To describe a coronary computed tomography angiography (CCTA)-adapted Leaman score (CT-LeSc) as a tool to quantify total coronary atherosclerotic burden with information regarding localization, type of plaque and degree of stenosis and to identify clinical predictors of a high coronary atherosclerotic burden as assessed by the CT-LeSc. Single center prospective registry including a total of 772 consecutive patients undergoing CCTA (Dual-source CT) from April 2011 to March 2012. For the purpose of this study, 581 stable patients referred for suspected coronary artery disease (CAD) without previous myocardial infarction or revascularization procedures were included. Pre-test CAD probability was determined using both the Diamond-Forrester extended CAD consortium method (DF-CAD consortium model) and the Morise score. Cardiovascular risk was assessed with the HeartScore. The cut-off for the 3rd tercile (CT-LeSc ≥8.3) was used to define a population with a high coronary atherosclerotic burden. The median CT-LeSc in this population (n = 581, 8,136 coronary segments evaluated; mean age 57.6 ± 11.1; 55.8 % males; 14.6 % with diabetes) was 2.2 (IQR 0-6.8). In patients with CAD (n = 341), the median CT-LeSc was 5.8 (IQR 3.2-9.6). Among patients with nonobstructive CAD, most were classified in the lowest terciles (T1, 43.0 %; T2, 36.1 %), but 20.9 % were in the highest tercile (T3). The majority of the patients with obstructive CAD were classified in T3 (78.2 %), but 21.8 % had a CT-LeSc in lower terciles (T1 or T2). The independent predictors of a high CT-LeSc were: Male sex (OR 1.73; 95 % CI 1.04-2.90) diabetes (OR 2.91; 95 % CI 1.61-5.23), hypertension (OR 2.54; 95 % CI 1.40-4.63), Morise score ≥ 16 (OR 1.97; 95 % CI 1.06-3.67) and HeartScore ≥ 5 (OR 2.42; 95 % CI 1.41-4.14). We described a cardiac CT adapted Leaman score as a tool to quantify total (obstructive and nonobstructive) coronary atherosclerotic burden, reflecting the comprehensive information about localization, degree of stenosis and type of plaque provided by CCTA. Male sex, hypertension, diabetes, a HeartScore ≥5 % and a Morise score ≥ 16 were associated with a high coronary atherosclerotic burden, as assessed by the CT-LeSc. About one fifth of the patients with nonobstructive CAD had a CT-LeSc in the highest tercile, and this could potentially lead to a reclassification of the risk profile of this subset of patients identified by CCTA, once the prognostic value of the CT-LeSc is validated.

(1) To study the prevalence and severity of coronary artery disease (CAD) in diabetic patients. (2) To provide a detailed characterization of the coronary atherosclerotic burden, including the localization, degree of stenosis and plaque composition by coronary computed tomography angiography (CCTA). Single center prospective registry including a total of 581 consecutive stable patients (April 2011-March 2012) undergoing CCTA (Dual-source CT) for the evaluation of suspected CAD without previous myocardial infarction or revascularization procedures. Different coronary plaque burden indexes and plaque type and distribution patterns were compared between patients with (n = 85) and without diabetes (n = 496). The prevalence of CAD (any plaque; 74.1 vs. 56%; p = 0.002) and obstructive CAD (≥50% stenosis; 31.8 vs. 10.3%; p < 0.001) were significantly higher in diabetic patients. The remaining coronary atherosclerotic burden indexes evaluated (plaque in LM-3v-2v with prox. LAD; SIS; SSS; CT-LeSc) were also significantly higher in diabetic patients. In the per segment analysis, diabetics had a higher percentage of segments with plaque in every vessel (2.6/13.1/7.5/10.5% for diabetics vs. 1.4/7.1/3.3/4.4% for nondiabetics for LM, LAD, LCx, RCA respectively; p < 0.001 for all) and of both calcified (19.3 vs. 9.2%, p < 0.001) and noncalcified or mixed types (14.4 vs. 7.0%; p < 0.001); the ratio of proximal-to-distal relative plaque distribution (calculated as LM/proximal vs. mid/distal/branches) was lower for diabetics (0.75 vs. 1.04; p = 0.009). Diabetes was an independent predictor of CAD and was also associated with more advanced CAD, evaluated by indexes of coronary atherosclerotic burden. Diabetics had a significantly higher prevalence of plaques in every anatomical subset and for the different plaque composition. In this report, the relative geographic distribution of the plaques within each subgroup, favored a more mid-to-distal localization in the diabetic patients.

In this population of stable patients undergoing CCTA for suspected CAD, BMI was an independent predictor of its presence, but was not correlated with the coronary disease severity.

The absence of coronary calcification is associated with an excellent prognosis. However, a calcium score of zero does not exclude the presence of coronary artery disease (CAD) or the possibility of future cardiovascular events. Our aim was to study the prevalence and predictors of coronary artery disease in patients with a calcium score of zero. Prospective registry consisted of 3,012 consecutive patients that underwent cardiac CT (dual source CT). Stable patients referred for evaluation of possible CAD that had a calcium score of zero (n = 864) were selected for this analysis. The variables that were statistically significant were included in a multivariable logistic regression model. From 864 patients with a calcium score of zero, 107 (12.4%) had coronary plaques on the contrast CT (10.8%, n = 93 with nonobstructive CAD and 1.6%, n = 14 with obstructive CAD). By logistic regression analysis, the independent predictors of CAD in this population were age >55 years [odds ratio (OR) 1.63 (1.05-2.52)], hypertension [OR 1.64 (1.05-2.56)] and dyslipidemia [OR 1.54 (1.00-2.36)]. In the presence of these 3 variables, the probability of having coronary plaques was 21%. The absence of coronary artery calcification does not exclude the presence of coronary artery disease, but the prevalence of obstructive disease is very low. In this population, the independent predictors of CAD in the setting of a calcium score of zero were hypertension, dyslipidemia, and age above 55 years. In the presence of these 3 predictors, the probability of having CAD was almost 2 times higher than in the general population.

Computerized prescription order entry has demonstrated effectiveness in eliminating medication errors related to transcribing and patient identification. Nevertheless, medication errors related to prescription and monitoring still occur. The use of clinical decision support systems and pharmacist involvement is vital to achieve maximum medication safety and reduce medication error rates.