Adverse drug reactions in patients with cardiovascular disease

Research hotspots and emerging trends of mesenchymal stem cells in cardiovascular diseases: a bibliometric-based visual analysis

Background

Mesenchymal stem cells (MSCs) have important research value and broad application prospects in cardiovascular diseases (CVDs). However, few bibliometric analyses on MSCs in cardiovascular diseases are available. This study aims to provide a thorough review of the cooperation and influence of countries, institutions, authors, and journals in the field of MSCs in cardiovascular diseases, with the provision of discoveries in the latest progress, evolution paths, frontier research hotspots, and future research trends in the regarding field.

Methods

The articles related to MSCs in cardiovascular diseases were retrieved from the Web of Science. The bibliometric study was performed by CiteSpace and VOSviewer, and the knowledge map was generated based on data obtained from retrieved articles.

Results

In our study, a total of 4,852 publications launched before August 31, 2023 were accessed through the Web of Science Core Collection (WoSCC) database via our searching strategy. Significant fluctuations in global publications were observed in the field of MSCs in CVDs. China emerged as the nation with the largest number of publications, yet a shortage of high-quality articles was noted. The interplay among countries, institutions, journals and authors is visually represented in the enclosed figures. Importantly, current research trends and hotspots are elucidated. Cluster analysis on references has highlighted the considerable interest in exosomes, extracellular vesicles, and microvesicles. Besides, keywords analysis revealed a strong emphasis on myocardial infarction, therapy, and transplantation. Treatment methods-related keywords were prominent, while keywords associated with extracellular vesicles gathered significant attention from the long-term perspective.

Conclusion

MSCs in CVDs have become a topic of active research interest, showcasing its latent value and potential. By summarizing the latest progress, identifying the research hotspots, and discussing the future trends in the advancement of MSCs in CVDs, we aim to offer valuable insights for considering research prospects.

Potentially Harmful Drug-Drug Interactions and Their Associated Factors Among Hospitalized Cardiac Patients: A Cross-Sectional Study

BACKGROUND

Cardiovascular diseases are responsible for a significant proportion of mortalities worldwide. Elderly patients are the most affected by cardiovascular diseases, and because of factors such as polypharmacy, multimorbidity, and age-related changes in drug availability and metabolism, they are highly susceptible to the occurrence of drug-drug interactions. Drug-drug interactions are among the many drug-related problems leading to negative outcomes among inpatients and outpatients. Thus, it is important to investigate the prevalence, involved drugs, and factors related to potential drug-drug interactions (pDDIs) to properly optimize pharmacotherapy regimens for these patients.

OBJECTIVE

We aimed to determine the prevalence of pDDIs, drugs most frequently implicated, and significant predictors associated with these interactions among hospitalized patients in the Cardiology Unit at Sultan Qaboos University Hospital in Muscat, Oman.

METHODS

This retrospective cross-sectional study included 215 patients. Micromedex Drug-Reax® was used to identify pDDIs. Data extracted from patients' medical records were collected and analyzed. Univariable and multivariable linear regression was applied to determine the predictors associated with the observed pDDIs.

RESULTS

A total of 2057 pDDIs were identified, with a median of nine (5-12) pDDIs per patient. Patients with at least one pDDI accounted for 97.2% of all the included patients. The majority of pDDIs were of major severity (52.6%), fair level of documentation (45.5%), and pharmacodynamic basis (55.9%). Potential drug-drug interactions between atorvastatin and clopidogrel were the most frequently observed (9%). Of all the detected pDDIs, around 79.6% of them included at least one antiplatelet drug. Having diabetes mellitus as a comorbidity (B = 2.564, p < 0.001) and the number of drugs taken during the hospitalization period (B = 0.562, p < 0.001) were factors positively associated with the frequency of pDDIs.

CONCLUSIONS

Potential drug-drug interactions were highly prevalent among hospitalized cardiac patients at Sultan Qaboos University Hospital, Muscat, Oman. Patients having diabetes as a comorbidity and with a high number of administered drugs were at a higher risk of an increased number of pDDIs.

