Search Results (111)

Background/Objectives: Women’s health has historically lagged behind other medical specialties in transformative innovation, despite significant technological advances in adjacent fields. In this collection of papers, we examine the current state of innovation in women’s health and maternal–fetal medicine, identify barriers to transformation, and propose strategies for accelerating breakthrough developments. This paper presents an overview of multiple forces and their often-competing relationships that influence the environment in which advances in multiple areas of healthcare have had to navigate to enter mainstream practice. An understanding of these forces is essential to explain why some new technologies are readily deployed into clinical practice while others take many years to be adopted. Understanding the entire “echo-system” around any specific technology provides a much fuller understanding of how any individual advance can make its way into actual utilization. Methods: We synthesized current literature on innovation in women’s health, analyzing technological advances in artificial intelligence, precision medicine, non-invasive diagnostics, and surgical robotics. We examined patterns of innovation adoption and barriers to implementation across multiple domains. Results: Several key areas presented in this paper and the following show promise for transformative change: artificial intelligence (AI)-driven diagnostics achieving expert-level performance in prenatal screening, precision medicine approaches transforming genetic disease management, and non-invasive monitoring technologies revolutionizing maternal–fetal care. However, systemic barriers including regulatory complexity, liability concerns, and institutional inertia continue to limit widespread adoption of numerous breakthrough technologies. Conclusions: The convergence of multiple technological advances, particularly artificial intelligence and precision medicine, positions women’s health for unprecedented transformation. Success requires fostering innovation-ready environments, embracing systems-awareness approaches, and maintaining focus on human-centered care while leveraging technological capabilities with continual feedback and course corrections. Full article

Background: Antiviral therapies are widely used during pregnancy and are generally considered safe, pregnancy-specific severe safety signals continue to be observed in post-marketing pharmacovigilance data. These signals are rarely interpreted within an integrated mechanistic framework. Methods: We analysed pregnancy-related EudraVigilance reports (2015–2025) using a previously network-based pharmacovigilance framework. Established ADR clusters were treated as fixed phenotypes and integrated with in silico ADMET liabilities, literature-derived pregnancy pharmacokinetic/pharmacodynamic (PK/PD) parameters, polypharmacy and co-medication network metrics, and exploratory statistical, machine-learning, and exposure–liability analyses for mechanistic prioritisation. Results: Phenotype membership explained 22.3% of the variance in composite ADMET risk (intraclass correlation coefficient = 0.223; p < 0.001), and all tested ADMET parameters differed significantly across phenotypes (FDR-adjusted p < 10⁻¹⁰). One phenotype showed pronounced enrichment, with 13 antivirals over-represented. Polypharmacy strongly modified seriousness, with odds of serious outcomes increasing by ~5% per additional co-reported active drug (OR 1.05, 95% CI 1.04–1.05). A composite mechanistic vulnerability index showed moderate concordance with empirical burden (Spearman’s ρ = 0.65), while regimen-level prioritisation of drug–drug interactions (DDIs) identified no high-priority combinations. Conclusions: Pregnancy-related antiviral ADRs cluster into reproducible phenotypes driven by mechanistic liability and system-level complexity, supporting mechanistically informed prioritisation and targeted pharmacometric follow-up. Full article

Compensation for mental distress in preschool children is a crucial mechanism for protecting their personality rights, yet current judicial practice in China relies heavily on judicial discretion and lacks child-sensitive standards for determining severity. Following the enactment of the Preschool Education Law of the People’s Republic of China in 2025, the principle of the Best Interests of the Child has placed new behavioral and developmental requirements on decision-making, particularly regarding the recognition of children’s expressive limitations and psychological vulnerability. Drawing on representative judicial cases, this research identifies inconsistencies in current adjudication—primarily between factual presumption and medical proof—and highlights their failure to reflect preschoolers’ developmental characteristics. To address this gap, we construct a child-centered liability determination framework integrating the Lundy model of child participation and Nussbaum’s Capabilities Approach. This framework provides a structured method for incorporating children’s voices into proceedings and offers multidimensional criteria for assessing capability impairment as an indicator of mental distress severity. These findings suggest that the framework can help reduce excessive discretion, strengthen developmental sensitivity, and promote more consistent and equitable adjudication. Beyond the Chinese context, this research offers an analytical lens for advancing international discussions on child-centered mental distress assessment and children’s rights protection. Full article

