Objective To investigate the association between the hemoglobin-to-red cell distribution width ratio (HRR) and in-hospital and 30-day mortality among critically ill patients with atrial fibrillation (AF). Methods We conducted a retrospective cohort study of AF patients from the MIMIC-III and IV databases. Patients were divided into HRR quartiles. The primary outcomes were in-hospital and 30-day mortality. Kaplan-Meier survival curves, dose-response analysis, and multivariable regression models assessed HRR-mortality associations, with subgroup and sensitivity analyses for robustness. Results Among 21,625 patients (median age 75.0 years, 59.8% male), in-hospital and 30-day mortality rates were 14.8% and 24.5%. Mortality was inversely related to HRR, with Q1 showing higher risk than Q4 (in-hospital: 20.0% vs. 12.7%). Dose-response analysis revealed linear HRR-mortality relationships. In adjusted models, each 0.1-unit HRR increase reduced risk by 37% for in-hospital mortality (OR: 0.63, 95% CI: 0.60-0.66) and 31% for 30-day mortality (HR: 0.69, 95% CI: 0.67-0.71). Compared with Q1, Q4 was associated with 79% lower adjusted odds of in-hospital mortality and a 71% lower adjusted hazard of 30-day mortality. Subgroup analyses confirmed consistent protective associations, with modification by age and myocardial infarction. Conclusions Higher HRR was independently associated with lower in-hospital and 30-day mortality in critically ill patients with atrial fibrillation. Higher HRR associates with improved survival, supporting its potential role as a complementary marker for risk assessment and prognostic evaluation.
Objective The present study aimed to develop and evaluate machine learning-based predictive models for acute kidney injury (AKI) and all-cause mortality in patients treated with imipenem or meropenem, integrating pharmacokinetic (PK) parameters with routine clinical features. Methods A total of 235 patients who received imipenem (n = 121) or meropenem (n = 114) between May 2021 and November 2023 were included. Elimination phase and trough concentrations were quantified by UPLC-MS/MS, and a nonlinear mixed-effects model was applied to derive PK/PD parameters. Linear regression was performed to examine associations between baseline characteristics and trough concentrations. Logistic regression was used for initial feature screening, after which 13 machine learning classifiers were developed to predict AKI and mortality. Model discrimination was evaluated using bootstrap internal validation, calibration was assessed via calibration curves, feature importance was examined using SHAP values, and clinical utility was evaluated through decision curve analysis. Results The incidence of AKI was 25.6% (31/121) in the imipenem group and 10.5% (12/114) in the meropenem group. For imipenem-related AKI, the Random Forest classifier yielded the highest discriminative performance (AUC: 0.996, 95% CI: 0.988-1.000); XGBoost performed optimally for meropenem-related AKI (AUC: 0.938, 95% CI: 0.876-1.000). For mortality prediction, Random Forest achieved the best performance for the imipenem group (AUC: 0.963, 95% CI: 0.923-1.000) and XGBoost for the meropenem group (AUC: 0.983, 95% CI: 0.957-1.000). SHAP analysis identified renal function indicators and PK parameters as the predominant contributors to model predictions. Decision curve analysis confirmed favorable net benefit across all optimal models. Conclusions Machine learning models integrating PK parameters with clinical features demonstrated discriminative ability for predicting carbapenem-associated AKI and mortality. These findings support further investigation into the combination of therapeutic drug monitoring and machine learning analytics for risk stratification, though prospective external validation is required.
Objective To systematically investigate whether the pathogenesis of polycystic ovary syndrome (PCOS) is causally related to dysregulated gene expression in specific immune cell subsets, and to evaluate the potential of these causal genes as actionable drug targets. Methods This study employed a two-sample Mendelian randomization (MR) framework using publicly available genome-wide association study (GWAS) summary statistics. The participant data included 797 PCOS cases and 140,558 controls (no direct patient recruitment was involved). Instrumental variables were derived from high-resolution immune cell-specific single-cell expression quantitative trait locus (sc-eQTL) data (OneK1K project) across 14 immune cell types. Primary analyses utilized the inverse-variance weighted (IVW) method. Shared causal variants were validated using Bayesian colocalization. Phenome-wide association analysis (PheWAS), external transcriptomic dataset validation (GSE8157), and DrugBank database screening were conducted for pleiotropy assessment and drug repositioning. Results MR analysis revealed genome-wide significant causal associations for GLIPR1 in non-classical monocytes (Mono NC) and XBP1 in CD4+ effector memory T cells (CD4 ET) with PCOS risk. Higher GLIPR1 expression was associated with a decreased PCOS risk (OR = 0.669, P = 4.34×10 -6 ), whereas higher XBP1 expression was associated with an increased risk (OR = 1.406, P = 9.53×10 -8 ). Colocalization analysis confirmed that GLIPR1 shares a causal variant with PCOS (PP.H4 = 96.73%). PheWAS and external validation confirmed the safety profile and significant upregulation (P = 0.03) of GLIPR1. Drug repositioning identified SOT-107, a Phase III protein therapy drug, as a potential interacting agent for GLIPR1. Conclusions This sc-eQTL MR study reveals immune cell-specific causal regulatory networks in PCOS. GLIPR1 in non-classical monocytes represents a high-confidence protective target, while XBP1 provides suggestive evidence for immune-mediated pathogenesis. The candidate drug SOT-107 highlights theoretical repositioning opportunities, though rigorous preclinical validation remains required.
