Search Results (3,515)

Neuromuscular hip dysplasia (NHD) is a common deformity in children with cerebral palsy (CP). Although some predictive factors of NHD are known, the prediction of NHD is in its infancy. We present a Clinical Decision Support System (CDSS) designed to calculate the probability of developing NHD in children with CP. The system utilizes an ensemble of three machine learning (ML) algorithms: Neural Network (NN), Support Vector Machine (SVM), and Logistic Regression (LR). The development and evaluation of the CDSS followed the DECIDE-AI guidelines for AI-driven clinical decision support tools. The ensemble was trained on a data series from 182 subjects. Inclusion criteria were age between 12 and 18 years and diagnosis of CP from two specialized units. Clinical and functional data were collected prospectively between 2005 and 2023, and then analyzed in a cross-sectional study. Accuracy and area under the receiver operating characteristic (AUROC) were calculated for each method. Best logistic regression scores highlighted history of previous orthopedic surgery (p = 0.001), poor motor function (p = 0.004), truncal tone disorder (p = 0.008), scoliosis (p = 0.031), number of affected limbs (p = 0.05), and epilepsy (p = 0.05) as predictors of NHD. Both accuracy and AUROC were highest for NN, 83.7% and 0.92, respectively. The novelty of this study lies in the development of an efficient Clinical Decision Support System (CDSS) prototype, specifically designed to predict future outcomes of neuromuscular hip dysplasia (NHD) in patients with cerebral palsy (CP) using clinical data. The proposed system, PredictMed-CDSS, demonstrated strong predictive performance for estimating the probability of NHD development in children with CP, with the highest accuracy achieved using neural networks (NN). PredictMed-CDSS has the potential to assist clinicians in anticipating the need for early interventions and preventive strategies in the management of NHD among CP patients. Full article

Background/Objectives: Osteoporosis remains a leading cause of morbidity in postmenopausal women, yet many high-risk individuals remain undiagnosed or untreated. This study aimed to assess the prevalence of osteoporosis and osteopenia, treatment patterns, and skeletal fragility indicators in a large cohort of postmenopausal women undergoing DXA screening. Methods: We analyzed data from 1669 postmenopausal women aged 40–89 years who underwent DXA evaluation. BMD status was categorized as normal, osteopenia, or osteoporosis. Treatment status was classified based on active antiosteoporotic therapy, calcium/vitamin D supplementation, hormonal therapy (historical use), or no treatment. Logistic regression models were used to explore independent predictors of osteoporosis and treatment uptake. Results: A total of 45.0% of women had osteoporosis and 43.5% had osteopenia. Despite this, 58.5% of the population, over half of women with osteoporosis, were not receiving any active pharmacologic treatment. Bisphosphonates were the most prescribed therapy (17.9%), followed by calcium/vitamin D supplements (20.6%). A prior history of fragility fractures and radiological bone lesions were significantly associated with lower BMD (p < 0.05). Historical hormone replacement therapy (HRT) use was not associated with current BMD (p = 0.699), but women with HRT use reported significantly fewer fractures (p < 0.001). In multivariate analysis, later menopause age and low BMD status predicted higher odds of receiving active treatment. Conclusions: Our findings highlight a substantial care gap in osteoporosis management, with treatment primarily initiated reactively in more severe cases. Improved screening and earlier intervention strategies are urgently needed to prevent fractures and reduce the long-term burden of osteoporosis. Full article

Background: Pancreatic adenocarcinoma (PDAC) with liver oligometastases (LOM) presents a therapeutic challenge, with optimal management strategies remaining uncertain. This study evaluates the long-term outcomes, patterns of disease progression, and potential factors influencing prognosis in this patient subset. Methods: Patients diagnosed with PDAC and LOM were retrospectively analyzed. Disease progression patterns, causes of death, and predictors of long-term outcomes were assessed. Results: Among 1442 patients diagnosed with metastatic PDAC between November 2009 and July 2024, 129 (9%) presented with LOM, defined as ≤3 liver lesions each measuring <2 cm. Patients with LOM had significantly improved overall survival (OS) compared to those with high-burden disease (p = 0.026). The cause of death (local regional disease vs. systemic disease) could be determined in 74 patients (57%), among whom age at diagnosis, history of smoking, and white blood cell (WBC) count differed significantly between groups. However, no significant difference in OS was observed between the two groups (p = 0.64). Sixteen patients (22%) died from local complications of the primary tumor, including 6 patients (7%) who showed no evidence of new or progressive metastases. In competing risk and multivariable analysis, a history of smoking remained the only factor significantly associated with death due to local complications. Conclusions: Approximately one in five patients with PDAC-LOM died from local tumor-related complications—some without metastatic progression—highlighting a potential role for surgical intervention. Further multicenter studies are warranted to refine diagnostic criteria and better identify patients who may benefit from surgery. Full article