Asbestos, a group 1 carcinogen, has generated a serious health and environmental liability in Pedro Leopoldo/MG, Brazil, even after its national ban in 2017. This study aims to analyze the silent epidemic of asbestos-related diseases (ARDs) through the lens of social injustice. We used a qualitative, socio-historical, and clinical approach within the framework of an Expanded Research Community (ERC), based on ergology, with content analysis of interviews with workers and institutional documents. The evidence reveals a pattern of institutional silencing and omission, marked by corporate fraud, denial of risk, and medical underreporting, perpetuating occupational, domestic, and environmental exposure. In response, the Brazilian Association of Asbestos-Exposed Individuals of Minas Gerais (ABREA/MG) emerged as a central actor in the struggle for recognition and justice. It is concluded that overcoming this injustice requires structured public policies of recognition, integrated surveillance, historical reparation, and strengthening of the SUS (Unified Health System), with collective resistance being fundamental to transforming suffering into memory and social demands. Full article

Background/Objectives: Artificial intelligence (AI) is increasingly applied to drug safety evaluation, yet evidence is dispersed across lifecycle stages and tasks. This scoping review aimed to (1) map how AI supports safety- and treatment-related decision types across the drug lifecycle, and (2) examine evaluation strategies used to assess model reliability for clinical or regulatory use. Methods: Using Arksey and O’Malley’s framework, we searched a major database for studies published in the past decade that applied AI or machine learning to drug safety or medication-related decisions. After screening, we extracted data on lifecycle stage, decision type, AI methods, data sources, and evaluation strategies. A lifecycle–decision matrix was constructed to characterize application patterns. Results: AI applications were concentrated in real-world clinical care × patient-level safety prediction and post-marketing × safety surveillance, using EHRs, spontaneous reporting systems, and clinical text. Common methods included gradient boosting, deep neural networks, graph neural networks, and natural language processing models. This concentration reflects structural incentives favoring safety-oriented applications with readily available data and lower decision liability. Evidence for treatment optimization, regulatory decision modeling, and evidence synthesis was limited. Most studies used internal validation; external validation and real-world deployment were uncommon, indicating early methodological maturity and limited translational readiness. Conclusions: AI demonstrates strong potential to enhance drug safety—particularly in risk prediction and pharmacovigilance—but its use remains uneven across the lifecycle. By situating AI applications within explicit lifecycle stages and decision contexts, this review clarifies where progress has advanced, where translation has stalled, and why these gaps persist. Limited external validation and minimal real-world testing constrain clinical and regulatory adoption. These findings suggest that external validation and real-world testing may contribute to further advances in AI for drug safety. Full article

Background and Objectives: The COVID-19 pandemic has led to an unprecedented mental health crisis among workers in the healthcare field, with average burnout rates increasing from about 32% before the pandemic to 46–52% during peak times and post-traumatic stress disorder (PTSD) affecting 24–34% of frontline staff. The primary objective of this article is to synthesize evidence on the prevalence of burnout and PTSD among healthcare workers before and during the COVID-19 pandemic. The secondary objectives are: (a) to examine the mechanisms and empirical evidence linking clinician mental health to medical errors and patient safety outcomes and (b) to analyze the medico-legal implications of this relationship, including malpractice liability, institutional responsibility, and opportunities for policy reform. Materials and Methods: We conducted a narrative review searching PubMed (November 2025–January 2026) using predefined keyword combinations. Inclusion criteria comprised original research, systematic reviews, and meta-analyses examining mental health outcomes or patient safety among clinical staff. Data were synthesized narratively across five thematic domains. Results: Burnout prevalence increased from approximately 32% pre-pandemic to 46–52% during peak periods, with emotional exhaustion reaching 67.5% in some settings. PTSD rates rose to 24–34% among frontline staff, exceeding pre-pandemic levels of 15–20%, with ICU staff particularly affected (27–40%). Substantial overlap exists between conditions (86–98% comorbidity). Physician burnout is associated with 2.72 times higher odds of self-reported errors (95% CI: 2.19–3.37), with each point increase in emotional exhaustion raising the error risk by 5–11%. Mechanisms include cognitive impairment (reduced executive function, g = −0.39; impaired working memory, g = −0.36) and sleep disturbance. Malpractice litigation compounds psychological harm, increasing depression and suicidal ideation. Conclusions: This review, synthesizing data from over 500,000 healthcare workers, demonstrates bidirectional relationships among burnout, PTSD, and medical errors with significant medico-legal ramifications. Addressing this crisis requires systemic interventions including workload management, psychological support, blame-free reporting cultures, and policy reforms balancing accountability with recognition of system-level contributors to error. Full article

