Search

Introduction and objectives Two particular polymorphisms, namely PON1-192 and PON2-311, in the genes encoding the antioxidant enzymes paraoxonase-1 (PON1) and paraoxonase-2 (PON2) have been associated with an increased risk of acute myocardial infarction (AMI). However, previous findings have been contradictory. The aim of this study was to investigate the association between the PON1-192 and PON2-311 polymorphisms and their interaction on AMI risk. Methods This case-control study involved 746 consecutive AMI patients and 1796 control subjects without cardiovascular disease, who were randomly selected from the same population from which the patients came. All participants were recruited between 1999 and 2000 from four Spanish autonomous regions. All were assessed for the presence of PON1-192 and PON2-311 and for classical cardiovascular risk factors. Multivariate analysis was carried out using logistic regression modeling. Results The odds ratios (OR) of AMI for patients with the PON1-192 QQ and PON2-311 SS genotypes (who comprised 50% and 66% of the population, respectively) were 1.26 (95% confidence interval [Cl], 1.02-1.55) and 1.25 (95% Cl, 1.04-1.50), respectively, compared with R and C allele carriers. Moreover, in patients with both QQ and SS genotypes, the adjusted OR of AMI increased to 1.41 (95% Cl, 1.13-1.76). Conclusiones Our results indicate that the PON1-192 and PON2-311 polymorphisms were independent risk factors of AMI in our population.

Introduction and objectives Generally, cardiovascular risk factors are poorly controlled after myocardial infarction. The objective of this study was to determine the effect of these risk factors on long-term morbidity and mortality in patients experiencing a myocardial infarction. Methods In total, 655 acute myocardial infarction survivors recorded in the IBERICA database for the Spanish province of Albacete were followed up. Provincial healthcare center databases and the regional death registry were consulted, and semistructured interviews were carried out. Bivariate and multivariate descriptive and comparative statistical analyses were performed. Results The median follow-up period was 5.5 years. At the end of the study, 74% of patients had hypertension or hypercholesterolemia, 39% had diabetes, 36% were obese, 13% smoked, and 1% were alcoholics. Overall, 48% of patients experienced a cardiovascular event. Uncontrolled hypercholesterolemia was found to be a risk factor for angina (odds ratio [OR], 2.4, 95% confidence interval [CI], 1.1-5.1), and uncontrolled diabetes was a risk factor for reinfarction (OR, 3.5, 95% CI, 1.6-7.6) and stroke (OR, 10.6, 95% CI, 3.6-31.2), both of which occurred earlier in patients with uncontrolled diabetes. In total, 115 (18%) patients died, with more than 50% of deaths being due to cardiovascular causes. Uncontrolled hypertension and diabetes were the most important risk factors for both overall and early mortality, whereas controlled hypercholesterolemia appeared to be a protective factor. Conclusions The prevalence of cardiovascular risk factors in patients who have experienced a myocardial infarction is very high. Control of these risk factors influences both cardiovascular events and long-term mortality.

Introduction and objectives Analysis of the effect of treatment in observational studies is complex due to differences between treated and nontreated patients. Calculating the probability of receiving treatment conditioned on relevant covariates (propensity score [PS]) has been proposed as a method to control for these differences. We report an application of PS to assess the association between reperfusion treatment and 28-day case fatality in patients with acute myocardial infarction (AMI). Method We describe the procedure used to calculate PS for receiving reperfusion treatment, and different strategies to analyze the association between PS and case fatality with regression modeling and matching. Data were from a population-based registry of 6307 patients with AMI in Spain during 1997–98. Results The PS for reperfusion was calculated in 5622 patients. In the multivariate analysis, reperfusion was associated with lower case fatality (OR=0.59; 95% confidence interval [95% CI], 0.46–0.77). When PS was included as a covariate, this association became non-significant (OR=0.76; 95% CI, 0.57–1.01). In the subgroup of matched patients with a similar PS (n=3138), treatment was not associated with case fatality (OR=0.95; 95% CI, 0.72–1.26). When the influence of cases with missing data on PS was controlled for, reperfusion treatment was associated with lower fatality (OR=0.66; 95% CI, 0.55–0.80). Conclusions Calculating propensity score is a method that controls for differences between treated and nontreated patients. This score has limitations when matching is incomplete and when data are missing. Results of the present example suggest that reperfusion treatment reduces AMI case fatality.