Background/Objectives: Acute kidney injury (AKI) is a common and severe complication in patients with acute myocardial infarction (AMI). Very elderly patients are at a heightened risk of developing AKI. Fibrinogen and albumin are well-known biomarkers of inflammation and nutrition, which are highly related to AKI. We aim to explore the predictive value of the fibrinogen-to-albumin ratio (FAR) for AKI in very elderly patients with AMI. Methods: A retrospective cohort of AMI patients ≥ 75 years old hospitalized at the First Affiliated Hospital of Xi’an Jiaotong University between January 2018 and December 2022 was established. Clinical data and medication information were collected through the biospecimen information resource center at the hospital. Univariate and multivariable logistic regression models were used to analyze the association between FAR and the risk of AKI in patients with AMI. FAR was calculated as the ratio of fibrinogen (FIB) to serum albumin (ALB) level (FAR = FIB/ALB). The primary outcome is acute kidney injury, which was diagnosed based on KDIGO 2012 criteria. Results: Among 1236 patients enrolled, 66.8% of them were male, the median age was 80.00 years (77.00–83.00), and acute kidney injury occurred in 18.8% (n = 232) of the cohort. Comparative analysis revealed significant disparities in clinical characteristics between patients with or without AKI. Patients with AKI exhibited a markedly higher prevalence of arrhythmia (51.9% vs. 28.1%, p < 0.001) and lower average systolic blood pressure (115.77 ± 25.96 vs. 122.64 ± 22.65 mmHg, p = 0.013). In addition, after adjusting for age, sex, history of hypertension, left ventricular ejection fraction (LVEF), and other factors, FAR remained an independent risk factor for acute kidney injury (OR = 1.47, 95%CI: 1.36–1.58). ROC analysis shows that FAR predicted stage 2–3 AKI with superior accuracy (AUC 0.94, NPV 98.6%) versus any AKI (AUC 0.79, NPV 93.0%), enabling risk-stratified management. Conclusions: FAR serves as both a high-sensitivity screening tool for any AKI and a high-specificity sentinel for severe AKI, with NPV-driven thresholds guiding resource allocation in the fragile elderly. Full article

Accurately predicting how quickly people will adopt electric vehicles (EVs) is vital for planning charging stations, managing supply chains, and shaping climate policy. We present a forecasting model that uses three separate Long Short-Term Memory (LSTM) branches—one for past EV sales, one for infrastructure and policy signals, and one for economic trends. An attention mechanism first highlights the most important weeks in each branch, then decides which branch matters most at any point in time. Trained end-to-end on publicly available data, the model beats traditional statistical methods and newer deep learning baselines while remaining small enough to run efficiently. An ablation study shows that every branch and both attention steps improve accuracy, and that adding policy and economic data helps more than relying on EV history alone. Because the network is modular and its attention weights are easy to interpret, it can be extended to produce confidence intervals, include physical constraints, or forecast adoption of other clean-energy technologies. Full article

Background: Patients diagnosed with melanoma are at increased risk of developing multiple primary melanomas (MPMs). Identifying clinical and genetic factors associated with MPM is critical for implementing personalized surveillance strategies. This study aims to describe the clinical, histopathological, and genetic characteristics of patients with MPM managed in a tertiary hospital and to contextualize findings within the current literature. Methods: We conducted a retrospective review of patients diagnosed with two or more primary melanomas between 2010 and 2023 at a tertiary dermatology unit. Demographic data, personal and family cancer history, phototype, melanoma characteristics, genetic testing, staging, treatments, and outcomes were collected. These data were compared with findings from the recent literature. Results: Thirteen patients (ten males, three females; median age: 59 years) were found to have a total of 33 melanomas. Most patients had Fitzpatrick phototype II and no immunosuppression. The number of melanomas per patient ranged from two to five. Synchronous lesions were observed in two patients. Common locations included the trunk and extremities. Histologically, 57% were in situ melanomas, and subsequent melanomas were generally thinner than the index lesion. Two patients showed progression to advanced disease. One patient was positive for MC1R mutation; the rest were negative or inconclusive. Additional phenotypic and environmental risk factors were extracted from patient records and are summarized as follows: Ten patients (76.9%) had Fitzpatrick skin phototype II, and three (23.1%) had phototype III. Chronic occupational sun exposure was reported in four patients (30.8%), while five (38.5%) recalled having suffered multiple sunburns during childhood or adolescence. Eight patients (61.5%) presented with a total nevus count exceeding 50, and five (38.5%) exhibited clinically atypical nevi. None of the patients reported use of tanning beds. Conclusions: Our findings are consistent with the existing literature indicating that patients with MPM often present with thinner subsequent melanomas and require long-term dermatologic follow-up. The inclusion of genetic testing and phenotypic risk factors enables stratified surveillance and supports the application of personalized medicine in melanoma management. Full article