Protective Effects of Phenylpropanoids and Phenylpropanoid-rich Essential Oils on the Cardiovascular System

BACKGROUND

Cardiovascular diseases are the leading cause of global mortality with a tendency to increase due to population ageing as well as an increase in associated risk factors. Although current therapies improve survival rates, they are associated with several side effects, thus justifying the development of novel preventive and/or therapeutic approaches. In this way, plant metabolites such as essential oils have emerged as promising agents due to their biological effects.

OBJECTIVE

Bearing in mind that several essential oils are characterized by high amounts of phenylpropanoids, which may play a crucial role in the activity of these volatile extracts, a comprehensive and systematic review focusing on the cardiovascular effects of phenylpropanoid-rich essential oils is presented.

METHODS

Popular search engines including PubMed, Science Direct, Scopus and Google Scholar were consulted and papers from 2000 onwards were selected. Non-volatile phenylpropanoids were not considered in this review.

RESULTS

A compilation of the current knowledge on this thematic pointed out beneficial effects for volatile phenylpropanoids namely hypotensive, vasorelaxant, antiplatelet aggregation, antidyslipidaemic and antidiabetic, as well as protective properties against ischemia/reperfusion injury and heart hypertrophy.

CONCLUSION

A better understanding of the protective effects of phenylpropanoids on the cardiovascular system is presented, thus paving the way towards future research on plant-based therapies for cardiovascular diseases.

Onco-cardiology: Drug-drug interactions of antineoplastic and cardiovascular drugs

Cardiovascular diseases (CVD) and cancer are still the leading causes of death. There are many common etiologic factors, especially smoking and obesity. Therefore, it is not uncommon for CVD and cancer to coexist. Drug-drug interactions (DDIs) inevitably occur in this group of patients, where polypharmacy is increasing due to older age and multiple comorbidities. However, multidisciplinary studies, especially close collaboration of medical oncologists and cardiologists, who deals with the diagnosis and treatment of these diseases, awareness and preventive approaches to DDIs may reduce serious morbidity and mortality. In this review, information about the common treatments used in cardiology and oncology and possible DDIs are discussed.

Adverse drug reactions caused by drug-drug interactions in cardiovascular disease patients: introduction of a simple prediction tool using electronic screening database items

Objective: Cardiovascular disease (CVD) drugs have been frequently implicated in adverse drug reaction (ADR)-related hospitalizations. Drug-drug interactions (DDIs) are common preventable cause of ADRs, but the impact of DDIs in the CVD population has not been investigated. Hence, the primary aim of the study was to identify DDIs associated with ADRs in CVD patients at hospital admission. The second aim was to develop a simple tool to identify high-risk patients for DDI-related adverse events. Methods: An observational study was conducted on the Cardiology Ward of University Clinical Hospital Center. Data were obtained from medical charts. A clinical panel identified DDIs implicated in ADRs, using LexiInteract database and Drug Interaction Probability Scale. Statistics were performed using PASW 22 (SPSS Inc.). Results: DDIs contributed to hospital admission with a total prevalence of 9.69%. DDI-related ADRs affected mainly cardiac function (heart rate or rhythm, 41.07%); bleeding and effect on blood pressure were equally distributed (17.86%). Non-cardiovascular ADRs were found in 23.21% of DDIs. After admission, 73% of the identified DDIs led to changes in prescription. Prediction ability of calculated DDI adverse event probability scores was rated as good (AUC = 0.80, p < .001). Conclusions: CVD patients are highly exposed to adverse DDIs; about one in ten patients hospitalized with CVD might have a DDI contributing to the hospitalization. Given the high prevalence of CVD, DDI-related harm might be a significant burden worldwide. Identification of patients with high DDI adverse event risk might ease the recognition of DDI-related harm and improve the use of electronic databases in clinical practice.

