Current Pharmaceutical Design - Volume 27, Issue 10, 2021

Nowadays, most patients with congenital heart disease survive to adulthood due to advances in pediatric cardiac surgery but often present with various comorbidities and long-term complications, posing challenges in their management. The development and clinical use of risk scores for the prediction of morbidity and/or mortality in adults with congenital heart disease (ACHD) is fundamental in achieving optimal management for these patients, including appropriate follow-up frequency, treatment escalation, and timely referral for invasive procedures or heart transplantation. In comparison with other fields of cardiovascular medicine, there are relatively few studies that report prediction models developed in the ACHD population, given the small sample size, heterogeneity of the population, and relatively low event rate. Some studies report risk scores originally developed in pediatric congenital or non-congenital population, externally validated in ACHD with variable success. Available risk scores are designed to predict heart failure or arrhythmic events, all-cause mortality, post-intervention outcomes, infective endocarditis, or atherosclerosis-related cardiovascular disease in ACHD. A substantial number of these scores are derived from retrospective studies and are not internally or externally validated. Adequately validated risk scores can be invaluable in clinical practice and an important step towards personalized medicine. Multicenter collaboration, adequate study design, and the potential use of artificial intelligence are important elements in the effort to develop reliable risk scores for the ACHD population.

Diabetes mellitus (DM) is an established risk factor for atherosclerotic cardiovascular disease (CVD), and patients with DM are at a two to four-fold higher cardiovascular risk, including myocardial infraction, unstable angina, stroke, and heart failure. All of the above have arisen interest in CVD preventive strategies by the use of non-invasive methods, such as risk scores. The most common approach is to consider DM as a CVD equivalent and, therefore, to treat patients with DM in a similar way to those who required secondary CVD prevention. However, this approach has been disputed as all patients with DM do not have the same risk for CVD, and since other potentially important factors within the context of DM, such as DM duration, presence of albuminuria, and comorbidities, should be taken into consideration. Thus, the second and third approach is the application of risk models that were either developed initially for the general population or designed specifically for patients with DM, respectively. This review summarizes the evidence and implications for clinical practice regarding these scores. Up to date, several models that can be applied to the diabetic population have been proposed. However, only a few meet the minimum requirement of adequate external validation. In addition, moderate discrimination and poor calibration, which might lead to inaccurate risk estimations in populations with different characteristics, have been reported. Therefore, future research is needed before recommending a specific risk model for universal clinical practice in the management of diabetes.

Hypertrophic cardiomyopathy (HCM) has historically been linked with sudden cardiac death (SCD). Currently, it is well established that only a subset of patients is at the highest risk stratum for such a catastrophic event. Detection of patients belonging to this high-risk category can allow for timely defibrillator implantation, changing the natural history of HCM. Inversely, device implantation in patients deemed at low risk leads to an unnecessary burden of device complications with no apparent protective benefit. Previous studies have identified a series of markers, now considered established risk factors, with genetic testing and newer imaging allowing for the detection of novel, highly promising indices of increased risk for SCD. Despite the identification of a number of risk factors, there is noticeable discrepancy in the utility of such factors for risk stratification between the current American and European guidelines. We sought to systematically review the data available on these two approaches, presenting their rationale and respective predictive capacity, also discussing the potential of novel markers to augment the precision of currently used risk stratification models for SCD in HCM.

Background: Pulmonary arterial hypertension (PAH) is a serious disease with increased morbidity and mortality. The need for an individualized patient treatment approach necessitates the use of risk assessment in PAH patients. That may include a range of hemodynamic, clinical, imaging and biochemical parameters derived from clinical studies and registry data. Objective: In the current systematic review, we summarize the available data on risk prognostic models and scores in PAH and we explore the possible concordance amongst different risk stratification tools in PAH. Methods: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines aided the performance of this systematic review. Eligible studies were identified through a literature search in the electronic databases PubMed, Science Direct, Google Scholar and Cochrane with the use of various combinations of MeSH and non-MeSH terms, with a focus on PAH. Results: Overall, 25 studies were included in the systematic review; out of them, 9 were studies deriving prognostic equations and risk scores and 16 were validating studies of an existing score. The majority of risk stratification scores use hemodynamic data for the assessment of prognosis, while others also include clinical and demographic variables in their equations. The risk discrimination in the overall PAH population was adequate, especially in differentiating the low versus high-risk patients, but their discrimination ability in the intermediate groups remained lower. Current ESC/ERS proposed risk stratification score utilizes a limited number of parameters with prognostic significance, whose prognostic ability has been validated in European patient populations. Conclusion: Despite improvement in risk estimation of prognostic tools of the disease, PAH morbidity and mortality remain high, necessitating the need for the risk scores to undergo periodic re-evaluation and refinements to incorporate new data into predictors of disease progression and mortality and, thereby, maintain their clinical utility.

