Biomedical subjects

Lorenzo Gerosa

Publications and source records attributed to Lorenzo Gerosa.

4 recordsLinked to original sources

PubMed2006

Measurement of carotid artery intima-media thickness in dyslipidemic patients increases the power of traditional risk factors to predict cardiovascular events.

A longitudinal observational study investigated whether the measurement, in clinical practice, of carotid maximum intima-media thickness (Max-IMT) could be combined with the Framingham risk score (FRS) to improve the predictability of cardiovascular events in dyslipidemic patients who are at low or intermediate risk. Max-IMT was measured by ultrasound in 1969 patients attending a lipid clinic. The "best threshold values" (BTVs) above which we considered the Max-IMT to be abnormally high were calculated for our dyslipdemic population for each 10-year age interval in men and women. Two hundred and forty-two patients (age 54+/-10 years; 43.8% women) with an FRS <20%, i.e. at low or intermediate risk, were monitored for more than 5 years. Twenty-four of these patients suffered a cardiovascular event within 5.1+/-2.3 years. Both FRS and Max-IMT proved to be independent outcome predictors (p<0.04, both), with a hazard ratio (HR) of 6.7 (95% CI 1.43, 31.04; p=0.015) in patients in whom FRS was 10-20% and Max-IMT was above the BTV (60th percentile of Max-IMT distribution for men or 80th for women). In Kaplan-Meier analysis, the Max-IMT significantly improved the predictive value of the FRS (chi(2)=8.13, p=0.04). Patients with FRS 10-20% (currently considered intermediate-risk) and also elevated Max-IMT values came into the same high-risk category as patients with FRS 20-30%. The combination of FRS with Max-IMT measurement can be used in routine clinical practice to greatly enhance the predictability of cardiovascular events in the large number of patients who fall into the intermediate-risk category, which currently does not call for aggressive preventive measures.

Adult↗

PubMed2005

Correlation of parents' longevity with carotid intima-media thickness in patients attending a Lipid Clinic.

The relationship between carotid intima-media thickness (IMT) and the subject's parents' longevity has been investigated. The association between parents' age at death and IMT was estimated in 593 consecutive patients attending a Lipid Clinic by survival-analysis methods. Average maximum IMT (Avg-IMT), maximum IMT (Max-IMT), clinical and laboratory variables and parental age at death, were assessed. Kaplan-Meier analyses showed significant differences in survival curves, low IMTs being associated with long-lived parents (p=0.0003 and 0.001 by log-rank test for fathers and mothers, respectively). A Cox proportional hazards regression model showed that higher carotid IMT values were associated with father's and mother's deaths at an early age, even after adjusting for conventional cardiovascular risk factors. These data were confirmed after the stratification of patients into younger (<65 y) and older (>/=65 y) or into subjects with and without a family history of dyslipidemia or vascular diseases. In addition, by stratifying subjects into those with no, one or two long-lived parents, we observed a significant trend for the combination of father's and mother's longevity on their offspring's IMTs (p<0.01 and 0.05 for Avg-IMT and Max-IMT, respectively). These data highlight a significant relationship between carotid artery IMT and a familial predisposition to be long-lived that is independent of the individual's vascular risk profile.

Adolescent↗

PubMed2004

Statins effect on smooth muscle cell proliferation.

Clinical trials have firmly established that 3-hydroxy-3-methylglutaryl-coenzyme-A reductase inhibitors (statins) can induce regression of vascular atherosclerosis as well as reduction of cardiovascular-related morbidity and death in patients with and without coronary artery disease. These beneficial effects of statins are usually assumed to result from their ability to reduce cholesterol synthesis. However, because mevalonic acid is the precursor not only of cholesterol but also of many nonsteroidal isoprenoid compounds, inhibition of 3-hydroxy-3-methylglutaryl-coenzyme-A reductase may result in pleiotropic effects. Indeed, statins can interfere with major events involved in the formation and the evolution of atherosclerotic lesions, such as arterial myocyte migration and proliferation and cholesterol accumulation, independent of their hypolipidemic properties. The aim of this article is to focus on clinical and experimental data that show that statins possess effects beyond cholesterol lowering, particularly on arterial smooth muscle cell proliferation. The contribution of these direct vascular effects to the reduction of cardiovascular events observed in clinical trials with statins represents one of the major challenges for future studies to understand the antiatherosclerotic benefits of these agents.

Animals↗

PubMed2004

Recognition of patients with cardiovascular disease by artificial neural networks.

BACKGROUND: Artificial neural networks (ANNs) are computer algorithms inspired by the highly interactive processing of the human brain. When exposed to complex data sets, ANNs can learn the mechanisms that correlate different variables and perform complex classification tasks. AIMS: A database, of 949 patients and 54 variables, was analysed to evaluate the capacity of ANNs to recognise patients with (VE+, n = 196) or without (VE-, n = 753) a history of vascular events on the basis of vascular risk factors (VRFs), carotid ultrasound variables (UVs) or both. METHOD: The performance of ANN was assessed by calculating the percentage of correct identifications of VE+ and VE- patients (sensitivity and specificity, respectively) and the prediction accuracy (weighted mean between sensitivity and specificity). RESULTS: The results showed that ANNs can be trained to identify VE+ and VE- subjects more accurately than discriminant analyses. When VRFs and UVs were used as input variables, the prediction accuracies of the ANN providing the best results were 80.8% and 79.2%, respectively. The addition of gender, age, weight, height and body mass index to UVs increased accuracy of prediction to 83.0%. When the ANNs were allowed to choose the relevant input data automatically (I.S. system-Semeion), 37 variables were selected among 54, five of which were UVs. Using this set of variables as input data, the performance of the ANNs in the classification task reached a prediction accuracy of 85.0%. with the 92.0% correct classification of VE+ patients. CONCLUSIONS: Artificial neural network technology is highly promising in the development of accurate diagnostic tools designed to recognize patients at high risk of cardiovascular diseases.

Adult↗