The role of the clinical pharmacist in the prevention of potential drug interactions in geriatric heart failure patients

Background The treatment of heart failure patients is very complex and includes lifestyle modification as well as different pharmacological therapies. Polypharmacy is very common in such patients and they are at increased risk of potential drug-drug interactions and associated effects such as poor adherence, compliance and adverse events. Objective The aim of the present study is to investigate retrospectively the prescribed pharmacotherapy of the hospital discharged heart failure patients for possible drug interactions. Settings Clinic for Cardiology of the "Saint Marina" University Hospital in Varna, Bulgaria. Method Lexicomp^® Drug interaction software was used for screening potential drug-drug interactions. Logistic regression was applied to determine the odds ratio for the association between the age and number of drugs taken and the number of potential drug-drug interactions. Main outcome measure Incidence and type of pDDIs in geriatric heart failure patients. Results A retrospective study was conducted by reviewing the medical records of 248 selected heart failure patients for the prescribed medicines for a 1-year period (January 2015-December 2015). The total number of potential drug-drug interactions was 1532, or approximately 6.28 (± 4.72 SD) per one person. The range of prescribed drugs was between three and fourteen, 92% of them have been taking more than five medicines, an average of 7.12 (± 2.07 SD) per patient. The average age was 72.35 (± 10.16 SD). The results have shown stronger association between the number of drugs taken (more than 7) and the occurrence of potential drug-drug interactions (more than 10)-37.84 (95% CI 9.012-158.896, P ≤ 0.001). No statistically significant differences were found between age and occurrence of potential drug-drug interactions (more than 10)-1.008 (95% CI 0.441-2.308, P = 0.848). Conclusion The incidence of drug-drug interactions in heart failure patients is high. The clinical pharmacist, as a part of the multidisciplinary team, could reduce medication-related problems, such as drug interactions, and to optimize drug therapy by checking the treatment prescribed at the discharge of these patients.

Adverse Drug Reaction-Related Hospitalizations in Elderly Australians: A Prospective Cross-Sectional Study in Two Tasmanian Hospitals

INTRODUCTION

Adverse drug reactions (ADRs) have been commonly cited as a major cause of hospital admissions in older individuals. However, despite the apparent magnitude of this problem, there are limited prospective data on ADRs as a cause of hospitalization in elderly medical patients.

OBJECTIVES

The objective of this study was to evaluate the proportion, clinical characteristics, causality, severity, preventability, and outcome of ADR-related admissions in older patients admitted to two Tasmanian hospitals.

METHODS

We conducted a prospective cross-sectional study at the Royal Hobart and Launceston General Hospitals in Tasmania, Australia. A convenience sample of patients, aged 65 years and older, undergoing unplanned overnight medical admissions was screened. ADR-related admissions were determined through expert consensus from detailed review of medical records and patient interviews. The causality, preventability and severity of each ADR-related admission were assessed.

RESULTS

Of 1008 admissions, the proportion of potential ADR-related medical admissions was 18.9%. Most (88.5%) ADR-related admissions were considered preventable. Cardiovascular complaints (29.3%) represented the most common ADRs, followed by neuropsychiatric (20.0%) and renal and genitourinary disorders (15.2%). The most frequently implicated drug classes were diuretics (23.9%), agents acting on the renin angiotensin system (16.4%), β-blocking agents (7.1%), antidepressants (6.9%), and antithrombotic agents (6.9%). Application of the Naranjo algorithm found 5.8% definite, 70.1% probable, and 24.1% possible ADRs. ADR severity was rated moderate and severe in 97.9% and 2.1% of admissions, respectively. For most (93.2%) ADR-related admissions the ADR resolved and the patient recovered.

CONCLUSION

Hospitalization due to an ADR is a common occurrence in this older population. There is need for future studies to implement and evaluate interventions to reduce the risk of ADR-related admissions in elderly populations.

The prevalence and preventability of potentially relevant drug-drug interactions in patients admitted for cardiovascular diseases: A cross-sectional study

AIM

The aim was to describe the type and prevalence of potentially relevant drug-drug interactions (pDDIs) in a population of patients admitted for cardiovascular diseases (CVD), and management strategies for reducing the occurrence of pDDIs.

METHODS

A retrospective cross-sectional study was performed on Cardiology ward of University Clinical Hospital Center in Belgrade, Serbia. A total of 527 patients, with more than one prescription during hospital stay, were enrolled in this study. Data were obtained from medical records. LexiInteract was used as the screening tool.

