Silent coronary artery disease in type 2 diabetes mellitus: the role of Lipoprotein(a), homocysteine and apo(a) polymorphism

BACKGROUND: There is little data on the relationship between novel cardiovascular risk factors and silent coronary artery disease (CAD) in diabetic patients. We investigated whether Lipoprotein(a), homocysteine and apolipoprotein(a) polymorphism are associated with angiographically assessed asymptomatic coronary artery disease (CAD) in diabetic patients. METHODS: 1,971 type 2 diabetic patients without clinical signs of cardiovascular diseases and with a negative history of CAD were consecutively evaluated. Among them, 179 patients showed electrocardiographic abnormalities suggestive of ischemia or previous asymptomatic myocardial infarction. These 179 patients were subjected to a non-invasive test for CAD (ECG stress testing and/or scintigraphy). Among patients with a highly positive stress testing (n = 19) or a positive scintigraphy (n = 74), 75 showed an angiographically documented CAD (CAD group). Seventy-five patients without CAD (NO CAD group) were matched by age, sex and duration of diabetes to CAD patients. In NO CAD patients an exercise ECG test, a 48-hour ambulatory ECG and a stress echocardiogram were negative for CAD. RESULTS: Lipoprotein(a) levels (22.0 ± 18.9 versus 16.0 ± 19.4 mg/dl; p < 0.05), homocysteine levels (13.6 ± 6.6 versus 11.4 ± 4.9 mmol/l; p < 0.05) and the percentage of subjects with at least one small apolipoprotein(a) isoform (70.7% versus 29.3%; p < 0.0001) were higher in CAD than NO CAD group. Logistic regression analysis showed that apolipoprotein(a) polymorphism (OR:8.65; 95%CI:3.05–24.55), microalbuminuria (OR:6.16; 95%CI:2.21–17.18), smoking (OR:2.53; 95%CI:1.05–6.08), HDL (OR:3.16; 95%CI:1.28–7.81), homocysteine (OR:2.25; 95%CI:1.14–4.43) and Lipoprotein(a) (OR:2.62; 95%CI:1.01–6.79) were independent predictors of asymptomatic CAD. CONCLUSIONS: The present investigation shows an independent association of Lipoprotein(a), homocysteine and apo(a) polymorphism with silent CAD. Other studies are needed to establish whether these parameters are suitable for CAD screening in diabetic patients

Assessing ‘no evidence of disease activity’ status in patients with relapsing–remitting multiple sclerosis: a long-term follow-up

IntroductionMultiple Sclerosis (MS) is a chronic inflammatory demyelinating disease of the CNS with an autoimmune pathogenesis. Over the years, numerous disease-modifying therapies (DMTs) have proven effective in disease control; to date, there is a need to identify a personalized treatment effective in ensuring disease-free status or no evidence of disease activity (NEDA).Objectiveidentify clinical, demographic and treatment approach characteristics that affect the maintenance of NEDA-3 and the occurrence of clinical relapses during a 6-years follow-up.Materials and methoda retrospective study was conducted on a cohort of MS patients followed up with six-year period. All participants were treated with first- or second-line MS drugs.Clinical relapse, NEDA-3 at 6 years and sustained EDSS were assessed as disease activity outcomes. Patients with follow-up of less than 6 years and insufficient clinical and radiological data were excluded from the study.ResultsTwo-hundred-eighty naive patients (mean age was 49.8 years, SD ± 11.35 years, 23–76, F/M 182/98), with MS were followed up for 6 years.The mean age at diagnosis was 34.3 years (SD ±11.5, 14–62 years), the mean EDSS score at the onset was 1.9 (±1.3), 76.8% of patients had an EDSS below or equal to 2.5 at diagnosis.In the cohort 37 (13.2%) directly received second-line treatment, 243 (86.8%) received first-line drugs.The analysis showed that second-line treatment from beginning had a protective effect for the achievement of NEDA-3 (p = 0.029), on the prevention of clinical relapse (p = 0.018) and on number of relapses (p = 0.010); this finding was confirmed by logistic regression analysis (p = 0.04) and Kaplan–Meier analysis (p = 0.034).ConclusionThe results of this study demonstrate the efficacy of targeted and early intervention so as to act in the right time window, ensuring a favorable outcome in both clinical and radiological terms; this could be decisive in reducing clinical relapse, disease progression and related disability. Therefore, prescribing highly effective drug in the early stages of the disease represents a leading strategy with the most favorable cost–benefit ratio

Temporal Data Mining for the Assessment of the Costs Related to Diabetes Mellitus Pharmacological Treatment

Diabetes care and chronic disease management represent data-intensive contexts which allow Local Healthcare Agencies (ASL) to collect a huge amount of information. Time is often an essential component of such information, given the strong importance of the temporal evolution of the considered disease and of its treatment. In this paper we show the application of a temporal data mining technique to extract temporal association rules over an integrated repository including both administrative and clinical data related to a sample of diabetic patients. We will show how the method can be used to highlight cases and conditions which lead to the highest pharmaceutical costs. Considering the perspective of a Regional Healthcare Agency, this method could be properly exploited to assess the overall standards and quality of care, while lowering costs

Lipoprotein(a), apolipoprotein(a) polymorphism and coronary atherosclerosis severity in type 2 diabetic patients

Abstract: Background: Few and conflicting data are available in the literature on the association between Lp(a) levels and the severity of coronary artery disease (CAD) in diabetic patients. In addition, no studies took into account the role of apo(a) polymorphism. The purpose of the present study was to analyse the association of the degree of coronary atherosclerosis with Lp(a) levels and apo(a) polymorphism in a large group of type 2 diabetic patients. Methods: The study population consisted of 227 consecutive type 2 diabetic patients undergoing a routine coronary angiography to evaluate chest pain or suspected CAD. The patients were subdivided into four subgroups according to the number of coronary arteries diseased: normal arteries (n = 26), mono-vessel disease (n = 67), bi-vessel disease (n = 54) and multi-vessel disease (n = 80). Results: Lp(a) levels (normal arteries: 14.6 +/- 19.6 mg/dl; mono-vessel disease: 19.0 +/- 16.4 mg/dl; bi-vessel disease: 19.3 +/- 15.1 mg/dl; multi-vessel disease: 26.5 +/- 16.8 mg/dl; p < 0.001) and the percentages of patients with at least one isoform of low molecular weight (normal arteries: 23.1%; mono-vessel disease: 38.8%; bi-vessel disease: 75.9%; multi-vessel disease: 81.2%; p < 0.001) were significantly correlated with increasing number of coronary vessels diseased. Multiple logistic regression analysis showed that both Lp(a) levels (OR: 1.31; 95% CI: 1.02-4.11) and apo(a) polymorphism (OR: 3.43; 95% CI: 1.67-7.05) were independent predictors of CAD severity. Conclusions: Our data suggest that Lp(a) levels and apo(a) polymorphism may be reliable predictors of CAD severity in type 2 diabetic patients