Objective This study aimed to validate the prognostic discriminatory power of the revised International Federation of Gynecology and Obstetrics (FIGO) 2018 staging system and to evaluate the association between regional lymph node resection (RLNR) and survival in cervical cancer (CC) patients who underwent RLNR followed by chemotherapy and radiotherapy. Methods In this retrospective cohort study utilizing the Surveillance, Epidemiology, and End Results (SEER) database (2000–2018), patients were categorized into early-stage (IA/IB1-IB2/IIA1) and locally advanced-stage (IB3/IIA2-IIB/III/IVA) groups. Survival outcomes were analyzed using Kaplan–Meier, univariate and multivariate Cox regression (including time-dependent), and year-of-diagnosis stratified analyses, applied to crude, inverse probability of treatment weighting (IPTW)-weighted, and propensity score matching (PSM)-matched models. Results The FIGO 2018 system revealed significant survival differences between IB1 vs IB2 and IIIC1 vs IIIA/IIIB (all p < 0.001). In early-stage patients, RLNR conferred no significant survival benefit. However, in locally advanced-stage patients, RLNR with primary surgery was associated with better survival than RLNR alone. In the cohort without primary surgery, RLNR alone was consistently identified as a prognostic factor versus non-surgery across all three analytical models (IPTW as primary, PSM as sensitivity; all p<0.001). The hazard ratios for RLNR alone versus non-surgery were all below 1.000, and year-of-diagnosis stratified analyses further supported this protective association, with consistently directional estimates. Conclusion This study suggested the prognostic value of the FIGO 2018 staging system and hypothesized that RLNR is a prognostic factor for better survival compared with chemotherapy and radiotherapy alone in locally advanced-stage CC, although the limitations of a retrospective study must be acknowledged.
Bioactive coatings have attracted considerable attention in the context of orthopedic and dental implantology, where establishing a stable and biologically active interface between the implant surface and surrounding hard tissue remains a central challenge. The present review examines the principal coating categories inorganic, organic, and hybrid with particular attention to their roles in promoting osseointegration, supporting bone regeneration, and reducing implant-associated infection in musculoskeletal and craniofacial applications. This review offers an in-depth examination of bioactive coatings, categorizing them into three main classes: inorganic, organic, and hybrid. It delves into their preparation techniques, characterization methods, and evaluation processes, detailing how these coatings are engineered and tested for optimal performance. Beyond the technical aspects, the review highlights several critical issues in the field, such as achieving long-term stability, preserving biofunctionality under physiological conditions, and enabling cost-effective scalability for broad application. Addressing these challenges could lead to significant progress, ranging from enhanced implant performance to reduced complications and improved patient outcomes. By overcoming existing limitations and integrating emerging technologies, bioactive coatings are well-positioned to play an important role in the future of medical device innovation and regenerative medicine, paving the way for more effective and personalized therapeutic solutions.
Objective Nonobstructive azoospermia (NOA), a severe male reproductive disorder, has a complex pathogenesis. This study aimed to identify novel oxidative stress potential biomarkers for NOA using bioinformatics. Methods Datasets GSE9210, GSE108886, and GSE45885 from the GEO database were used for training, while GSE145467 supported weighted gene coexpression network analysis. The limma package identified differentially expressed genes, cross-referenced with oxidative stress genes from GeneCards for drug prediction. Three machine learning algorithms identified potential hub genes, validated by GSE45887 and GSE216907. Advanced analyses focused on these hub genes, including regulatory networks and single-gene enrichment studies. qRT-PCR validated hub gene expression, and single-cell RNA sequencing (GSE149512 and GSE202647) explored cellular expression patterns. Results IL1RN , NOSIP , PDYN , PRKCZ , and UTRN were potential NOA markers. qRT-PCR validation confirmed IL1RN , NOSIP , PRKCZ , and UTRN align with bioinformatic results. Single-cell analysis showed stage-specific dysregulation of these four genes in NOA. Conclusions This study broadens the spectrum of known NOA candidate biomarkers and enhances the comprehension of NOA.