RESULTS

At least one potentially relevant pDDI was identified in 83.9% of patients. Occurrence was significantly more prevalent in patients with higher number of drugs, multimorbidity, longer length of stay, arrhythmia, heart failure, infectious and respiratory disease. About 13% of pDDIs exposures were accompanied with concurrent renal or liver disease, as an additional risk for DDI manifestation. Among CVD, patients with a history of myocardial infarction possessed the highest additional risk. The most common potential clinical outcome was the effect on cardiovascular system 48.5%, renal function and/or potassium 22.3%, bleeding 9.5%, impaired glucose control 6.8% and digoxin toxicity 4.6%. Main management strategies to avoid X or D class included using paracetamol instead of NSAID or alternative NSAID (38%), alternative antibiotic or antifungal (20.4%), H₂ receptor antagonist instead of PPI (8.3%), avoiding therapeutic duplication (7.3%), and alternative HMG-CoA reductase inhibitor (7%). Heart rate, blood pressure, electrolytes/potassium and blood glucose could have been employed in monitoring for potential consequence of 72.2% C class pDDIs.

CONCLUSIONS

Use of drug interaction screening tools can be beneficial risk mitigation strategy for potentially relevant pDDIs in CVD patients. DDI screening software could be linked to the patient's laboratory results or clinical data regarding renal or liver function, as an approach to reinforce DDIs alert quality.

The active modulation of drug release by an ionic field effect transistor for an ultra-low power implantable nanofluidic system

We report an electro-nanofluidic membrane for tunable, ultra-low power drug delivery employing an ionic field effect transistor. Therapeutic release from a drug reservoir was successfully modulated, with high energy efficiency, by actively adjusting the surface charge of slit-nanochannels 50, 110, and 160 nm in size, by the polarization of a buried gate electrode and the consequent variation of the electrical double layer in the nanochannel. We demonstrated control over the transport of ionic species, including two relevant hypertension drugs, atenolol and perindopril, that could benefit from such modulation. By leveraging concentration-driven diffusion, we achieve a 2 to 3 order of magnitude reduction in power consumption as compared to other electrokinetic phenomena. The application of a small gate potential (±5 V) in close proximity (150 nm) of 50 nm nanochannels generated a sufficiently strong electric field, which doubled or blocked the ionic flux depending on the polarity of the voltage applied. These compelling findings can lead to next generation, more reliable, smaller, and longer lasting drug delivery implants with ultra-low power consumption.

Assessment of potential drug-drug interactions and its associated factors in the hospitalized cardiac patients

Drug-drug interactions (DDIs) may result in the alteration of therapeutic response. Sometimes they may increase the untoward effects of many drugs. Hospitalized cardiac patients need more attention regarding drug-drug interactions due to complexity of their disease and therapeutic regimen. This research was performed to find out types, prevalence and association between various predictors of potential drug-drug interactions (pDDIs) in the Department of Cardiology and to report common interactions. This study was performed in the hospitalized cardiac patients at Ayub Teaching Hospital, Abbottabad, Pakistan. Patient charts of 2342 patients were assessed for pDDIs using Micromedex® Drug Information. Logistic regression was applied to find predictors of pDDIs. The main outcome measure in the study was the association of the potential drug-drug interactions with various factors such as age, gender, polypharmacy, and hospital stay of the patients. We identified 53 interacting-combinations that were present in total 5109 pDDIs with median number of 02 pDDIs per patient. Overall, 91.6% patients had at least one pDDI; 86.3% were having at least one major pDDI, and 84.5% patients had at least one moderate pDDI. Among 5109 identified pDDIs, most were of moderate (55%) or major severity (45%); established (24.2%), theoretical (18.8%) or probable (57%) type of scientific evidence. Top 10 common pDDIs included 3 major and 7 moderate interactions. Results obtained by multivariate logistic regression revealed a significant association of the occurrence of pDDIs in patient with age of 60 years or more (p < 0.001), hospital stay of 7 days or longer (p < 0.001) and taking 7 or more drugs (p < 0.001). We found a high prevalence for pDDIs in the Department of Cardiology, most of which were of moderate severity. Older patients, patients with longer hospital stay and with elevated number of prescribed drugs were at higher risk of pDDIs.

