Actualities in the evaluation of the level of psychic insight correlated with the modifications in the penal code in rm

Catedra Psihiatrie, Narcologie şi Psihologie medicală, USMF „Nicolae Testemiţanu”The present article reveals the actuality of elaboration of qualitative-functional parameters and the criteria of implementation in expertal practice of the notion “low insight” correlated with the fresh modifications in the Penal Code of RM. Prezenta lucrare abordează actualitatea elaborării parametrilor calitativ-funcţionali şi criteriilor de implementare în practica expertală a noţiunii de „discernămînt diminuat” prin prisma modificărilor de ultima oră a Codului Penal al R. Moldova

Enhancing the Evidence with Algorithms: How Artificial Intelligence Is Transforming Forensic Medicine

Background: The integration of artificial intelligence (AI) into various fields has ushered in a new era of multidisciplinary progress. Defined as the ability of a system to interpret external data, learn from it, and adapt to specific tasks, AI is poised to revolutionize the world. In forensic medicine and pathology, algorithms play a crucial role in data analysis, pattern recognition, anomaly identification, and decision making. This review explores the diverse applications of AI in forensic medicine, encompassing fields such as forensic identification, ballistics, traumatic injuries, postmortem interval estimation, forensic toxicology, and more. Results: A thorough review of 113 articles revealed a subset of 32 papers directly relevant to the research, covering a wide range of applications. These included forensic identification, ballistics and additional factors of shooting, traumatic injuries, post-mortem interval estimation, forensic toxicology, sexual assaults/rape, crime scene reconstruction, virtual autopsy, and medical act quality evaluation. The studies demonstrated the feasibility and advantages of employing AI technology in various facets of forensic medicine and pathology. Conclusions: The integration of AI in forensic medicine and pathology offers promising prospects for improving accuracy and efficiency in medico-legal practices. From forensic identification to post-mortem interval estimation, AI algorithms have shown the potential to reduce human subjectivity, mitigate errors, and provide cost-effective solutions. While challenges surrounding ethical considerations, data security, and algorithmic correctness persist, continued research and technological advancements hold the key to realizing the full potential of AI in forensic applications. As the field of AI continues to evolve, it is poised to play an increasingly pivotal role in the future of forensic medicine and pathology

Drugs Associated with Adverse Effects in Vulnerable Groups of Patients

In recent years, a series of recommendations have been issued regarding the administration of drugs because of awareness of the serious side effects associated with certain classes of drugs, especially in vulnerable patients. Taking into account the obligation of the continuous improvement of professionals in the medical fields and the fact that we are in the midst of a “malpractice accusations pandemic”, through this work, we propose to carry out a “radiography” of the scientific literature regarding adverse effects that may occur as a result of the interaction of drugs with the physiopathological particularities of patients. The literature reports various cases regarding different classes of drugs administration associated with adverse effects in the elderly people, such as fluoroquinolones, which can cause torsade de pointes or tendinopathy, or diuretics, which can cause hypokalemia followed by torsade de pointes and cardiorespiratory arrest. Also, children are more prone to the development of adverse reactions due to their physiological particularities, while for pregnant women, some drugs can interfere with the normal development of the fetus, and for psychiatric patients, the use of neuroleptics can cause agranulocytosis. Considering the physiopathological particularities of each patient, the drug doses must be adjusted or even completely removed from the treatment scheme, thus requiring the mandatory active participation both of clinician pharmacists and specialists in the activity of medical-pharmaceutical analysis laboratories within the structure of hospitals

The Relationship between Subclinical Hypothyroidism and Carotid Intima-Media Thickness as a Potential Marker of Cardiovascular Risk: A Systematic Review and a Meta-Analysis

