<strong>Background:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> Stroke is the second leading cause of death in the world and ...<strong>Background:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> Stroke is the second leading cause of death in the world and the third due to disability. However, there are few data available that identify the risk factors associated with it and their weight in different populations (population risk). </span><b><span style="font-family:Verdana;">Aim: </span></b><span style="font-family:Verdana;">Contribute to the knowledge of burden risk factors in stroke </span></span><span style="font-family:Verdana;">in a large cohort of Southern Italy</span><span style="font-family:;" "=""><span style="font-family:Verdana;">. </span><b><span style="font-family:Verdana;">Methods</span></b><span style="font-family:Verdana;">: The data refer to a randomized Campania cohort of 1200 subjects (35</span></span><span style="font-family:Verdana;"> </span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;"> </span><span style="font-family:;" "=""><span style="font-family:Verdana;">74 years) enrolled in 2008-09. Ten years later (2018-19) they were re-evaluated. We analyzed data from 32 patients who reported a cerebrovascular event (stroke or TIA) with the event-free group of subjects (804 subjects: 378 men and 426 women). We evaluated: absolute risk, Odds Ratio (OR), Additional Risk (AR), Risk Attributable to the Population (PAR) and, finally, the Population Attributable risk Fraction (FAP). </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> In the comparison between the two groups (patients with events and patients without events) the risk factors with statistically significant differences were: age, Systolic Blood Pressure (SBP), BMI, cholesterol, triglycerides, glycemia and hyperinsulinemia. The ORs with the greatest impact were: blood glucose (5.1), BMI (3.3) and BPS (2.9). Linear regression analysis identified Glycemia and BMI as the only independent variables. The FAPs with the greatest impact were SBP (47.4%) and BMI (42.6%展开更多
文摘<strong>Background:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> Stroke is the second leading cause of death in the world and the third due to disability. However, there are few data available that identify the risk factors associated with it and their weight in different populations (population risk). </span><b><span style="font-family:Verdana;">Aim: </span></b><span style="font-family:Verdana;">Contribute to the knowledge of burden risk factors in stroke </span></span><span style="font-family:Verdana;">in a large cohort of Southern Italy</span><span style="font-family:;" "=""><span style="font-family:Verdana;">. </span><b><span style="font-family:Verdana;">Methods</span></b><span style="font-family:Verdana;">: The data refer to a randomized Campania cohort of 1200 subjects (35</span></span><span style="font-family:Verdana;"> </span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;"> </span><span style="font-family:;" "=""><span style="font-family:Verdana;">74 years) enrolled in 2008-09. Ten years later (2018-19) they were re-evaluated. We analyzed data from 32 patients who reported a cerebrovascular event (stroke or TIA) with the event-free group of subjects (804 subjects: 378 men and 426 women). We evaluated: absolute risk, Odds Ratio (OR), Additional Risk (AR), Risk Attributable to the Population (PAR) and, finally, the Population Attributable risk Fraction (FAP). </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> In the comparison between the two groups (patients with events and patients without events) the risk factors with statistically significant differences were: age, Systolic Blood Pressure (SBP), BMI, cholesterol, triglycerides, glycemia and hyperinsulinemia. The ORs with the greatest impact were: blood glucose (5.1), BMI (3.3) and BPS (2.9). Linear regression analysis identified Glycemia and BMI as the only independent variables. The FAPs with the greatest impact were SBP (47.4%) and BMI (42.6%