Rapid Assessment of Adverse Drug Reactions by Statistical Solution of Gene Association Network

Adverse drug reaction (ADR) is a common clinical problem, sometimes accompanying with high risk of mortality and morbidity. It is also one of the major factors that lead to failure in new drug development. Unfortunately, most of current experimental and computational methods are unable to evaluate clinical safety of drug candidates in early drug discovery stage due to the very limited knowledge of molecular mechanisms underlying ADRs. Therefore, in this study, we proposed a novel na€ıve Bayesian model for rapid assessment of clinical ADRs with frequency estimation. This model was constructed on a gene-ADR association network, which covered 611 US FDA approved drugs, 14,251 genes, and 1,254 distinct ADR terms. An average detection rate of 99.86 and 99.73 percent were achieved eventually in identification of known ADRs in internal test data set and external case analyses respectively. Moreover, a comparative analysis between the estimated frequencies of ADRs and their observed frequencies was undertaken. It is observed that these two frequencies have the similar distribution trend. These results suggest that the naıve Bayesian model based on gene-ADR association network can serve as an efficient and economic tool in rapid ADRs assessment.

The effect of different drugs on the preparation and biological outcomes of plasma rich in growth factors

Chronic diseases are the major contributors to the global burden of disease and involve prodigious consumption of various drugs that usually affect platelet function. The autologous technology of plasma rich in growth factors (PRGF) provides a biological approach using autologous platelets as a reservoir and local delivery of proteins to promote tissue healing. The purpose of this study was to evaluate the effect of the consumption of acetylsalicylic acid, acenocoumarol and glucosamine sulfate on the preparation as well as on the biological properties of the PRGF technology. Clotting time and platelet activation of PRGF was evaluated. The latter was performed by flow cytometry. PRGF growth factor content and the release of various biomolecules by gingival fibroblasts were quantified by enzyme-linked immunosorbent assay. Cell proliferation was evaluated by means of a fluorescence-based method and cell migration was performed on culture inserts. None of the parameters evaluated was modified by the consumption of any of the three drugs tested; only the plasma of patients who had consumed acetylsalicylic acid and acenocoumarol expressed greater gingival fibroblast migration compared to plasma control. The intake of acetylsalicylic acid, acenocoumarol and glucosamine sulfate does not alter the preparation and biological properties of the autologous technology of PRGF.

Pharmacoepidemiological profile and polypharmacy indicators in elderly outpatients

This cross-sectional study was carried out with 1000 elderly outpatients assisted by a Basic Health District Unit (UBDS) from the Brazilian Public Health System (SUS) in the municipality of Ribeirão Preto. We analyzed the clinical, socioeconomic and pharmacoepidemiological profile of the elderly patients in order to identify factors associated with polypharmacy amongst this population. We used a truncated negative binomial model to examine the association of polypharmacy with the independent variables of the study. The software SAS was used for the statistical analysis and the significance level adopted was 0.05. The most prevalent drugs were those for the cardiovascular system (83.4%). There was a mean use of seven drugs per patient and 47.9% of the interviewees used >7 drugs. The variables that showed association with polypharmacy (P value < 0.01) were female gender, age >75 years, self-medication, number of health problems, number of medical appointments, presence of adverse drug events, use of over-the-counter drugs, use of psychotropic drugs, lack of physical exercise and use of sweeteners. The exposition to all these factors justified the high prevalence of polypharmacy amongst the interviewees. These results showed the need to adopt clinical intervention and educational and managerial measures to analyze and promote rationality in the use of drugs amongst the elderly users of SUS.

Drug-drug interactions in hospitalized cardiac patients

Drug–drug interactions (DDIs) are defined as two or more drugs interacting in such a manner that the effectiveness or toxicity of one or more drugs is altered. DDI in patients receiving multidrug therapy is a major concern. The aim of the present study was to assess the incidence and risk factors of DDIs in patients admitted in cardiology unit of a teaching hospital. A prospective, observational study was carried out for a period of 3 months (April–July 2009). During the study period, a total of 600 prescriptions were analyzed and it was found that 88 patients had at least one DDI. The percentage of DDIs was higher in females compared to males (56.82% vs. 43.18%). DDIs were observed more in the age group of 60 years and above (57.96). Patients with more than 10 prescribed drugs developed DDIs more frequently [58 (65.91%)]. Heparin [55 (62.25%)] and aspirin [42 (47.72%)] were the most common drugs responsible for DDIs. Bleeding was the commonest clinical consequence [76 (86.63%)] found in this study population. On assessment of severity of DDIs, majority of the cases were classified as moderate in severity (61.36%). Aging, female gender and increase in concurrent medications were found to be associated with increased DDIs. Patients having these risk factors can be actively monitored during their stay in the cardiology department to identify DDIs.