This study developed a model to predict ships with high deficiency risk under Port State Control (PSC) through machine learning techniques, particularly the Random Forest algorithm. The study utilized actual ship inspection data from the Port of Singapore, comprehensively considering various operational and safety indicators of ships, including but not limited to flag state, ship age, past deficiencies, and detention history. By analyzing these factors in depth, this research enhances the efficiency and accuracy of PSC inspections, provides decision support for port authorities, and offers strategic guidance for shipping companies to comply with international safety standards. During the research process, I first conducted detailed data preprocessing, including data cleaning and feature selection, to ensure the effectiveness of model training. Using the Random Forest algorithm, I identified key factors influencing the detention risk of ships and established a risk prediction model accordingly. The model validation results indicated that factors such as ship age, tonnage, company performance, and flag state significantly affect whether a ship exhibits a high deficiency rate. In addition, this study explored the potential and limitations of applying the Random Forest model in predicting high deficiency risk under PSC, and proposed future research directions, including further model optimization and the development of real-time prediction systems. By achieving these goals, I hope to provide valuable experience for other global shipping hubs, promote higher international maritime safety standards, and contribute to the sustainable development of the global shipping industry. This research not only highlights the importance of machine learning in the maritime domain but also demonstrates the potential of data-driven decision-making in improving ship safety management and port inspection efficiency. It is hoped that this study will inspire more maritime practitioners and researchers to explore advanced data analytics techniques to address the increasingly complex challenges of global shipping. Full article

The tufted deer (Elaphodus cephalophus), a Near-Threatened (NT) species endemic to China and Myanmar, requires robust genetic data for effective conservation. However, the genetic landscape of key populations, such as those in Chongqing, remains poorly understood. This study aimed to comprehensively evaluate the genetic diversity, population structure, gene flow, and demographic history of tufted deer across this critical region. We analyzed mitochondrial DNA (mtDNA) from 46 non-invasively collected fecal samples from three distinct populations: Jinfo Mountain (JF, n = 13), Simian Mountain (SM, n = 21), and the Northeastern Mountainous region (NEM, n = 12). Genetic variation was assessed using the cytochrome b (Cyt b) and D-loop regions, with analyses including F_st, gene flow (N_m), neutrality tests, and Bayesian Skyline Plots (BSP). Our results revealed the highest genetic diversity in the SM population, establishing it as a genetic hub. In contrast, the JF population exhibited the lowest diversity and significant genetic differentiation (>0.23) from the SM and NEM populations, indicating profound isolation. Gene flow was substantial between SM and NEM but severely restricted for the JF population. Demographic analyses, including BSP, indicated a long history of demographic stability followed by a significant expansion beginning in the Middle to Late Pleistocene. We conclude that the SM/NEM metapopulation serves as the genetic core for the species in this region, while the highly isolated JF population constitutes a distinct and vulnerable Management Unit (MU). This historical demographic expansion is likely linked to climatic and environmental changes during the Pleistocene, rather than recent anthropogenic factors. These findings underscore the urgent need for a dual conservation strategy: targeted management for the isolated JF population and the establishment of ecological corridors to connect the Jinfo Mountain and Simian Mountain populations, ensuring the long-term persistence of this unique species. Full article