Objectives: This study aims to evaluate whether contemporary artificial intelligence (AI), including convolutional neural networks (CNNs) for medical imaging and large language models (LLMs) for language processing, could replace physicians in the near future and to identify the principal clinical, technical, and regulatory barriers. Methods: A narrative review is conducted on the scientific literature addressing AI performance and reproducibility in medical imaging, LLM competence in medical knowledge assessment and patient communication, limitations in out-of-distribution generalization, absence of physical examination and sensory inputs, and current regulatory and legal frameworks, particularly within the European Union. Results: AI systems demonstrate high accuracy and reproducibility in narrowly defined tasks, such as image interpretation, lesion measurement, triage, documentation support, and written communication. These capabilities reduce interobserver variability and support workflow efficiency. However, major obstacles to physician replacement persist, including limited generalization beyond training distributions, inability to perform physical examination or procedural tasks, susceptibility of LLMs to hallucinations and overconfidence, unresolved issues of legal liability at higher levels of autonomy, and the continued requirement for clinician oversight. Conclusions: In the foreseeable future, AI will augment rather than replace physicians. The most realistic trajectory involves automation of well-defined tasks under human supervision, while clinical integration, physical examination, procedural performance, ethical judgment, and accountability remain physician-dependent. Future adoption should prioritize robust clinical validation, uncertainty management, escalation pathways to clinicians, and clear regulatory and legal frameworks. Full article

Background/Objectives: Orthopedic surgery is among the most frequently litigated medical specialties worldwide. However, high-court malpractice decisions involving orthopedic specialists in Türkiye remain underexplored. This study aims to identify the patterns, causes, and outcomes of malpractice cases involving orthopedists by analyzing Turkish Supreme Court decisions over the past 15 years. Methods: A retrospective review of orthopedic malpractice cases adjudicated by the Turkish Court of Cassation between January 2010 and November 2025 was conducted. Variables included type of alleged offense, clinical context, primary/secondary liability, initial court outcomes, high-court decisions, and fault attribution. Findings were compared with international literature to contextualize national patterns. Results: A total of 71 decisions were analyzed. Negligent injury was the most common allegation. Initial acquittal and conviction rates were 50.7% and 49.3%, respectively. The Supreme Court affirmed 53.5% of decisions and overturned 46.5%. Fault was attributed to orthopedic specialists in 29.6% of cases, while 40.8% were found faultless; the remaining cases required additional expert evaluation. Litigation themes included diagnostic delay, postoperative complications, inadequate monitoring, and documentation deficiencies. Comparative analysis revealed substantial alignment between Turkish and international malpractice patterns. Conclusions: Orthopedic malpractice litigation in Türkiye mirrors global trends, with most claims stemming from trauma-related care and diagnostic errors. Although many cases undergo prolonged appeals, ultimate conviction rates remain low. Strengthened documentation, improved communication, and enhanced clinical guideline adherence may reduce litigation risk and improve patient safety. Full article

Background/Objectives: Chagas disease remains a major unmet medical need due to the limited efficacy and safety of current therapies. Here, we investigated sixteen thiosemicarbazone (TSC) derivatives as cruzain inhibitors using an integrated in silico/in vitro workflow. Methods: Docking against cruzain (PDB 3KKU) guided hit prioritization and correlated with enzyme inhibition; validation by redocking supported the protocol’s reliability. Results: The top compounds—H7, H10 and H11—showed potent cruzain inhibition (IC₅₀ = 0.306, 0.512 and 0.412 µM, respectively) and low-micromolar trypanocidal activity, with negligible cytotoxicity in human fibroblasts (CC₅₀ > 64 µM) and favorable selectivity. Structure–activity insights highlighted the role of expanded aromatic systems and electron-donating groups in enhancing binding within S2/S1′ subsites, while nitro substituents were associated with higher cytotoxicity. In silico ADMET parameters supported oral drug-likeness and acceptable metabolic liabilities. Conclusions: Overall, these data position TSCs as promising anti-T. cruzi leads and underscore the value of rational design against cruzain. Full article

