| Objective:Coronary heart disease (CHD) has became a common disease thatendangers the health of all mankind. The chest pain is the common one clinicalcomplaint of CHD. But the manifestation of CHD in patients with chest pain is diverseand complex. It leads difficult for clinicians in the diagnosis and distinction. It is easilymisdiagnosed, especially for the atypical angina. CHD often complicates with multiplecoronary risk factors such as smoking, hypertension, diabetes dyslipidemia and so on.For suspected CHD patients with atypical angina, diagnostic score based on risk factorswhich relate to the simple history and a preliminary judgment of the possibility of CHDhave great significant. Coronary CT examination has a higher accuracy in diagnosis ofCHD except for coronary angiography.At present, application of coronary CTexamination is more widely in clinical practice. Coronary CT examination attracts moreand more clinician’s attention. Our aim is to establish efficient diagnostic scoring systemof predicting the prevalence of CHD in the population with atypical angina. CoronaryCT examination integrals into the diagnostic scoring system to observe its impact onapplication efficiency of the scoring system.Methods: By retrospectively studing a database of3420patients with atypicalangina and with CHD, risk factors are selected on basic of clinical factors’ study bylogistic regression analysis and then risk factors are assigned according to OR (oddsratio) values. Risk points are calculated. To analyse correlation between risk points andprevalence of CHD and between risk points and coronary artery stenosis. By calculatingthe area under the receiver operating characteristic (ROC) curve to test the applicationefficiency of diagnostic score scheme. To conduct univariate analysis for CT coronaryangiography. CT coronary angiography is assigned according to the OR value. The diagnostic score scheme takes CT coronary angiography into account. And to calculatenew the area under the ROC curve and to test the application efficiency of new scheme.Results: The prevalence of CHD is63.68%in a population of patients withatypical angina and with suspected CHD. Age, male, smoking, hypertension, diabetesmellitus and dyslipidemia are the risk factors for the population with atypical angina. Totake the first letters of six risk factors and the scoring system was named ABCDDSscheme. For diagnostic score scheme, the area under the ROC curve is0.72with a highstatistical significance. The cut-off value of diagnosis of CHD is determined andinterprets at≧4pointswith higher sensitivity and specificity(0.75and0.61,respectively). Range of points is from0to11values. The higher risk point is, thegreater prevalence of CHD in the population with atypical angina is. There is asignificant linear correlation between the risk points and prevalence of CHD in thepopulation with atypical angina. Linear equation is: y=0.81x+19.06. The higher therisk points are, the higher the average count is, the higher the average total score ofCHD and the proportion of three lesions are, but the lower the proportion of0lesion is.From0to5risk points, coronary lesions are mainly0lesions; from6to7risk points,coronary lesions are mainly1and2lesions; from9to10risk points, coronary lesionsmainly with2lesions; from8and11risk points, coronary lesions mainly with3lesions.When risk score is>6points, coronary lesions are≧1lesions.Coronary CTexamination integrals into the diagnostic scoring scheme, the area under the ROC curveincreases to0.83.Conclusions:(1) Age, male, smoking, diabetes, hypertension and dyslipidemia are risk factorsof population with atypical angina.(2) Diagnostic scoring scheme is simple and practical. It can effectively predictthe possibility of CHD of population with atypical angina. When risk score is>6points,it suggests the presence of CHD.(3) Coronary CT examination can improve the diagnostic performance of theapplication of diagnostic scoring scheme. |
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