There is limited published guidance available to help less experienced practitioners assess and manage shoulder conditions, including spasticity, after acquired central nervous system (CNS) lesions. To address this gap, 11 spasticity and dystonia experts convened in a 2023 meeting to build on existing guidance, provide consensus on best treatment practice, and develop expert recommendations to guide the diagnosis and treatment of complications of shoulder conditions following CNS lesions. Presentations by each expert on diagnosis and management were followed by discussion; consensus on assessment and treatment practices was identified and recommendations developed. The expert panel recommended an assessment approach structured using the following components: patient history, including interpretation of reported symptoms; observation of postures and pain responses; clinical examination with targeted tests for specific signs; diagnostic tests; and assessment of upper limb impairment, activity limitations, and participation restrictions. This assessment process and the recommended measures recognize the importance of identifying shoulder involvement in upper limb spasticity as part of the diagnostic process in shoulder conditions following CNS lesions. These recommendations provide a practical approach to diagnosis and treatment for clinicians who are less experienced in evaluating and treating such conditions, simplifying otherwise complicated clinical scenarios. Full article

Background/Objectives: Acute kidney injury (AKI) worsens outcomes in COPD exacerbation (COPDe), yet limited data compare the demographics and mortality risk factors of COPDe admissions with and without AKI. Understanding this association may enhance risk stratification and management strategies. The aim of this study was to identify demographic differences and mortality risk factors in COPDe admissions with and without AKI. Methods: We conducted a retrospective cohort study using the National Inpatient Sample (NIS) from 1 January 2016 to 1 January 2021. Patients aged ≥ 35 years with a history of smoking and a diagnosis of COPDe were included. Patients with CKD stage 5, end-stage kidney disease (ESKD), heart failure decompensation, urinary tract infections, myocardial infarction, alpha-1 antitrypsin deficiency, or active COVID-19 infection were excluded. Baseline demographics were analyzed using descriptive statistics. Multivariate logistic regression analysis was used to measure the odds ratio (OR) of mortality. Statistical analyses were conducted using IBM SPSS Statistics V.30, with statistical significance at p < 0.05. Results: Among 405,845 hospitalized COPDe patients, 13.6% had AKI. These patients were older, had longer hospital stays, and included fewer females and White patients. AKI was associated with significantly higher mortality (OR: 2.417), more frequent acute respiratory failure (OR: 4.559), intubation (OR: 10.262), and vasopressor use (OR: 2.736). CVA, pneumonia, and pulmonary hypertension were significant mortality predictors. Hypertension, CAD, and diabetes were associated with lower mortality. Conclusions: AKI in COPDe admissions is associated with worse outcomes. Protective effects from certain comorbidities may relate to renoprotective medications. Study limitations include coding errors and retrospective design. Full article

Background: The prevalence of BARD1 mutations in breast and ovarian cancers varies across different ethnic groups. Evaluating the cancer risk and clinical significance of BARD1 mutations in the local Chinese patients with breast cancer, ovarian cancer, or both is clinically important for designing an appropriate surveillance scheme. Methods: This study used a 30 gene panel to identify BARD1 germline mutations in 2658 breast and ovarian cancer patients. Results: Among this cohort, the BARD1 mutation prevalence was 0.45% for breast cancer and 0.29% for ovarian cancer. In our 12 mutation carriers, we identified eight types of mutation variants, including three novel mutations. BARD1 mutation carriers were more likely to have a family history of liver, prostate, and cervical cancers (p-values = 0.004, 0.018, and 0.037, respectively) than patients who tested negative for mutations. Among the BARD1 mutants, the majority of the breast tumors were invasive ductal carcinoma (NOS type) (10/11, 90.9%) of high-grade disease (9/9, 100%) and half of them were triple-negative breast cancer (5/10, 50%). Conclusions: Although the prevalence of BARD1 mutations is low and the penetrance is incomplete, we recommend including BARD1 in the test panel for breast cancer patients. Our data suggest that more comprehensive surveillance management may be considered in mutation carriers due to the familial aggregation of a relatively wide spectrum of cancers. Full article

The need for systems that forecast and respond proactively to meteorological disasters is growing amid climate variability. Although the early warning system in South Korea includes countermeasure information, it remains limited in terms of data recency, granularity, and regional adaptability. Additionally, its closed architecture hinders interoperability with external systems. This study aims to redesign the countermeasure function as an independent cloud-based platform grounded in the common standard terminology framework in South Korea. A multi-dimensional data model was developed using attributes such as crop type, cultivation characteristics, growth stage, disaster type, and risk level. The platform incorporates user-specific customization features and history tracking capabilities, and it is structured using a microservices architecture to ensure modularity and scalability. The proposed system enables real-time management and dissemination of localized countermeasure suggestions tailored to various user types, including central and local governments and farmers. This study offers a practical model for enhancing the precision and applicability of agrometeorological response information. It is expected to serve as a scalable reference platform for future integration with external agricultural information systems. Full article