Objective Surgical decision-making during arthroscopic procedures often relies on the subjective visual assessment of tissue morphology, particularly the redness of the long head of the biceps tendon (LHB), which serves as an indicator for potential surgical intervention. This subjectivity introduces variability across clinicians, underscoring the need for objective, data-driven methods. The present study aimed to evaluate the feasibility of applying the MASKRCNN_RESNET50_FPN deep learning model for automated segmentation of the LHB in arthroscopic images, thereby converting subjective visual assessments into quantifiable, reproducible measurements. Methods This original research article is a retrospective cohort analysis of arthroscopic images obtained from 124 participants (84 male, 40 female) who underwent arthroscopic procedures between March 2015 and May 2019 at a single institution. From a comprehensive database of 130,000 arthroscopic images, 15,000 images featuring the LHB were identified, and 200 were selected for manual annotation by an experienced physician. The MASKRCNN_RESNET50_FPN model, combining a ResNet50 backbone with a Feature Pyramid Network and a mask prediction branch, was trained for 10,000 iterations using the AdamW optimizer (learning rate 1×10 -5 ) with transfer learning from COCO-pretrained weights. Model performance was assessed through expert evaluation on 400 randomly selected validation images and through automated pixel-level evaluation computing Precision, Recall, F1-score (Dice coefficient), and Intersection over Union (IoU). A baseline comparison with a U-Net (ResNet34 encoder) and three classical segmentation methods was performed. The reporting of this study conforms to the STROBE guidelines. Results Expert evaluation of 400 validation images yielded a precision of 0.88. The automated pixel-level evaluation on the same 400 images yielded a mean precision of 0.83, recall of 0.86, F1-score of 0.83, and IoU of 0.76 (median IoU: 0.90). The model demonstrated consistent performance across varying tendon orientations and background conditions, and effectively assigned low relevance scores (0.1–0.3) to imaging artifacts. In the baseline comparison, a U-Net achieved a higher mean IoU of 0.91 (Wilcoxon p < 0.001). The combined training loss converged to 0.0809 after 10,000 iterations. Conclusions The MASKRCNN_RESNET50_FPN model may serve as a tool for objective and reproducible segmentation of the LHB in arthroscopic images, with performance corroborated by both expert assessment and automated pixel-level evaluation. These findings suggest that deep learning-based image segmentation has the potential to reduce subjectivity in surgical decision-making. Limitations include the single-center design, limited demographic diversity, and the relatively small training dataset. Multi-center validation with a more diverse patient cohort is recommended.
This review critically examines integrated adsorption–degradation strategies for the remediation of air, water, and soil contaminants, with emphasis on recent advances reported since 2020. Rather than treating adsorption and degradation as standalone processes, the review highlights how adsorption functions as an effective pretreatment step that enhances degradation efficiency by increasing the pollutant concentration at reactive interfaces, improving mass transfer, and stabilizing reactive species. Comparative analyses across environmental media have shown that most studies target aqueous systems, while integrated approaches for air and soil remain underexplored. Representative systems—including TiO 2 -based photocatalysts, MOF-supported Fenton-like catalysts, and biochar-assisted electrochemical electrodes—demonstrate improved removal efficiency, reaction kinetics, and material reusability compared with single-process treatments. Key mechanisms underlying adsorption–degradation synergy are discussed, along with material design strategies that enable multifunctionality. This review identifies critical knowledge gaps in multiphase systems, real-field applications, and medium-specific optimization and outlines future research directions toward scalable, energy-efficient, and environmentally sustainable remediation technologies aligned with global sustainability goals. This review aligns with SDGs 6, 11, 12, 13, and 15 to promote clean water, sustainable urban environments, responsible production, climate action, and land restoration.