Intelligent driving cabins operated by artificial intelligence technology are evolving into the third living space. They aim to integrate perception, analysis, decision making, and intervention. By using multimodal biosignal acquisition technologies (flexible sensors and non-contact sensing), it is possible to monitor the physiological indicators of heart rate and blood pressure in real time. Leveraging the benefits of domain controllers in the vehicle and edge computing helps the AI platform reduce data latency and enhance real-time processing capabilities, as well as integrate the cabin’s internal and external data through machine learning. Its aim is to build tailored health baselines and high-precision risk prediction models (e.g., CNN, LSTM). This system can initiate multi-level interventions such as adjustments to the environment, health recommendations, and ADAS-assisted emergency parking with telemedicine help. Current issues consist of sensor precision, AI model interpretation, security of data privacy, and whom to attribute legal liability to. Future development will mainly focus on cognitive digital twin construction, L4/L5 autonomous driving integration, new biomedical sensor applications, and smart city medical ecosystems. Full article

The long-stop rule, under the UK Consumer Protection Act (CPA) 1987, imposes a 10-year limitation period for product liability claims, providing legal certainty for manufacturers and consumers. However, this timeframe is increasingly problematic in the case of medical devices, particularly implantable ones, which can fail decades after implantation. This review considers an extension to the long-stop period for medical devices, emphasising the need for patient protection, legal clarity, and reduced clinician burden, and contrasts the current UK system with the EU’s proposed 25-year long-stop period under the recently implemented 2024 Product Liability Directive. Through case studies, including surgical mesh and orthopaedic implants, the discussion highlights the challenges posed by delayed failure modes and the resulting difficulties in seeking redress within the 10-year window. Lastly, the role of publicly funded redress schemes and the evolving legal landscape are examined, underscoring the importance of reconsidering the current statutory limitations. Extending the long-stop period, combined with the use of explant analysis to evaluate defective medical devices, is proposed as a means to enhance patient safety and align with ongoing advancements in medical technology and regulation. Full article

Italian Court of Cassation Ruling Decree 30032 of 30 October 2023 discusses a medical malpractice case concerning the diagnosis of dermatofibrosarcoma protuberans and the alleged diagnostic and therapeutic delay. By examining how the ruling frames the role of histopathology in proving pathology benignity, authors prompt to reflect on diagnostic path, the allocation of the burden of proof, and the role of dermatologist’s expertise in professional liability issues. Over a four-year period, five health professionals were involved in a claim concerning an initial diagnosis of an epidermoid cyst and a subsequent diagnosis of dermatofibrosarcoma protuberans. The plaintiff questioned the delay in diagnosis, and the Court of Cassation found two physicians liable because they could not prove that the treated pathology was initially benign. We argue that equating diagnostic correctness exclusively with histological confirmation is unnecessary, both clinically and legally, in typical cases, if the reasoning and findings are adequately documented. Additionally, we examine the value of dermatologists’ experience and the scope of professional competence as measures of liability. Finally, we outline the minimum standards of clinical documentation necessary to make the diagnostic pathway traceable and verifiable. The diagnostic process is a discretionary effort that integrates multiple sources of information, both instrumental and experiential, to reach the most reasonable hypothesis. While histopathology is a crucial tool, it is not the sole gateway to a correct diagnosis of every cutaneous alteration. Adequate disclosure and structured documentation of the diagnostic reasoning are fundamental to the care process and fair assessment of professional responsibility. Full article

