医学
慢性阻塞性肺病
肺康复
物理疗法
氧饱和度
膈式呼吸
麻醉
内科学
病理
有机化学
化学
替代医学
氧气
作者
Natasha Ahmed,S Begum,Taskina Ali,M Suhana
出处
期刊:PubMed
日期:2020-04-01
卷期号:29 (2): 424-430
被引量:3
摘要
Pulmonary rehabilitation (PR) program of a sufficient duration has impact on consequence of COPD. To evaluate the effects of combination of pursed lip breathing (PLB), diaphragmatic breathing (DB) and lower extremity endurance training (LEET) as part of PR program in stable patients with COPD on oxygenation status, dyspnea and fatigue. This prospective interventional study was performed in the Department of Physiology, Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh from July 2010 to June 2011 and was performed on 116 male stable moderate COPD patients aged 50 to 65 years. Among them, 56 patients were without PR (control group) and 60 patients were intervened with PR (experimental group). The experimental patients were advised to perform the home based PR program (PLB, DB and LEET) for 30 minutes duration per session at home twice per day, along with standard drug treatment of COPD for uninterrupted 60 days. The control patients continued their treatment of COPD with standard drug for successive 60 days were advised. To evaluate the effects of PR, Peripheral capillary oxygen saturation (SpO₂, by pulse Oximeter), level of dyspnea and level of fatigue by Modified Borg Scale from baseline to end of six minute walk test (6MWT) of all subjects were recorded on day 0 and day 60 for both the groups. Independent sample 't' test and paired Student's 't' test were done with SPSS software. In the interpretation of results, p value of <0.05 was considered as statistically significant. In the present study, we found less decrement of SpO₂ and less increment of level of dyspnea as well as level of fatigue after 6MWT in the COPD patients with PR on 60th day of follow up. The study reveals that oxygenation status, dyspnea and fatigue improve after execution of regular home based PR program in patients with moderate stable COPD.
科研通智能强力驱动
Strongly Powered by AbleSci AI