Objective Breast cancer (BC) is a major global health issue for women. Although insulin resistance (IR) and circadian disruption are both associated with BC, their interaction remains unclear. This study examined the association between circadian syndrome (CircS) and BC, and explored the mediating role of the triglyceride-glucose (TyG) index and related molecular mechanisms. Methods This cross-sectional study analyzed 5,498 women from the NHANES 2005–2014. Multivariate logistic regression assessed the association between CircS and BC, with mediation analysis to evaluate TyG’s indirect effect. Bioinformatics validation used TCGA-BRCA data, including differential expression of TyG and circadian rhythm-related gene sets, survival analysis, and pathway enrichment. Results Among 5,498 participants, 158 had BC. After adjusting for sociodemographic, lifestyle, and cardiovascular factors, CircS was significantly associated with higher BC risk (OR = 2.07, 95% CI: 1.12–3.83). Each one-unit increase in the TyG index was also linked to increased BC risk (OR = 1.64, 95% CI: 1.20–2.23). Mediation analysis showed the TyG index mediated 10.84% of CircS’s effect on BC (Indirect Effect: 0.0042, 95% CI: 0.0011–0.0103). Bioinformatics analysis identified dysregulated prognostic circadian rhythm DEGs and insulin receptor DEGs in tumors, and their expression correlated with overall survival. These genes were co-enriched in oncogenic pathways such as lipid metabolism and MAPK signaling. Conclusions This nationally representative study indicates that CircS is strongly associated with a higher prevalence of BC, with IR—measured by the TyG index—partially mediating this association. Molecular evidence shows that circadian and metabolic disruptions converge on key signaling pathways, suggesting a synergistic role in BC development.
Increasing attention has been drawn to the delamination of the external thermal insulation layer, which severely impacts the residents’ living quality and insurers’ claim risks. Therefore, the probability distribution of losses caused by external insulation layer delamination is investigated in this study through weather tests, considering that such delamination occurs due to a bond strength of zero, in order to provide scientific support for the inherent defect insurance (IDI). Using a thin-coat external thermal insulation system with expanded polystyrene (EPS) boards (500*500mm) as the test subject, weather tests were designed to simulate the monsoon climate in China. Bond strength testing was then performed to quantify the degradation level of the insulation layer. The results indicate that bond strength degradation and the initial bond strength under non-load conditions follows logistic distribution and Weibull distribution respectively, with 25% of the test blocks exhibiting Grade I damage. Additionally, the delamination failure probability is counted out 0.164 based on the structural reliability theory. Further analysis indicated that IDI claim frequencies can be approximated through a Poisson distribution using parameter λ, thereby establishing a quantitative model for insurers’ premium pricing and risk management. Moreover, the probabilistic patterns of insulation layer delamination were clarified by integrating experimental and theoretical methods, thereby not only addressing a critical knowledge gap in the IDI’s loss assessment for external insulation systems, but also directly enhancing the accuracy and reliability of construction quality insurance practices and IDI risk evaluation.
This study investigates a nonlinear fractional soliton neuron model that arises in fluid mechanics, nonlinear dynamics, mathematical physics, engineering, neuroscience, plasma physics, and related scientific fields. An efficient mapping approach is employed after transforming the governing nonlinear partial differential equation into an ordinary differential equation through a suitable wave transformation. A machine learning approach is also applied for data-driven analysis of the obtained solution. These two proposed methods yield a variety of exact analytical solutions, including lump, local breather, periodic, anti-kink, multiple bright-dark breather, singular soliton, bright soliton, and kink waves. Their propagation characteristics are illustrated using three-dimensional, two-dimensional, contour, polar, and surface-of-revolution plots generated in Maple. Stability properties of the model and the obtained solutions are also examined. Furthermore, nonlinear dynamics are explored through MATLAB-based chaos diagnostics, including bifurcation diagrams, strange attractors, recurrence plots, fractal dimensions, phase portraits, basins of attraction, return maps, power spectra, time series, and multistability. The results demonstrate that variations in the amplitude and frequency of external forcing significantly influence the system’s dynamical behavior.
Agricultural water management is essential for food security in high-altitude cold regions, such as the Qinghai–Tibet Plateau, the Rocky Mountains, and the Alps. However, extreme environmental conditions—including low temperatures, intense radiation, and complex terrain—impede traditional hydrological monitoring. This narrative review systematically evaluates “space-air-ground” multi-source sensing technologies, summarizing recent advances in satellite remote sensing, low-altitude Unmanned Aerial Vehicles (UAVs), and cold-resistant ground sensors to address these constraints. Beyond individual platforms, this study synthesizes how multi-source data fusion and edge computing enhance hydrological modeling and decision-making for regional drought monitoring, crop assessment, and precision irrigation. Finally, current challenges—such as insufficient cross-platform integration, limited data consistency, and poor model generalization—are critically analyzed, and future research directions are proposed to provide a theoretical framework for advancing smart irrigation.
