Falling Coronary Heart Disease Rates: A Better Explanation?

Precision Medicine Approaches in Cardiology and Personalized Therapies for Improved Patient Outcomes: A systematic review

Personalized medicine is a novel and rapidly evolving approach to clinical practice that involves making decisions about disease prediction, prevention, diagnosis, and treatment by utilizing modern technologies. The concepts of precision medicine have grown as a result of ongoing developments in genomic analysis, molecular diagnostics, and technology. These advancements have enabled a deeper understanding and interpretation of the human genome, allowing for a personalized approach to clinical care. The primary objective of this research is to assess personalized medicine in terms of its indications, advantages, practical clinical uses, potential future directions, problems, and effects on healthcare. An extensive analysis of the scientific literature regarding this topic demonstrated the new medical approach's relevance and usefulness, as well as the fact that personalized medicine is becoming increasingly prevalent in various sectors. The online, internationally indexed databases PubMed and Cochrane Reviews were used to conduct searches for and critically evaluate the most relevant published research including original papers and reviews in the scientific literature. The findings suggest that precision medicine has a lot of potential and its implementation lowers the incidence of stroke as well as coronary heart disease and improves patient health in cardiology.

Atherogenic index of plasma and coronary artery disease: A systematic review

Various studies suggest that the atherogenic index of plasma (AIP) is associated with the risk of coronary artery disease (CAD) in different clinical scenarios. This review aimed to synthesize evidence of the association between AIP values and CAD. A literature search was carried out on four databases, namely, PubMed, Scopus, Web of Science, and Ovid-Medline. A handsearch was performed on preprint repositories (MedRxiv and Research Square). The effect measurements were expressed as odds ratios (OR) with their corresponding 95% confidence intervals (CI). For the quantitative synthesis, we employed a random-effects model. We analyzed 14 articles (with 40,902 participants) from seven different countries. The quantitative analysis revealed that an increase in one unit of AIP was associated with higher odds of developing CAD (OR 2.11; 95% CI 1.65-2.69; P < 0.001; I ² = 98%). We conducted subgroup analyses of Chinese (OR 1.89; 95% CI 1.40-2.56; P < 0.001) and non-Chinese studies (OR 2.51; 95% CI 1.42-4.42; P < 0.001). The sensitivity analysis by risk of bias continued to demonstrate an association, and the heterogeneity remained unchanged (OR 1.75; 95% CI 1.33-2.31; P < 0.001; I ² = 98%). Higher AIP values were associated with higher odds of developing CAD.

Population-Based Recalibration of the Framingham Risk Score and Pooled Cohort Equations

BACKGROUND

The Framingham Risk Score (FRS) and Pooled Cohort Equations (PCEs) overestimate risk in many contemporary cohorts.

OBJECTIVES

This study sought to determine if recalibration of these scores using contemporary population-level data improves risk stratification for statin therapy.

METHODS

Five-year FRS and PCEs were recalibrated using a cohort of Ontario residents alive January 1, 2011, who were 30 to 79 years of age without cardiovascular disease. Scores were externally validated in a primary care cohort of routinely collected electronic medical record data from January 1, 2010, to December 31, 2014. The relative difference in mean predicted and observed risk, number of statins avoided, and number needed to treat with statins to reduce a cardiovascular event at 5 years were reported.

RESULTS

The FRS was recalibrated in 6,938,971 Ontario residents (51.6% women, mean age 48 years) and validated in 71,450 individuals (56.1% women, mean age 52 years). Recalibration reduced overestimation from 109% to 49% for women and 131% to 32% for men. The recalibrated FRS was estimated to reduce statin prescriptions in up to 26 per 1,000 low-risk women and 80 per 1,000 low-risk men, as well as reduce the number needed to treat from 61 to 47 in women and from 53 to 41 in men. In contrast, after recalibration of the PCEs, risk remained overestimated by 217% in women and 128% in men.

CONCLUSIONS

Recalibration is a feasible solution to improve risk prediction but is dependent on the model being used. Recalibration of the FRS but not the PCEs reduced overestimation and may improve utilization of statins.

Nonadherence to Statins and Antihypertensives and Hospitalizations Among Elderly Medicare Beneficiaries With Incident Cancer

Background: Incident cancer diagnosis may increase the risk of coronary artery disease (CAD)-related hospitalizations, especially in older individuals. Adherence to statins and/or angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin II receptor blockers (ARBs)/β-blockers reduces CAD-related hospitalizations. This study examined the relationship between medication adherence and CAD-related hospitalizations immediately following cancer diagnosis. Patients and Methods: A retrospective observational longitudinal study was conducted using SEER-Medicare data. Elderly Medicare fee-for-service beneficiaries with preexisting CAD and incident breast, colorectal, or prostate cancer (N=12,096) were observed for 12 months before and after cancer diagnosis. Hospitalizations measured every 120 days were categorized into CAD-related hospitalization, other hospitalization, and no hospitalization. Medication adherence was categorized into 5 mutually exclusive groups: adherent to both statins and ACEIs/ARBs/β-blockers (reference group), not adherent to both statins and ACEIs/ARBs/β-blockers, adherent to either statins or ACEIs/ARBs/β-blockers, use of one medication class and adherent to that class, and use of one medication class and not adherent to that class. The relationship between medication adherence and hospitalization was analyzed using repeated measures multinomial logistic regressions. Inverse probability treatment weights were used to control for observed group differences among medication adherence categories. Results: Adherence to both statins and ACEIs/ARBs/β-blockers was estimated at 31.2% during the 120-day period immediately following cancer diagnosis; 13.7% were not adherent to both medication classes during the same period, and 27.4% had CAD-related hospitalizations immediately after cancer diagnosis, which declined to 10.6% during the last 4 months of the postdiagnosis period. In the adjusted analyses, those not adherent to both statins and ACEIs/ARBs/β-blockers were more likely to have CAD-related hospitalization compared with those adherent to both medication classes (adjusted odds ratio, 1.82; 95% CI, 1.72-1.92; P<.0001). Conclusions: Given the complexity of interaction between CAD and cancer, it is important to routinely monitor medication adherence in general clinical practice and to provide linkages to support services that can increase medication adherence.

Precision medicine in cardiology

The cardiovascular research and clinical communities are ideally positioned to address the epidemic of noncommunicable causes of death, as well as advance our understanding of human health and disease, through the development and implementation of precision medicine. New tools will be needed for describing the cardiovascular health status of individuals and populations, including 'omic' data, exposome and social determinants of health, the microbiome, behaviours and motivations, patient-generated data, and the array of data in electronic medical records. Cardiovascular specialists can build on their experience and use precision medicine to facilitate discovery science and improve the efficiency of clinical research, with the goal of providing more precise information to improve the health of individuals and populations. Overcoming the barriers to implementing precision medicine will require addressing a range of technical and sociopolitical issues. Health care under precision medicine will become a more integrated, dynamic system, in which patients are no longer a passive entity on whom measurements are made, but instead are central stakeholders who contribute data and participate actively in shared decision-making. Many traditionally defined diseases have common mechanisms; therefore, elimination of a siloed approach to medicine will ultimately pave the path to the creation of a universal precision medicine environment.