PurposeEarly identification of pathological changes in high myopia (HM) with tessellated fundus (TF) remains challenging. To address this, a diagnostic nomogram was developed and validated to aid clinical screening of pathologic myopia (PM) in HM patients with TF.Patients and MethodsA cross-sectional study was performed at The First Affiliated Hospital of Guangxi Medical University between May 10, 2023, and March 31, 2024. Patients with HM, defined as a spherical refractive error of ≤ −6.0 D or an axial length of ≥ 26.5 mm, who presented with TF were enrolled. The collected clinical data were randomly divided into training and validation sets at a 7:3 ratio. A diagnostic nomogram was constructed from independent predictive factors. Its discrimination, calibration, and clinical utility were assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).ResultsData from 418 eyes with TF were included in this study. Independent predictors for PM, in descending order of association, were axial length, optic disc tilt ratio, spherical equivalent, education level, and extent of peripapillary atrophy. The nomogram demonstrated robust performance in both sets. In the training set, the area under the ROC curve (AUC) was 0.851 (95% CI: 0.808–0.895), with a sensitivity of 0.775 and a specificity of 0.736. In the validation set, the AUC was 0.827 (95% CI: 0.755–0.900), with a sensitivity of 0.773 and a specificity of 0.700.ConclusionThis simple predictive model, developed and validated using common interpretable clinical and fundus imaging features, serves as a valuable tool for screening PM in HM patients with TF.

PurposeThis study aims to explore the perspectives of hospital incident command system (HICS) members to identify key gaps in hospital disaster preparedness and set recommendations to enhance hospital resilience and disaster response capacity in Nepal.MethodsA qualitative case study method was employed, involving semi-structured in-depth interviews as a sole method of data collection, with HICS members purposively selected based on their active involvement in hospital disaster preparedness. The interviews were conducted in person in Nepali, transcribed verbatim, translated into English, and analyzed using an inductive thematic approach.ResultsThree themes arose from the results. The first theme highlighted the need for policy and systemic reforms, including revising staffing quotas based on an updated organization and management survey, developing standardized national guidelines for hospital nonstructural safety, revising tender policies to allow greater flexibility in emergency resource procurement, and updating hospital disaster preparedness and response plans to adopt a more comprehensive, all-hazards approach. The second theme entailed strategic partnerships and community engagement, demanding formal collaboration with external stakeholders, establishing a local coordination hub to streamline disaster response efforts, and pre-disaster coordination meetings with relevant partners. The third theme was concerned with hospital-level operational reforms, suggesting capacity-building efforts like cross-training and mentoring programs, extending training to alternative HICS focal persons, aligning stockpiling strategies with local hazard risks, and assessing triage areas to ensure their functionality during actual emergencies.ConclusionHospitals in Nepal need a coordinated effort among policymakers, healthcare administrators, frontline hospital personnel, and local stakeholders to bridge existing gaps and build a resilient healthcare system.

Afghan women and girls have been prohibited from working outside the home, attending schools and universities, traveling without a male companion, and, banned from studying in medical institutes in courses such as midwifery and nursing. Here we discuss how the current policies in Afghanistan affect early child marriage and education of young girls and the consequences on women’s health.These restrictions have, and will continue to have, significant impacts on the health and wellbeing of women and girls in Afghanistan reversing advances made in the last two decades. These limitations increase the vulnerability of girls to early marriage leading to increased adolescent pregnancies, maternal and infant mortality and morbidity, mental health consequences, and gender-based violence. Limiting available female healthcare providers further threatens maternal health by reducing already limited access to care. Urgent national and international action is needed to restore access to education and healthcare to safeguard women’s rights and protect the health and lives of mothers and their children in Afghanistan.

Background/ObjectivesArtificial intelligence (AI) is revolutionizing the healthcare industry, improving diagnoses, treatments, and clinical processes. However, its integration poses significant cybersecurity risks, including data breaches, algorithmic opacity, and vulnerabilities in AI-controlled medical devices. This narrative review analyzes these threats and evaluates blockchain technology as a potential mitigation strategy within a Clinical Risk Management framework.MethodsThe literature search was conducted on PubMed, Scopus, and Web of Science, considering peer-reviewed publications from 2000 to January 2025. 1,204 articles were identified. Inclusion criteria included studies on cybersecurity risks in healthcare, blockchain applications in the clinical setting, and regulatory references (eg, General Data Protection Regulation). Conference abstracts, non-English articles, and non-peer-reviewed contributions were excluded. To ensure methodological rigor, the Scale for the Assessment of Narrative Review Articles criteria were applied.ResultsThe thematic analysis highlighted recurring critical issues: difficulties with informed consent, unauthorized access to sensitive data, and systemic vulnerabilities in hospital digital infrastructures. Blockchain presents a promising solution thanks to its decentralization, immutability, and transparency. Integration with smart contracts enables dynamic consent management, secure data sharing, and real-time monitoring of medical devices. Permissioned networks improve traceability and regulatory compliance, while Layer 2 solutions and optimized consent protocols address scalability challenges.ConclusionDespite its potential, blockchain adoption faces obstacles: high costs, regulatory rigidity, and poor acceptance among healthcare professionals. The review highlights the need for pilot projects, interdisciplinary collaboration, and regulatory updates for effective integration. Combining AI and blockchain in Clinical Risk Management can transform clinical risk management from reactive to proactive, improving patient safety, data governance, and accountability.