Vestibular neurology has undergone substantial evolution over the past two decades, driven by advances in bedside diagnostics, neuroimaging, computational neuroscience, and therapeutics. Despite this progress, dizziness and vertigo remain among the most common yet diagnostically challenging neurological complaints. This narrative review examines the current state of vestibular neurology, focusing on key clinical syndromes, ongoing diagnostic controversies, and emerging opportunities for innovation. Particular attention is given to acute vestibular syndrome, audiovestibular disorders, bilateral vestibulopathy, functional dizziness, vestibular migraine, and the role of cerebral small vessel disease. In parallel, advances in understanding vestibular contributions to cognition and the development of novel therapeutic strategies, including vestibular implants, neuromodulation, and digital diagnostics, are highlighted. The field is at a pivotal stage, where integration of technology, improved phenotyping, and mechanistic insights promise to transform both diagnosis and management.
Objective Methotrexate (MTX) is a very effective agent used to treat rheumatoid arthritis and malignant diseases. Despite its usefulness, the long-term use of MTX is associated with multiorgan toxicities, including kidney injury. Thus, there is a necessity to explore a renoprotective agent with low side effects. Procyanidin B2 (PCB2), a natural flavonoid, possesses antioxidant and anti-inflammatory activities. This study aims to investigate the potential protective efficacy of PCB2 against MTX-induced nephrotoxicity. Methods Rats were allocated into four groups: control group, PCB2 group (40 mg/kg, p.o), MTX-intoxicated group (20 mg/kg, i.p.), and PCB2+MTX group. PCB2 was administered daily for ten days, while MTX was injected as a single dose on day 8. Oxidative stress and inflammatory biomarkers in kidney tissues were assessed using biochemical, histological, and immunohistochemical examinations. Results MTX markedly elevated the levels of kidney malondialdehyde (MDA), tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6), while glutathione (GSH) level and superoxide dismutase (SOD) activity were significantly reduced. In addition, rats intoxicated with MTX exhibited positive and strong immunoreactions for nucleotide-binding oligomerization domain 1 (NOD1), nuclear factor-kappa B (NF-κB), and mitogen-activated protein kinase (MAPK). The administration of PCB2 significantly prevented tissue injury and restored the altered parameters. Conclusions PCB2 reduced oxidative stress and inflammatory responses, indicating potential protective effects against MTX-induced kidney damage.
Objective To evaluate the cross-sectional association between routinely documented arteriovenous fistula thrill categories and Doppler hemodynamic parameters in mature radiocephalic fistulas. Methods This single-center retrospective observational study included 474 patients receiving maintenance hemodialysis with mature native radiocephalic fistulas who underwent color Doppler ultrasound between January 2021 and March 2025. Each patient contributed one eligible examination with same-visit thrill documentation classified as strong, weak, or absent before Doppler interpretation. Hemodynamic parameters, lesion-related records, exploratory receiver operating characteristic analyses, multivariable associations with abnormal thrill, and Doppler reproducibility were evaluated. Results Of 474 patients, 367 had strong thrill, 67 had weak thrill, and 40 had absent thrill. Median brachial artery blood flow decreased across the strong, weak, and absent groups from 783 to 206 and 86 mL/min, respectively, whereas median brachial artery resistance index increased from 0.53 to 0.78 and 1.00 (overall P < 0.001 for both). Stenosis-related records were most frequent in the weak-thrill group, whereas thrombosis-related records were concentrated in the absent-thrill group. For exploratory discrimination of abnormal versus strong thrill, blood flow had an AUC of 0.987 at a cohort-specific cutoff of 376 mL/min (sensitivity 98.1%, specificity 92.4%), and resistance index had an AUC of 0.969 at a cutoff of 0.69 (sensitivity 87.9%, specificity 95.9%). In the principal adjusted model, lower blood flow and higher resistance index remained independently associated with abnormal thrill (adjusted OR 0.25 per 100 mL/min and 2.92 per 0.1 unit, respectively; both P < 0.001). Measurement reproducibility was high. Conclusions Routinely documented thrill category was associated with Doppler hemodynamics in mature radiocephalic fistulas. The exploratory cutoffs describe separation between documentation groups and should not be interpreted as validated diagnostic thresholds or evidence of a thrill-based triage strategy.
