Objective:To analyze the clinical characteristics and related factors of cognition disorders in elderly hypertensive patients.Methods:It was a cross-sectional study. A total of 612 hypertensive patients with the age of (69.06±6.58) years (median 68.00 years) admitted in the Department of Cardiology, General Hospital of Chinese People′s Liberation Army from October 2022 to April 2024 were enrolled. The demographic and clinical data were collected, the cognition status was assessed with Mini-Mental State Examination (MMSE) at admission. The related factors of cognition disorders were analyzed with univariate and multivariate logistic regression.Results:The results showed that female hypertensive patients and those with older age, lower education, higher fasting blood glucose (FBG) and diabetes mellitus, higher low-density lipoprotein cholesterol (LDL-C) level, higher systolic blood pressure (SBP) and more cardiovascular comorbidities were likely to have cognition disorders (all P<0.05). Multivariate logistic regression analysis showed that smoking history, elevated SBP, elevated heart rate, elevated FBG, and elevated LDL-C were independent risk factors for cognition disorders in elderly hypertensive patients,while higher education level was an independent protective factor (all P<0.05). Conclusion:Smoking, increased SBP, increased heart rate, increased FBG, increased LDL-C and lower education level are independently associated with cognition disorders in elderly hypertensive patients.

Objective:To analyze the clinical characteristics and related factors of cognition disorders in elderly hypertensive patients.Methods:It was a cross-sectional study. A total of 612 hypertensive patients with the age of (69.06±6.58) years (median 68.00 years) admitted in the Department of Cardiology, General Hospital of Chinese People′s Liberation Army from October 2022 to April 2024 were enrolled. The demographic and clinical data were collected, the cognition status was assessed with Mini-Mental State Examination (MMSE) at admission. The related factors of cognition disorders were analyzed with univariate and multivariate logistic regression.Results:The results showed that female hypertensive patients and those with older age, lower education, higher fasting blood glucose (FBG) and diabetes mellitus, higher low-density lipoprotein cholesterol (LDL-C) level, higher systolic blood pressure (SBP) and more cardiovascular comorbidities were likely to have cognition disorders (all P<0.05). Multivariate logistic regression analysis showed that smoking history, elevated SBP, elevated heart rate, elevated FBG, and elevated LDL-C were independent risk factors for cognition disorders in elderly hypertensive patients,while higher education level was an independent protective factor (all P<0.05). Conclusion:Smoking, increased SBP, increased heart rate, increased FBG, increased LDL-C and lower education level are independently associated with cognition disorders in elderly hypertensive patients.

OBJECTIVE： To optimize and improve the quality standard for Citrus reticulata formula granules. METHODS： Totally 13 batches of C. Reticulata formula granules from 4 different manufacturers were used as trial samples， and qualitative identification of hesperidin and nobiletin in the samples were carried out by TLC according to the method of 2015 edition of Chinese Pharmacopoeia （part Ⅳ）. The quantitative analysis of naringin， hesperidin， hesperetin， nobiletin and tangeretin in C. reticulatae formula granules were conducted by UPLC[The determination was performed on Waters Acquity UPLC BEH C18 column with mobile phase consisted of acetonitrile-0.2％ phosphoric acid aqueous solution （gradient elution）. The detection wavelength was set at 283 nm， and sample size was 3 μL]. RESULTS： The results of TLC showed that in the chromatograms of samples， same color spots were shown in the corresponding positions of the chromatogram of reference substance. The results of UPLC showed， that the linear range of naringin， hesperidin， hesperetin， nobiletin and tangeretin were 0.64-6.44， 15.78-157.80， 0.17-1.66， 2.08-20.85 and 2.04-20.43 μg/mL， respectively （all r≥0.999 2）； the limits of detection were 0.03， 0.33， 0.10， 0.20 and 0.06       μg/mL； the limits of quantitation were 0.07， 1.34， 0.20， 0.60 and 0.22 μg/mL. The average recoveries were 99.4％， 99.6％， 99.7％， 99.7％ and 99.7％ （n＝9）； RSDs of precision （n＝6）， stability （n＝7） and reproducibility （n＝6） tests were all≤2.03％； naringin was detected in only 3 batches of samples from one manufacturer （the content ranged from 0.067 3 to 0.069.6    mg/g）， while the other 4 components were detected in 13 batches of samples （the contents of them ranged 0.646 5-1.728 0，   0.102 6-0.290 5， 0.023 1-0.689 8， 0.018 2-0.270 7 mg/g）. CONCLUSIONS： In this study， the quality standard of C. reticulata formula granules was improved by qualitative and quantitative methods， and the contents of hesperidin， hesperetin， nobiletin and tangeretin were not less than 0.60， 0.10， 0.02 and 0.01 mg/g， respectively.

OBJECTIVE： To establish UPLC fingerprint of Fortunella margarita， and to conduct its cluster analysis and principal component analysis. METHODS： UPLC method was adopted. The determination was performed on Waters Acquity UPLC BEH C18 column with mobile phase consisted of acetonitrile-0.1％ phosphoric acid solution （gradient elution） at the flow rate of 0.3 mL/min. The detection wavelength was set at 330 nm， and sample size was 2 μL. Using fortunellin as reference， UPLC fingerprints of 8 batches of F. margarita were determined. The similarity of 8 batches of samples was evaluated by TCM Chromatographic Fingerprint Similarity Evaluation System（2012 edition） to confirm common peak. Cluster analysis and principal component analysis were performed by using SPSS 24.0 software. RESULTS： There were 24 common peaks in UPLC fingerprints of 8 batches of sample，the similarity of which was higher than 0.97. Cluster analysis showed that 8 batches of samples were clustered into 2 categories. S1， S2， S3， S4， S6， S7 and S8 were clustered into one category； S5 was clustered into the other category. By principal component analysis， the accumulative contribution rate of three main components was 81.366％. CONCLUSIONS： Established UPLC fingerprint， the results of cluster analysis and principal component analysis can provide reference for quality control of F. margarita.