Journal of Cardiovascular Pharmacology and Therapeutics最新文献

Peripheral artery disease (PAD) is a severe manifestation of atherosclerosis. Patients with PAD are at heightened risk for atherothrombotic complications, including myocardial infarction and stroke (MACE); however, there is also an equal or greater risk of major adverse limb events (MALE), such as acute limb ischemia (ALI) and major amputation. Therefore, there is a need for effective medical therapies to reduce the risk of both MACE and MALE. Recent trials have demonstrated the role of thrombin inhibition in reducing the risk of MACE and MALE in PAD patients. One such medical therapy, vorapaxar, is a potent inhibitor of protease activated receptor-1 which mediates the cellular effects of thrombin. Vorapaxar, used in addition to aspirin, has demonstrated robust reductions in MACE and MALE in PAD patients. In this article, we provide a contemporary review of the current state of PAD and the role of antithrombotic medications in the treatment of PAD, as well as the current clinical data on vorapaxar and strategies to integrate vorapaxar into contemporary medical management of peripheral artery disease.

Aim: This retrospective cohort study aimed to evaluate the prognostic implications of the distinct atrial fibrillation (AF) temporal patterns: first diagnosed, paroxysmal, and persistent or permanent AF.

Methods: In this post hoc analysis of the MISOAC-AF trial (NCT02941978), a total of 1052 patients with AF (median age 76 years), discharged from the cardiology ward between 2015 and 2018, were analyzed. Kaplan-Meier and Cox-regression analyses were performed to compare the primary outcome of all-cause mortality, the secondary outcomes of stroke, major bleeding and the composite outcome of cardiovascular (CV) mortality or hospitalization among AF patterns.

Results: Of patients, 121 (11.2%) had first diagnosed, 356 (33%) paroxysmal, and 575 (53.2%) persistent or permanent AF. During a median follow-up of 31 months (interquartile range 10 to 52 months), 37.3% of patients died. Compared with paroxysmal AF, patients with persistent or permanent AF had higher mortality rates (adjusted hazard ratio (aHR), 1.37; 95% confidence interval [CI], 1.08-1.74, P = .009), but similar CV mortality or hospitalization rates (aHR, 1.09; 95% CI, 0.91-1.31, P = .35). Compared with first diagnosed AF, patients with persistent or permanent AF had similar mortality (aHR, 1.26; 95% CI, 0.87-1.82, P = .24), but higher CV mortality or hospitalization rates (aHR, 1.35; 95% CI, 1.01-1.8, P = .04). Stroke and major bleeding events did not differ across AF patterns (all P > .05).

Conclusions: In conclusion, in recently hospitalized patients with comorbid AF, the presence of persistent or permanent AF was associated with a higher incidence of mortality and morbidity compared with paroxysmal and first diagnosed AF.

Objective: This study aimed to evaluate the effects of potential risk factors on antihypertensive treatment success.

Methods: Patients with hypertension who were treated with antihypertensive medications were included in this study. Data from the last visit were analyzed retrospectively for each patient. To evaluate the predictive models for antihypertensive treatment success, data mining algorithms (logistic regression, decision tree, random forest, and artificial neural network) using 5-fold cross-validation were applied. Additionally, study parameters between patients with controlled and uncontrolled hypertension were statistically compared and multiple regression analyses were conducted for secondary endpoints.

Results: The data of 592 patients were included in the analysis. The overall blood pressure control rate was 44%. The performance of random forest algorithm (accuracy = 97.46%, precision = 97.08%, F1 score = 97.04%) was slightly higher than other data mining algorithms including logistic regression (accuracy = 87.31%, precision = 86.21%, F1 score = 85.74%), decision tree (accuracy = 76.94%, precision = 70.64%, F1 score = 76.54%), and artificial neural network (accuracy = 86.47%, precision = 83.85%, F1 score = 84.86%). The top 5 important categorical variables (predictive correlation value) contributed the most to the prediction of antihypertensive treatment success were use of calcium channel blocker (-0.18), number of antihypertensive medications (0.18), female gender (0.10), alcohol use (-0.09) and attendance at regular follow up visits (0.09), respectively. The top 5 numerical variables contributed the most to the prediction of antihypertensive treatment success were blood urea nitrogen (-0.12), glucose (-0.12), hemoglobin A1c (-0.12), uric acid (-0.09) and creatinine (-0.07), respectively. According to the decision tree model; age, gender, regular attendance at follow-up visits, and diabetes status were identified as the most critical patterns for stratifying the patients.

Conclusion: Data mining algorithms have the potential to produce predictive models for screening the antihypertensive treatment success. Further research on larger populations and longitudinal datasets are required to improve the models.

Background: Because of logistic challenges associated with the COVID-19 pandemic, direct oral anticoagulants (DOAC) were favored over warfarin in patients presenting postoperative atrial fibrillation (AF) after cardiac surgery in our institution. Considering the limited evidence supporting the use of DOAC in this context, we sought to evaluate the safety and efficacy of this practice change.

Methods: A retrospective study was performed with patients from the Quebec City metropolitan area who were hospitalized at the Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval following cardiac surgery and who required oral anticoagulant (OAC) for postoperative AF. The primary objective was to compare the pre- and peri-COVID-19 period for OAC prescribing patterns and the incidence of thrombotic and bleeding events at 3 months post-surgery. The secondary objective was to compare DOAC to warfarin in terms of thrombotic events and bleeding events.

Results: A total of 233 patients were included, 142 from the pre-COVID-19 and 91 from the peri-COVID-19 period, respectively. Both groups had equivalent proportions of preoperative AF (48%) and new-onset postoperative AF (52%). The proportion of patients treated with a DOAC increased from 13% pre-COVID-19 to 82% peri-COVID-19. This change in practice was not associated with a significant difference in the incidence of thrombotic or bleeding events 3 months postoperatively. However, compared to DOAC, warfarin was associated with a higher incidence of major bleeding. Only 1 thrombotic event was reported with warfarin, and none were reported with DOAC.

Conclusion: This study suggests that DOAC are an effective and safe alternative to warfarin to treat postoperative AF after cardiac surgery and that this practice can be safely maintained.

Background: Atrial fibrillation (AF) is the most common arrhythmia to appear in clinical practice. People with AF have 5 times the risk of stroke compared to the general population.

Objective: This study aimed to determine the prevalence of AF in people over the age of 50 without known AF, who presented to a community pharmacy to check their cardiovascular risk factors, to identify risk factors associated with AF, and to assess the risk of stroke in people who screened positive for AF.

Methods: A multicenter observational descriptive study of a screening program took place from May to December 2016. A blood pressure monitor (Microlife Watch BP Home) was used to screen for AF, and the CHA2DS2-VASc questionnaire was used to assess stroke risk.

Results: The study included 452 adults over the age of 50. The CRIFAFARMA study detected a prevalence of AF of 9.1%. Risk factors for AF were: age of 75 years or older (P = .024), lack of physical activity (P = .043), diabetes (P < .001), dyslipidemia (P = .003), and history of cardiovascular disease (P = .003). Diabetes (OR 2.79, P = .005) and dyslipidemia (OR 2.16, P = .031) had a combined explanatory capacity in the multivariable logistic regression model adjusted for age. 85% were at high risk of stroke according to the CHA2DS2-VASc scale.

Conclusions: AF was detected in more than 9% of the included population. Factors associated with AF were advanced age, lack of physical activity, diabetes, dyslipidemia, and history of cardiovascular disease, with diabetes and dyslipidemia standing out as the factors with independent explanatory capacity.