Peripheral artery disease (PAD) affects more than 200 million patients worldwide and chronic limbthreatening ischemia (CLTI) is the most advanced stage of PAD with very high morbidity and mortality rates. Cardiovascular medicine is trending towards a more personalized approach where each individual patient will be managed according to specific risk factors, disease characteristics, expectations related to their disease and individualized assessment of potential outcomes. For this reason, a number of risk models and scores have been developed during the last few years. Our aim in this comprehensive review article is to provide an overview of selected risk models and scores for patients with PAD and CLTI. Given that some of the published scores were of low quality (minimal discriminatory ability), we included scores that were already externally validated or scores that had promising initial findings. Available scoring systems were grouped in the five following categories according to their utility: i) scores that can detect asymptomatic patients who should be screened for PAD, ii) scores for assessment of functional status and quality of life in patients with PAD, iii) scores assessing risk for amputation and other major adverse limb events among patients with CLTI, iv) scores for the optimal revascularization strategy in each patient and scores predicting successful procedural outcomes; v) scores predicting short or long-term cardiovascular and limb related outcomes after either revascularization or at least angiographic assessment. Limitations of available scoring systems include development and validation in specific populations, lack of external validation (for some of them) and also lack of synchrony with current era endovascular technology. However, with further optimization of current scores and the development of new scores, the field of PAD and CLI can be transitioned to a personalized medicine approach.

Background: Heart failure affects a substantial proportion of the adult population, with an estimated prevalence of 1-2% in developed countries. Over the previous decades, many prediction models have been introduced for this specific population in an attempt to better stratify and manage heart failure patients. Objective: The aim of this study is the systematic review of recent, relevant literature regarding risk scores or prediction models in ambulatory patients with an established diagnosis of chronic heart failure. Methods: We conducted a systematic search of the literature in PubMed and CENTRAL from their inception up till December 2019 for studies assessing the performance of risk scores and prediction models and original research studies. Grey literature was searched as well. This review is reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. Results: We included 16 eligible studies in this systematic review. Major heart failure risk scores derived from large heart failure populations were among the included studies. Due to significant heterogeneity regarding the main endpoints, a direct comparison of the included prediction scores was inevitable. The majority referred to patients with heart failure with reduced ejection fraction, while only two out of 16 prediction scores have been developed exclusively for heart failure patients with preserved ejection fraction. Ischemic heart disease was the most common aetiology of heart failure in the included studies. Finally, more than half of the prediction scores have not been externally validated. Conclusion: Prediction models aiming at heart failure patients with a preserved or mid-range ejection fraction are lacking. Prediction scores incorporating recent advances in pharmacotherapy should be developed in the future.

Background: Atrial Fibrillation (AF) has become a major global health concern and is associated with an increased risk of poor outcomes. Identifying risk factors in patients with AF can be challenging, given the high burden of comorbidities in these patients. Risk stratification schemes appear to facilitate accurate prediction of outcomes and assist therapeutic management decisions. Objective: To summarize current evidence on risk stratification scores for patients with AF. Results: Traditional risk models rely heavily on demographics and comorbidities, while newer tools have been gradually focusing on novel biomarkers and diagnostic imaging to facilitate more personalized risk assessment. Several studies have been conducted to compare existing risk schemes and identify specific patient populations in which the prognostic ability of each scheme excels. However, current guidelines do not appear to encourage the implementation of risk models in clinical practice, as they have not incorporated new ones in their recommendations for the management of patients with AF for almost a decade. Conclusion: Further work is warranted to analyze new reliable risk stratification schemes and optimally implement them into routine clinical life.

Bacterial resistance is considered one of the most important public health problems of the century, due to the ability of bacteria to rapidly develop resistance mechanisms, which makes it difficult to treat infections, leading to a high rate of morbidity and mortality. Based on this, several options are being sought as an alternative to currently available treatments, with a particular focus on nanotechnology. Nanomaterials have important potential for use in medical interventions aimed at preventing, diagnosing and treating numerous diseases by directing the delivery of drugs. This review presents data on the use of polymeric nanoparticles having in vitro and in vivo activity against bacteria belonging to the Enterobacteriaceae family.

Background: The evolution of the pandemic has burdened the national healthcare systems worldwide and at present, there is no preferred antiviral treatment for COVID-19. Recently, the SARS-Cov-2 protease structure was released that may be exploited in in-silico studies in order to conduct molecular docking analysis.

Methods: In particular, we compared the binding of twoantimalarial drugs, already in use, (i.e. chloroquine and hydroxychloroquine), which showed some potential clinical effects on COVID-19 patients, using ritonavir, lopinavir and darunavir as positive control tree antiviral recognized compounds.

Results: Our results showed that hydroxychloroquine but not chloroquine exhibited a significant binding activity to the main protease similar to that possessed by protease inhibitors tested for other viral infections.

Conclusion: Our data suggest that hydroxychloroquine may exert additional direct antiviral activity compared to chloroquine. In the absence of clinical studies comparing the efficacy of these two compounds, hydroxychloroquine may offer additional effects and may be considered as the first choice.