The comorbidity conundrum: a focus on the role of noncardiovascular chronic conditions in the heart failure patient

The rapid aging of the US population combined with improvements in modern medicine has created a new public health concern of comorbidity, a chronic condition that co-exists with a primary illness. Over 141 million Americans suffer from one or more comorbid conditions. In the heart failure (HF) patient, this comorbidity burden is particularly high, with over 40% of patients having five or more chronic conditions. These comorbidities can vary from being a risk factor to a cause of HF progression or even a precipitating factor for decompensation. Comorbidities, particularly the noncardiovascular conditions, have been associated with greater health resource utilization, poor health outcomes, and increased mortality. To minimize the negative impact that these comorbidities have on patient outcomes, appropriate attention should be paid to identifying, prioritizing, and managing each condition; minimizing medication complexity and polypharmacy; and improving overall coordination of care between providers and patients.

Pre-treatment with curcumin enhances plasma concentrations of losartan and its metabolite EXP3174 in rats

The study was carried out in the Wistar rats to investigate the effect of curcumin pre-treatment on the pharmacokinetics of the hypertension-treating drug losartan and its metabolite EXP3174 following single oral administration. In the treatment group, rats were gavaged with losartan 10 mg/kg after repeat oral doses of curcumin (100 mg/kg, for 7 d), while rats in the control group were administrated only with the same dose losartan. The results showed that curcumin significantly increased the plasma concentrations of losartan and its metabolite EXP3174. The present study implicated the existence of herb-drug interaction between curcumin and losartan, and further evaluation of the possible interaction during curcumin administration needs to be considered.

Modeling chemical interaction profiles: II. Molecular docking, spectral data-activity relationship, and structure-activity relationship models for potent and weak inhibitors of cytochrome P450 CYP3A4 isozyme

Polypharmacy increasingly has become a topic of public health concern, particularly as the U.S. population ages. Drug labels often contain insufficient information to enable the clinician to safely use multiple drugs. Because many of the drugs are bio-transformed by cytochrome P450 (CYP) enzymes, inhibition of CYP activity has long been associated with potentially adverse health effects. In an attempt to reduce the uncertainty pertaining to CYP-mediated drug-drug/chemical interactions, an interagency collaborative group developed a consensus approach to prioritizing information concerning CYP inhibition. The consensus involved computational molecular docking, spectral data-activity relationship (SDAR), and structure-activity relationship (SAR) models that addressed the clinical potency of CYP inhibition. The models were built upon chemicals that were categorized as either potent or weak inhibitors of the CYP3A4 isozyme. The categorization was carried out using information from clinical trials because currently available in vitro high-throughput screening data were not fully representative of the in vivo potency of inhibition. During categorization it was found that compounds, which break the Lipinski rule of five by molecular weight, were about twice more likely to be inhibitors of CYP3A4 compared to those, which obey the rule. Similarly, among inhibitors that break the rule, potent inhibitors were 2–3 times more frequent. The molecular docking classification relied on logistic regression, by which the docking scores from different docking algorithms, CYP3A4 three-dimensional structures, and binding sites on them were combined in a unified probabilistic model. The SDAR models employed a multiple linear regression approach applied to binned 1D ¹³C-NMR and 1D ¹⁵N-NMR spectral descriptors. Structure-based and physical-chemical descriptors were used as the basis for developing SAR models by the decision forest method. Thirty-three potent inhibitors and 88 weak inhibitors of CYP3A4 were used to train the models. Using these models, a synthetic majority rules consensus classifier was implemented, while the confidence of estimation was assigned following the percent agreement strategy. The classifier was applied to a testing set of 120 inhibitors not included in the development of the models. Five compounds of the test set, including known strong inhibitors dalfopristin and tioconazole, were classified as probable potent inhibitors of CYP3A4. Other known strong inhibitors, such as lopinavir, oltipraz, quercetin, raloxifene, and troglitazone, were among 18 compounds classified as plausible potent inhibitors of CYP3A4. The consensus estimation of inhibition potency is expected to aid in the nomination of pharmaceuticals, dietary supplements, environmental pollutants, and occupational and other chemicals for in-depth evaluation of the CYP3A4 inhibitory activity. It may serve also as an estimate of chemical interactions via CYP3A4 metabolic pharmacokinetic pathways occurring through polypharmacy and nutritional and environmental exposures to chemical mixtures.

