LUO Gan, TAO Yong-hua, LI Cui, et al. Correlation Analysis of Inhalation Performance of Reduning Inhalation Solution[J]. Chinese journal of experimental traditional medical formulae, 2018, 24(4): 1-7.
DOI:
LUO Gan, TAO Yong-hua, LI Cui, et al. Correlation Analysis of Inhalation Performance of Reduning Inhalation Solution[J]. Chinese journal of experimental traditional medical formulae, 2018, 24(4): 1-7. DOI: 10.13422/j.cnki.syfjx.2018040001.
Correlation Analysis of Inhalation Performance of Reduning Inhalation Solution
Objective: To find out the correlation between information groups of delivery dose and aerosol particle size of Reduning inhalation solution. Method: Taking chlorogenic acid and geniposide as index components
the delivery dose uniformity was determined by a breathing simulator and the aerodynamic particle size distribution was measured by a new generation of particle impactor.Realtime particle size distribution was monitored by a laser diffractometers.The correlation analysis between information groups of delivery dose and aerosol particle size was investigated. Result: Most primitive variables of two sets had good intra-class correlations
but the inter-group correlation was not as good as intra-class correlation.After the canonical correlation analysis
two pairs of canonical variables had significant correlations with correlation coefficients being 0.998 and 0.955
respectively.Almost 90% information of delivery dose group and more than 70% information of particle size group could be elucidated by the two pairs of canonical variables. Conclusion: There is a good intra-class correlation for each of delivery dose group and particle size group
but the correlation between two sets is not so good.Canonical variables perform better inter-group correlation by comparing with original variables
indicating there is a certain correlation between delivery dose and aerosol particle size of Reduning inhalation solution.Furthermore
original variables of these two sets can be well predicted by the two pairs of canonical variables extracted.