Trends and concerns of potentially inappropriate medication use in patients with cardiovascular diseases.
Nina D AnfinogenovaIrina A TrubachevaSergey V PopovElena V EfimovaWladimir Y UssovPublished in: Expert opinion on drug safety (2021)
Introduction: The use of potentially inappropriate medications (PIM) is an alarming social risk factor in cardiovascular patients. PIM administration may result in iatrogenic disorders and adverse consequences may be attenuated by limiting PIM intake.Areas covered: The goal of this review article is to discuss the trends, risks, and concerns regarding PIM administration with focus on cardiovascular patients. To find data, we searched literature using electronic databases (Pubmed/Medline 1966-2021 and Web of Science 1975-2021). The data search terms were cardiovascular diseases, potentially inappropriate medication, potentially harmful drug-drug combination, potentially harmful drug-disease combination, drug interaction, deprescribing, and electronic health record.Expert opinion: Drugs for heart diseases are the most commonly prescribed medications in older individuals. Despite the availability of explicit and implicit PIM criteria, the incidence of PIM use in cardiovascular patients remains high ranging from 7 to 85% in different patient categories. Physician-induced disorders often occur when PIM is administered and adverse effects may be reduced by limiting PIM intake. Main strategies promising for addressing PIM use include deprescribing, implementation of systematic electronic records, pharmacist medication review, and collaboration among cardiologists, internists, geriatricians, clinical pharmacologists, pharmacists, and other healthcare professionals as basis of multidisciplinary assessment teams.
Keyphrases
- end stage renal disease
- electronic health record
- healthcare
- cardiovascular disease
- ejection fraction
- newly diagnosed
- adverse drug
- primary care
- peritoneal dialysis
- risk factors
- systematic review
- public health
- prognostic factors
- type diabetes
- metabolic syndrome
- big data
- mental health
- patient reported outcomes
- coronary artery disease
- physical activity
- patient reported
- body mass index
- data analysis