IntroductionChronic kidney disease (CKD) treatment is often delayed in many countries, creating challenges for the health system. Therefore, it is necessary to strengthen its detection and management from the early stages. Local experiences that have been successful in managing CKD could transfer their policies and thus systematically expand the scope of their organizational learning.PurposeTo characterize the elements of a success story of early detection and care of CKD in an adult population with social security, in order to transfer it to a similar organization.Patients and MethodsQualitative study of organizational nature, exploratory, descriptive, and analytical. It consisted of a narrative review, documentation of the process in a primary care unit of a social security institution in Jalisco, Mexico, and a flowchart linking the primary components. The analysis followed the questions used in the design of integrated care pathways.ResultsThe literature review highlighted that early detection should be targeted at groups at risk for developing CKD, defining the clinical tests necessary to monitor and stage CKD, as well as management by a multidisciplinary team and the use of nephroprotective drugs. The case characterization provided insight into the institutional context in which the care process for patients with risk factors for CKD takes place. By incorporating the results of the review into the clinical care process, an ideal process for early detection of CKD was developed.ConclusionThis research allowed the incorporation of elements of the institutional context in the characterization of the process of early detection and care of CKD, systematically identifying organizational and clinical elements that can promote the transfer of this process to other contexts.

BackgroundTo better understand the temporal evolution of healthcare utilization in Shanghai, this study examines changes in Shanghai’s ecology of medical care from 2018 to 2023 and compares them with other countries to contextualize global trends.MethodsUsing data from the 7th Shanghai Health Service Survey (2023), this study estimated monthly health-related symptoms and healthcare-seeking behaviors per 1,000 residents, examined subgroup differences via logistic regression, and contextualized findings through a scoping review of international studies applying the ecology of medical care framework.ResultsIn 2023, per 1,000 Shanghai residents per month, 503 reported illness, 495 sought treatments (including healthcare visits or self-medication), 228 visited healthcare facilities, 144 visited primary care, 98 self-medicated, 31 used TCM, 6 were hospitalized, and 3 underwent surgery. Compared to 2018, self-reported illness (+59), treatment seeking (+62), and self-medication (+6) increased, while outpatient visits, primary care, TCM use, and hospitalizations declined. Internationally, Shanghai shows relatively low illness reporting, primary care use, TCM use, and hospitalization rates, but relatively high treatment-seeking and self-medication.ConclusionThese findings suggest a shift in Shanghai’s healthcare utilization from formal services toward individual-led actions, with increased treatment-seeking, higher self-medication, and decreased outpatient, primary care, TCM, and hospitalization use. Internationally, Shanghai shows a distinctive pattern of high treatment-seeking and self-care despite low formal service use, indicating greater reliance on informal health strategies.

PurposeFMEA (Failure Mode and Effects Analysis), a widely used tool in risk management, lacks systematic guidance on selecting the type of precaution. This study introduces a rule-based FMEA. Although the Risk Priority Number (RPN), widely used in the literature, expresses the risk level quantitatively, it is insufficient for guiding the appropriate type of precaution. The proposed rule-based model uses a multi-dimensional rule system that considers numerical parameters (probability, severity, detectability, and RPN) and contextual variables.Material and MethodsThe model, structured according to the Occupational Health and Safety precaution hierarchy, defines six precaution classes: elimination, substitution, engineering measures, training, administrative measures, and personal protective equipment (PPE). The model’s theoretical consistency, sensitivity, and practical applicability were tested in a neonatal intensive care unit (NICU).ResultsThe FMEA method identified 24 failure modes related to infections. Scenario-based sensitivity analyses revealed that contextual variables significantly influenced the recommended precautions. Administrative and training measures were the most frequently recommended, while PPE was consistently recommended for exposure-related risks. Expert evaluation indicated 95.8% agreement with the model outputs.ConclusionThese findings indicate that the development of a rule-based system can serve as a repeatable and explainable decision-support tool, especially in high-risk settings such as healthcare, which is the study’s most distinctive contribution.