Objective To assess the relationship between coronary plaques and risk factor of coronary heart disease in a asymptomatic population.Methods A total of 604 in-patients who received coronary computerized tomography angiography (CCTA) during January 1 th,2010 and April 1 th,2011 were enrolled in this study and assigned to the non-lesion group (0),mild lesion group (0 ＜ score ≤ 5) andmoderate-severe lesion group (＞ 5) according to the third quartile of CCTA score.Clinical data including physical examination,laboratory test,ultrasound sonogram and discharge diagnoses were collected and compared between the groups.Multivariable linear regression and bivariate logistic regression were performed to find out the main risk factors of coronary heart disease.ROC curve was drawn to estimate the diagnostic value of coronary lesions.Results There were 240 individuals in the non-lesion group,271 in the mild lesion group,93 in the moderate-severe lesion group.Multivariable linear regression indicated Y =-6.56 +3.22 × mean carotid intima-media thickness (cIMT) + 1.106 × male + 0.597 × low-density lipoprotein cholesterol (LDL-C) + 0.116 × age-1.596 × high-density lipoprotein cholesterol (HDL-C).Bivariate logistic regression and ROC curve showed that mean cIMT was the main risk factor of coronary heart disease (odds ratio (OR) =7.19,ROC =0.730,P=0.00,95％ confidence interval (CI):0.68 to 0.78).Furthermore,major coronary lesions were located in the LAD (20.8％) and was soft plaque (42.5％).Conclusion In this investigation,60.2％ of the asymptomatic patients showed plaques in CCTA.Age,cIMT,LDL-C and HDL-C may be predictive to moderate to severe coronary artery lesions.

OBJECTIVETo investigate the correlation between the findings by coronary computed tomography angiography (CCTA) and the risk factors for major adverse cardiac events (MACE).

METHODSThis cohort study involved 706 out-patients who received examination with CCTA between June, 2008 and April, 2011. The severity of coronary artery disease (CAD) was graded to normal, mild, moderate, severe, and revascularization. Pearson correlation analysis and ANOVA were used to evaluate the relationship between the risk factors for CAD and coronary plaques identified by CCTA, and the predictive accuracy was determined by the receiver-operating characteristic (ROC) curve.

RESULTSOf the 706 patients, 58.63% were found to have abnormal CCTA findings. A older age, hypertension, hyperlipidemia, diabetes mellitus, cerebral infarction, CAD, and myocardial infarction were associated with an significantly increased incidence of coronary plaques (P<0.01). The Framingham score, LDL, HCY, IMT, HDL and TC were also significantly correlated with the severity of the coronary plaques (P<0.05). The ROC curves showed that Framingham risk score (0.845), Cr (0.766), HCY (0.697), IMT (0.693) and HDL (0.316) had greater predictive value for the occurrence of coronary plaques (P<0.001).

CONCLUSIONThe Framingham risk score, Cr, HCY, IMT and HDL are validated by CCTA as the major coronary risk factors and can be used for screening of CAD.

Aged ; Coronary Angiography ; methods ; Coronary Artery Disease ; diagnostic imaging ; Cross-Sectional Studies ; Female ; Humans ; Male ; Middle Aged ; Risk Factors ; Tomography, Spiral Computed ; Tomography, X-Ray Computed ; methods

Objective To establish an online quantitative analysis model for moisture content assay of hydroxychloroquine sulfate particles by near infrared (NIR) spectroscopy. Methods The NIR spectra were collected in real time when the material particles were dried in the fluidized bed. Meanwhile the water content of the particles was measured with the standard moisture tester. The multiplicative signal correction (MSC) and first derivative followed by Karl Norris smoothing were used for spectra pretreatment. Two spectral range (4 935−5 336 cm⁻¹ and 6 911−7 297 cm⁻¹) were selected for the quantitative model with the partial least squares (PLS) regression. Results The quantitative calibration model had good correlation coefficients with Rc value=0.952 9 and Rp value=0.936 6. The root mean square error of calibration (RMSEC) was 0.408 and the root mean square error of prediction error (RMSEP) was 0.435. The ratio of standard deviation of validation set to prediction standard deviation (RPD) was 5.18. There was no significant difference between the predicted value and the reference value by t test when the established model was applied in large-scale production. Conclusion The online model established for monitoring water content has high accuracy and stability, which can be applied in industrial scale process to monitor the particle moisture in real time.