Medicolegal and insurance issues regarding BRCA1 and BRCA2 gene tests in high income countries.

Hereditary breast and ovarian cancer syndrome is an autosomal dominant cancer susceptibility syndrome mainly due to variants in BRCA1 or BRCA2 genes. Patients presenting with BRCA1 or BRCA2 gene mutations have a lifetime risk of developing breast or ovarian cancer (80% and 40%, respectively). Genetic testing to explore the predisposition to develop cancer represents a pivotal factor in such cases, and this review wants to explore the main implications in terms of medicolegal liability and insurance issues. Medicolegal issues related to these diagnostic processes include: (a) failure to recommend the test; (b) failure to properly interpret the test; (c) failure to correctly translate results into clinical practice; (d) lack of informed consent; and (e) failure to refer patients to specialized genetic counseling. Such errors may lead to compensation since the legal burden inherent in the efficacy of prophylactic interventions is a proof that requires the so-called 'preponderance of the evidence'. Concerning insurance issues, the carriers of such alleles without cancer are healthy because the genetic predisposition is not a disease per se but represents a (relevant) health risk. However, disclosure of these conditions can be impelled by insurers. It can lead to so-called 'genetic discrimination' because insurance companies might use genetic information to limit insurance options or increase their costs. Many private and public healthcare funders do not cover risk reducing surgeries, even when recommended as part of a risk reduction management plan for BRCA gene mutation carriers. Here, positions on these matters from different high income countries are discussed, stressing the importance of a common supranational or international regulatory framework to reach a trade-off between the economic interests of insurers and the rights of carriers not to disclose extremely sensitive information.

Potentiality of algorithms and artificial intelligence adoption to improve medication management in primary care: a systematic review.

OBJECTIVES: The aim of this study is to investigate the effect of artificial intelligence (AI) and/or algorithms on drug management in primary care settings comparing AI and/or algorithms with standard clinical practice. Second, we evaluated what is the most frequently reported type of medication error and the most used AI machine type. METHODS: A systematic review of literature was conducted querying PubMed, Cochrane and ISI Web of Science until November 2021. The search strategy and the study selection were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and the Population, Intervention, Comparator, Outcome framework. Specifically, the Population chosen was general population of all ages (ie, including paediatric patients) in primary care settings (ie, home setting, ambulatory and nursery homes); the Intervention considered was the analysis AI and/or algorithms (ie, intelligent programs or software) application in primary care for reducing medications errors, the Comparator was the general practice and, lastly, the Outcome was the reduction of preventable medication errors (eg, overprescribing, inappropriate medication, drug interaction, risk of injury, dosing errors or in an increase in adherence to therapy). The methodological quality of included studies was appraised adopting the Quality Assessment of Controlled Intervention Studies of the National Institute of Health for randomised controlled trials. RESULTS: Studies reported in different ways the effective reduction of medication error. Ten out of 14 included studies, corresponding to 71% of articles, reported a reduction of medication errors, supporting the hypothesis that AI is an important tool for patient safety. CONCLUSION: This study highlights how a proper application of AI in primary care is possible, since it provides an important tool to support the physician with drug management in non-hospital environments.

Structural Heart Alterations in Brugada Syndrome: Is it Really a Channelopathy? A Systematic Review.

Brugada syndrome (BrS) is classified as an inherited cardiac channelopathy attributed to dysfunctional ion channels and/or associated proteins in cardiomyocytes rather than to structural heart alterations. However, hearts of some BrS patients exhibit slight histologic abnormalities, suggesting that BrS could be a phenotypic variant of arrhythmogenic cardiomyopathy. We performed a systematic review of the literature following Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement (PRISMA) criteria. Our comprehensive analysis of structural findings did not reveal enough definitive evidence for reclassification of BrS as a cardiomyopathy. The collection and comprehensive analysis of new cases with a definitive BrS diagnosis are needed to clarify whether some of these structural features may have key roles in the pathophysiological pathways associated with malignant arrhythmogenic episodes.

Update on the Diagnostic Pitfalls of Autopsy and Post-Mortem Genetic Testing in Cardiomyopathies.

Inherited cardiomyopathies are frequent causes of sudden cardiac death (SCD), especially in young patients. Despite at the autopsy they usually have distinctive microscopic and/or macroscopic diagnostic features, their phenotypes may be mild or ambiguous, possibly leading to misdiagnoses or missed diagnoses. In this review, the main differential diagnoses of hypertrophic cardiomyopathy (e.g., athlete's heart, idiopathic left ventricular hypertrophy), arrhythmogenic cardiomyopathy (e.g., adipositas cordis, myocarditis) and dilated cardiomyopathy (e.g., acquired forms of dilated cardiomyopathy, left ventricular noncompaction) are discussed. Moreover, the diagnostic issues in SCD victims affected by phenotype-negative hypertrophic cardiomyopathy and the relationship between myocardial bridging and hypertrophic cardiomyopathy are analyzed. Finally, the applications/limits of virtopsy and post-mortem genetic testing in this field are discussed, with particular attention to the issues related to the assessment of the significance of the genetic variants.