration: 3 Aug 2018 → 4 Aug 2018
- Logistic regression