Pulmonary Rehabilitation for Post-COVID-19.

来自 PUBMED

作者:

Aljazeeri JAlmusally RWert YAbdelhalim MKlinger CRamesh NRahman T

展开

摘要:

Patients with COVID-19 often report persistent respiratory symptoms. Limited data exist on how to mitigate long-term sequelae of exercise intolerance and dyspnea. We aimed to study the role of pulmonary rehabilitation (PR) in patients with post-COVID-19. This was an observational study. Consecutive patients with post-COVID-19, admitted to three separate outpatient PR programs, were enrolled. The program consisted of 8-12 wk of PR sessions (3 times/wk). Data were gathered at the initial visit and discharge. The primary outcome was the change in the 6-min walk test (6MWT) distance. Secondary outcomes included the Shortness of Breath Questionnaire (SOBQ), modified Borg dyspnea scale, Patient Health Questionnaire-9 (PHQ-9), and Lung Information Needs Questionnaire (LINQ). A total of 56 patients completed the PR program (age 62.8 ± 14.7 yr, 57% were men). At baseline, the mean 6MWT was 313.3 ± 193.8 m. On average, the 6MWT improved by 84.3 m after PR ( P < .0001). Apart from the modified Borg dyspnea scale, there was improvement across secondary outcomes: SOBQ (-16.9 points), PHQ-9 (-2.6 points), and LINQ (-4.2 points); all P < .05. Pulmonary rehabilitation showed a promising positive effect on patients with with post-COVID-19. It improved exercise capacity, perception of dyspnea, depressive symptoms, and patient knowledge needed to manage their lung disease. Pulmonary rehabilitation should be considered for post-COVID-19 patients.

收起

展开

DOI:

10.1097/HCR.0000000000000813

被引量:

2

年份:

1970

SCI-Hub (全网免费下载) 发表链接

通过 文献互助 平台发起求助,成功后即可免费获取论文全文。

查看求助

求助方法1:

知识发现用户

每天可免费求助50篇

求助

求助方法1:

关注微信公众号

每天可免费求助2篇

求助方法2:

求助需要支付5个财富值

您现在财富值不足

您可以通过 应助全文 获取财富值

求助方法2:

完成求助需要支付5财富值

您目前有 1000 财富值

求助

我们已与文献出版商建立了直接购买合作。

你可以通过身份认证进行实名认证,认证成功后本次下载的费用将由您所在的图书馆支付

您可以直接购买此文献,1~5分钟即可下载全文,部分资源由于网络原因可能需要更长时间,请您耐心等待哦~

身份认证 全文购买

相似文献(137)

参考文献(0)

引证文献(2)

来源期刊

-

影响因子:暂无数据

JCR分区: 暂无

中科院分区:暂无

研究点推荐

关于我们

zlive学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们不忘初心,砥砺前行。

友情链接

联系我们

合作与服务

©2024 zlive学术声明使用前必读