Cannabidiol (CBD) has transitioned from anecdotal use to an evidence-based adjunctive therapy for Lennox–Gastaut syndrome, Dravet syndrome, and tuberous sclerosis complex. This review integrates knowledge on CBD’s pharmacology, pharmacokinetics, and clinical implementation, with focus on metabolism, therapeutic drug monitoring (TDM), and clinically relevant interactions with antiseizure medications. CBD exerts CB1/CB2-independent mechanisms—prominently GPR55 antagonism, TRP-channel desensitization, and adenosine-mediated network dampening—supporting efficacy across heterogeneous seizure phenotypes. Its pharmacokinetic profile is characterized by low and variable oral bioavailability, a pronounced food effect, extensive tissue distribution, and phase I/II biotransformation to the active 7-hydroxy-CBD and abundant 7-carboxy-CBD, resulting in substantial inter-individual variability and liability for drug–drug interactions. Clinically salient interactions include CYP2C19-mediated elevation of N-desmethylclobazam and increased transaminases in valproate co-therapy. We summarize emerging TDM practices—standardized fed-state trough sampling with paired measurement of CBD and 7-hydroxy-CBD—and discuss how preliminary interpretive ranges can support dose optimization, adherence assessment, and safety surveillance. Practical recommendations emphasize interaction-aware titration within evidence-based dose bands, liver function monitoring, and standardized documentation of formulation and sampling conditions. Future work should align pharmacogenomics with TDM, refine bioavailability through advanced delivery systems, and tighten analytical and product-quality standards to consolidate CBD as a precision-ready component of modern epilepsy care. Full article

Introduction: Refusal to undergo treatment, including one of its manifestations, discharge against medical advice, must be informed, just as consent is, which is considered a core ethical principle in contemporary medical ethics. The aim of this study was to explore physicians’ attitudes and intended behaviour toward patients’ refusal of necessary treatment and to identify factors associated with their clinical decisions in such situations. Methods: A cross-sectional anonymous online survey of 393 physicians working in Lithuanian public hospitals was conducted between November 2020 and March 2021 using the secure national platform manoapklausa.lt. A convenience sampling strategy ensured representation of both large university and smaller regional hospitals, and all responses were complete due to mandatory fields in the questionnaire. Results: Most physicians (85%; 95% CI 81.2 to 88.5) have encountered situations of refusal to undergo treatment. Women (p < 0.05) and senior physicians (aged 51 years and over) (p < 0.05) tend to apply treatment without patients’ consent more often in all clinical cases, especially in surgical ones (VN1 and VN2). Difficulty in the decision-making process was associated with chronic conditions and the influence of individual religious beliefs. Insufficient patient information on the intervention was indicated as the main cause of refusal to undergo treatment (62.9%; 95% CI 58.0 to 67.4). Refusal to undergo treatment was associated with physicians’ concern about the patient (57.5%; 95% CI 52.7 to 62.3) and anxiety (38.9%; 95% CI 34.1 to 43.8). Physicians’ attitudes towards patients’ refusal to undergo treatment reflect paternalistic patterns and are mainly associated with the physician’s older age, gender, and duration of professional experience. Insufficient patient information on the intervention was indicated as the most important factor determining patients’ refusal to undergo treatment. Under Lithuanian law, patients have a clear legal right to refuse treatment, and physicians who proceed without consent may face criminal liability. Conclusions: Our findings show that, despite the legal restrictions, many physicians would still choose to treat against a patient’s will, reflecting a persistent paternalistic attitude even in the presence of clear legal prohibitions. Full article

Cataract surgery is the most common eye operation worldwide and is regarded as one of the safest procedures in medicine. Yet, despite its low complication rates, it generates a disproportionate share of litigation. The gap between excellent safety profiles and rising medico-legal claims is driven less by surgical outcomes than by patient expectations, often shaped by healthcare marketing and the promise of risk-free recovery. This narrative review explores the clinical and legal dimensions of cataract surgery, focusing on complications, perioperative risk factors, and medico-legal concepts of predictability and preventability. Particular emphasis is given to European frameworks, with the Italian Gelli-Bianco Law (Law No. 24/2017) providing a model of accountability that balances innovation and patient safety. Analysis shows that liability exposure spans all phases of surgery: preoperative (inadequate consent, poor documentation), intraoperative (posterior capsule rupture, zonular instability), and postoperative (endophthalmitis, poor follow-up). Practical strategies for risk reduction include advanced imaging such as macular OCT, rigorous adherence to updated guidelines, systematic video recording, and transparent perioperative communication. Patient-reported outcomes further highlight that satisfaction depends more on visual quality and dialogue than on spectacle independence. By translating legal principles into clinical strategies, this review offers surgeons actionable “surgical–legal pearls” to improve outcomes, strengthen patient trust, and reduce medico-legal vulnerability in high-volume cataract surgery. Full article