Modern aircraft increasingly utilizes highly integrated electronic equipment, driving continuously increasing heat dissipation demands. Vapor compression refrigeration systems demonstrate stronger alignment with future aircraft thermal management trends, leveraging their superior volumetric cooling capacity, high energy efficiency, and independence from engine bleed air. This paper reviews global research progress on aircraft vapor compression refrigeration systems, covering performance optimization, dynamic characteristics, control strategies, fault detection, and international development histories and typical applications. Analysis identifies emerging challenges under large-temperature-range cooling requirements, with comparative assessment establishing zeotropic mixture auto-cascade vapor compression refrigeration systems as the optimal forward-looking solution. Finally, recognizing current research gaps, we propose future research directions for onboard auto-cascade vapor compression refrigeration systems: optimizing refrigerant mixtures for flight conditions, achieving efficient gas-liquid separation during variable overloads and attitude conditions, and developing model predictive control with intelligent optimization to ensure reliability. Full article

Gastric cancer traditionally affects older adults, and its precursor lesions and risk factors are well-documented in this population. Helicobacter pylori (H. pylori) infection remains highly prevalent in Saudi Arabia and contributes to gastric pathology. However, early-onset gastric cancer (EOGC), diagnosed in individuals aged ≤ 45 years, presents unique challenges and remains poorly understood in young populations. Therefore, we conducted an observational cohort study using a prospective longitudinal design (2021–2024) involving 1823 Saudi nationals aged 18–45 years who underwent zoom high-definition chromoendoscopy to evaluate the prevalence of premalignant gastric lesions (PGLs) and EOGC. We found a high H. pylori prevalence (78.0%) with PGLs in 1.9% of participants and EOGC-adenocarcinoma in 0.7% of patients. All EOGC cases arose from dysplasia, with most PGLs being classified as OLGA/OLGIM stage II/III. Multiple risk factorswere significantly associated with PGLs and EOGC, including H. pylori infection (p = 0.022), increasing age (p < 0.001), a family history of gastric cancer (p < 0.001), poor dietary habits (p < 0.001), obesity (p < 0.001), and smoking (p < 0.001). Additional EOGC risk factors include dage of 36–45 years (p = 0.018), EBV infection (p = 0.016), and diabetes mellitus (p = 0.001). These findings demonstrate the notable presence of PGLs and EOGC in young Saudi adults and emphasize the importance of early detection and risk factor management in this vulnerable population. Full article

Background/Objectives: Malnutrition is a common problem in children with cerebral palsy (CP). The aim of this study was to investigate the suitability and diagnostic performance of mid-upper arm circumference (MUAC) z-score in diagnosing wasting in children with CP, and its impact on diagnostic accuracy when evaluated concomitantly with additional clinical factors (birth weight, history of phototherapy). Methods: This single-center, cross-sectional study included 83 children with CP, aged 6 months–17 years, followed-up in our clinic. Anthropometric measurements (MUAC, Body Mass Index (BMI)) and clinical data (birth weight, history of phototherapy, Gross Motor Function Classification System (GMFCS)) were prospectively collected. Wasting was defined according to the BMI z-score ≤ −2 criteria. The diagnostic performance of MUAC z-score was evaluated by Receiver Operating Characteristic (ROC) analysis. The contribution of additional covariates was examined using logistic regression analysis and the backward elimination method. Results: MUAC z-score alone demonstrated good discrimination in diagnosing wasting with an Area Under the Curve (AUC) value between 0.805 and 0.821, but its sensitivity was limited (67.0%). No statistically significant difference was found in diagnostic performance between MUAC measurements of the right arm, left arm, and the unaffected arm (p > 0.050). In logistic regression analysis, MUAC z-score (p = 0.001), birth weight (p = 0.014), and a history of phototherapy (p = 0.046) were found to be significantly associated with wasting malnutrition. The simplified model including these variables yielded an AUC value of 0.876. Conclusions: MUAC z-score is a usable tool for wasting malnutrition screening in children with CP. Although its sensitivity is limited when used alone, its diagnostic accuracy increases when evaluated concomitantly with additional clinical factors such as birth weight and a history of phototherapy. This combined approach may offer clinicians a more robust tool for the early diagnosis and management of wasting malnutrition in children with CP. Full article