Background and Objectives: Thyroid dysfunction is known to have significant consequences on the cardiovascular system. The correlation between carotid intima-media thickness (CIMT) and subclinical hypothyroidism (SCH) has been frequently evaluated in clinical studies in recent years. This study aimed to evaluate the significance of this association through a meta-analysis. Methods: We conducted a systematic search of PubMed, MedLine, Scopus, and Web of Science databases using the keywords ‘subclinical hypothyroidism and carotid intima-media thickness’, from the beginning of each database until January 2023. We established the inclusion and exclusion criteria and considered studies that met the inclusion criteria. We used Jamovi for statistical analysis of the data. Results: We identified 39 observational studies that met the inclusion criteria, with 3430 subjects: 1545 SCH and 1885 EU. Compared to euthyroid subjects (EU), subjects with subclinical hypothyroidism (SCH) had significantly increased carotid intima-media thickness (CIMT) values; the estimated average mean difference was 0.08 (95% CI 0.05 to 0.10), p 2 = 93.82%. After the sensitivity analysis, a total of 19 from the 39 abovementioned studies were analyzed, with most studies showing a positive association between SCH and thickening of the carotid wall; the estimated average mean difference was 0.04 (95% CI 0.02 to 0.07), p = 0.03, I2 = 77.7. In addition, female sex, advanced age, and high cholesterol levels statistically significantly influenced this association. Conclusions: Our meta-analysis indicates a significant positive association between SCH and increased CIMT, but with some limitations

Revolutionizing Cardiology through Artificial Intelligence—Big Data from Proactive Prevention to Precise Diagnostics and Cutting-Edge Treatment—A Comprehensive Review of the Past 5 Years

Background: Artificial intelligence (AI) can radically change almost every aspect of the human experience. In the medical field, there are numerous applications of AI and subsequently, in a relatively short time, significant progress has been made. Cardiology is not immune to this trend, this fact being supported by the exponential increase in the number of publications in which the algorithms play an important role in data analysis, pattern discovery, identification of anomalies, and therapeutic decision making. Furthermore, with technological development, there have appeared new models of machine learning (ML) and deep learning (DP) that are capable of exploring various applications of AI in cardiology, including areas such as prevention, cardiovascular imaging, electrophysiology, interventional cardiology, and many others. In this sense, the present article aims to provide a general vision of the current state of AI use in cardiology. Results: We identified and included a subset of 200 papers directly relevant to the current research covering a wide range of applications. Thus, this paper presents AI applications in cardiovascular imaging, arithmology, clinical or emergency cardiology, cardiovascular prevention, and interventional procedures in a summarized manner. Recent studies from the highly scientific literature demonstrate the feasibility and advantages of using AI in different branches of cardiology. Conclusions: The integration of AI in cardiology offers promising perspectives for increasing accuracy by decreasing the error rate and increasing efficiency in cardiovascular practice. From predicting the risk of sudden death or the ability to respond to cardiac resynchronization therapy to the diagnosis of pulmonary embolism or the early detection of valvular diseases, AI algorithms have shown their potential to mitigate human error and provide feasible solutions. At the same time, limits imposed by the small samples studied are highlighted alongside the challenges presented by ethical implementation; these relate to legal implications regarding responsibility and decision making processes, ensuring patient confidentiality and data security. All these constitute future research directions that will allow the integration of AI in the progress of cardiology

Pharyngeal-Esophageal Malignancies with Dermatologic Paraneoplastic Syndrome

Systemic changes often send signals to the skin, and certain neoplastic diseases of the internal organs can also trigger skin manifestations. In this article, the authors make clinical photography presentations of the patients seen at our clinic with dermatologic paraneoplastic syndromes within pharyngeal–esophageal malignancies, describe several paraneoplastic dermatoses, and also review high-quality scientific literature in order to be able to highlight the dermatological signs of pharyngoesophageal malignant tumors. The majority of our patients with paraneoplastic dermatoses, filtering for pharyngoesophageal malignancies, had esophageal neoplasms, out of whom seven were female and two were male, making esophageal cancer more common within the paraneoplastic dermatoses within pharyngoesophageal malignancies. An early recognition of paraneoplastic dermatoses can diagnose neoplasms and sequentially contribute to a better prognosis for the patient. This matter is also useful for front-line medical personnel in order to improve early diagnosis of the underlying malignancy, curative interventions with prompt therapy administration and good prognosis