Modeling chemical interaction profiles: I. Spectral data-activity relationship and structure-activity relationship models for inhibitors and non-inhibitors of cytochrome P450 CYP3A4 and CYP2D6 isozymes

An interagency collaboration was established to model chemical interactions that may cause adverse health effects when an exposure to a mixture of chemicals occurs. Many of these chemicals—drugs, pesticides, and environmental pollutant—interact at the level of metabolic biotransformations mediated by cytochrome P450 (CYP) enzymes. In the present work, spectral data-activity relationship (SDAR) and structure-activity relationship (SAR) approaches were used to develop machine-learning classifiers of inhibitors and non-inhibitors of the CYP3A4 and CYP2D6 isozymes. The models were built upon 602 reference pharmaceutical compounds whose interactions have been deduced from clinical data, and 100 additional chemicals that were used to evaluate model performance in an external validation (EV) test. SDAR is an innovative modeling approach that relies on discriminant analysis applied to binned nuclear magnetic resonance (NMR) spectral descriptors. In the present work, both 1D ¹³C and 1D ¹⁵N-NMR spectra were used together in a novel implementation of the SDAR technique. It was found that increasing the binning size of 1D ¹³C-NMR and ¹⁵N-NMR spectra caused an increase in the tenfold cross-validation (CV) performance in terms of both the rate of correct classification and sensitivity. The results of SDAR modeling were verified using SAR. For SAR modeling, a decision forest approach involving from 6 to 17 Mold² descriptors in a tree was used. Average rates of correct classification of SDAR and SAR models in a hundred CV tests were 60% and 61% for CYP3A4, and 62% and 70% for CYP2D6, respectively. The rates of correct classification of SDAR and SAR models in the EV test were 73% and 86% for CYP3A4, and 76% and 90% for CYP2D6, respectively. Thus, both SDAR and SAR methods demonstrated a comparable performance in modeling a large set of structurally diverse data. Based on unique NMR structural descriptors, the new SDAR modeling method complements the existing SAR techniques, providing an independent estimator that can increase confidence in a structure-activity assessment. When modeling was applied to hazardous environmental chemicals, it was found that up to 20% of them may be substrates and up to 10% of them may be inhibitors of the CYP3A4 and CYP2D6 isoforms. The developed models provide a rare opportunity for the environmental health branch of the public health service to extrapolate to hazardous chemicals directly from human clinical data. Therefore, the pharmacological and environmental health branches are both expected to benefit from these reported models.

Anticoagulation and psychotropic medications

Anticoagulants and psychotropic medications are commonly prescribed together. Thus, the potential for interaction exists. Whereas thrombolytics and heparins are implicated in few pharmacokinetic interactions, warfarin and platelet inhibitors have been implicated in various interactions with psychotropic medications. In this article, I review the various psychotropic drug classes' relationships to anticoagulants. In a field devoid of randomized, placebo-controlled trials, clinical vigilance is advised when managing patients on concomitant therapy.

Treatment of ventricular arrhythmias in the elderly

Underlying causes of ventricular tachycardia (VT) or complex ventricular arrhythmias (VA) should be treated if possible. Antiarrhythmic drugs should not be administered to treat asymptomatic individuals with complex VA and no heart disease. Beta-blockers are the only antiarrhythmic drugs that have been documented to reduce mortality in patients with VT or complex VA. Radiofrequency catheter ablation of VT has been beneficial in treating selected patients with arrhythmogenic foci of monomorphic VT. The automatic implantable cardioverter-defibrillator (AICD) is the most effective treatment for patients with life-threatening VT or ventricular fibrillation. Patients with AICDs should be treated with biventricular pacing, not with dual-chamber rate-responsive pacing at a rate of 70/min. Patients with AICDs should also be treated with beta-blockers, statins, and angiotensin-converting enzyme inhibitors or angiotensin blockers.