Background:
Percutaneous coronary intervention (PCI) is an effective revascularization strategy in patients with coronary heart disease (CHD). However, recent studies had indicated that postPCI patients usually suffer from a low-quality life. Cardiac rehabilitation (CR) has been recommended by numerous guidelines in the clinic for these patients. And Baduanjin exercise can significantly benefit patients with CHD. Regrettably, the effect of Baduanjin exercise on postPCI patients is still not clear. Therefore, this systematic review and meta-analysis protocol is planned to explore the effect of Baduanjin exercise in patients with CHD who have undergone PCI.
Methods:
PubMed, Excerpta Medica Database, Cochrane Library, Web of Science, Wanfang Database, SINOMED, China Science and Technology Journal Database, and China National Knowledge Infrastructure will be searched for appropriate articles from respective inceptions until December 1th, 2020. Two reviewers will independently conduct article selection, data collection, and risk of bias evaluation. Disagreements will be resolved first by discussion and then by consulting a third author for arbitration. The primary outcome will include left ventricular ejection fraction. And the change in the scores on the Seattle Angina Questionnaire, SF-36 health survey scale, Zung Self-rating Anxiety scale and self-rating depression scale will be used as the secondary outcomes. RevMan 5.3 will be used for meta-analysis.
Results:
This systematic review and meta-analysis will explore whether Baduanjin exercise is an effective intervention in postPCI patients.
Conclusion:
This systematic review and meta-analysis will provide convincing evidence of Baduanjin exercise that specifically focuses on CR of Baduanjin exercise on CHD after PCI.
Registration number:
INPLASY202130065.
In this letter, we compare three polynomial chaos expansion (PCE)-based methods for ANCOVA (ANalysis of CO-VAriance) indices based global sensitivity analysis for correlated random inputs in two power system applications. Surprisingly, the PCE-based models built with independent inputs after decorrelation may not give the most accurate ANCOVA indices, though this approach seems to be the most correct one and was applied in [1] in the field of civil engineering. In contrast, the PCE model built using correlated random inputs directly yields the most accurate ANCOVA indices for global sensitivity analysis. Analysis and discussions about the errors of different PCE-based models will also be presented. These results provide important guidance for uncertainty management and control in power system operation and security assessment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.