Borderline personality disorder (BPD) is a severe and heterogeneous psychiatric condition characterized by emotional dysregulation, impulsivity, and interpersonal instability. Increasing evidence suggests that disruptions in white matter (WM) microstructure may contribute to its neurobiological underpinnings. Clarifying these findings is important because diffusion MRI studies in BPD remain heterogeneous in terms of age, symptom severity, comorbidity, medication status, trauma exposure, and analytic approach. This narrative review synthesizes current findings from diffusion tensor imaging (DTI) studies examining WM alterations in individuals with BPD and discusses key methodological considerations that influence the interpretation of results. Across studies, the most consistent abnormalities were observed in the corpus callosum, particularly the genu and body, which may reflect altered interhemispheric connectivity. Additional alterations were reported in fronto-limbic pathways, including the cingulum and fornix, as well as long association tracts such as the superior and inferior longitudinal fasciculi. These findings are consistent with the hypothesis that WM alterations in BPD may extend across large-scale structural networks that are anatomically connected to emotional and cognitive systems. However, results remain heterogeneous due to methodological variability, small sample sizes, and clinical heterogeneity. Differences in imaging techniques and analytical approaches further complicate comparisons across studies. Overall, WM alterations may represent one component of the neurobiological profile of BPD; however, their functional and clinical significance requires confirmation using advanced diffusion methods, longitudinal designs, and standardized protocols.
ObjectiveTo evaluate the diagnostic value of the preoperative CT-based Node Reporting and Data System (Node-RADS) score for lymph node metastasis (LNM) and its prognostic significance for disease-free survival (DFS) in NAC-naive, radically resected non-metastatic gastric cancer (GC, pTNM stage I-III), and to construct nomogram models for predicting LNM and DFS.MethodsThis retrospective study included NAC-naive GC patients who underwent radical gastrectomy with D2 lymphadenectomy between January 2019 and December 2022. Node-RADS scores were independently assessed by two radiologists. Logistic and Cox regression analyses were performed to identify independent predictors of LNM and DFS. Nomogram models were developed and evaluated using area under the curve (AUC), concordance index (C-index), calibration curves, and decision curve analysis.ResultsA total of 150 patients were included (median age 61 years). Pathological LNM was present in 72.7% of patients. Node-RADS scores were significantly associated with tumor size, CEA level, pTNM stage, N stage, and recurrence (all P < 0.05). Inter- and intra-observer agreement were good (κ = 0.746 and 0.798). Tumor size, CA19-9, and Node-RADS score were independent predictors of LNM. The LNM nomogram achieved an AUC of 0.88. During follow-up, 34.7% of patients developed recurrence, and Node-RADS score was significantly associated with DFS.ConclusionPreoperative CT-based Node-RADS scoring shows good diagnostic and prognostic value in gastric cancer and may assist in preoperative risk stratification.
ObjectiveTo evaluate the association between aspirin administration during the first 24 hours of intensive care unit (ICU) admission and 28-day all-cause mortality among critically ill adults with cerebral embolism and to explore associations with early cumulative dose.MethodsThis retrospective cohort study used MIMIC-IV version 3.1 and included each patient's first eligible adult ICU admission. Aspirin exposure was defined as at least one documented administration within 24 hours. After 1:1 propensity-score matching, 125 matched pairs were obtained. Associations were examined using Kaplan-Meier methods and Cox proportional hazards models, with exploratory dose, subgroup, and sensitivity analyses. Given only 45 deaths, a parsimonious Cox model was prioritized over the approximately 40-variable saturated model.ResultsThe cohort included 568 patients (430 aspirin-exposed and 138 unexposed), with 45 deaths by day 28. Aspirin exposure was associated with lower 28-day mortality before matching (HR 0.32, 95% CI 0.18-0.58; P<0.001) and after matching (HR 0.31, 95% CI 0.13-0.73; P=0.008). Matching improved balance, but residual imbalance remained; the largest absolute post-match standardized mean difference in Table 1 was 0.177. The parsimonious adjusted model produced a similar estimate (HR 0.31, 95% CI 0.17-0.57; P<0.001). Dose analyses were exploratory and hypothesis-generating; sparse dose-specific events, nonrandom treatment selection, and time-related exposure classification prevented identification of an optimal dose. Laboratory abnormalities were examined only as exploratory surrogates; clinical bleeding was not ascertained.ConclusionsIn this single-center retrospective cohort, aspirin exposure during the first 24 hours of ICU admission was associated with lower 28-day mortality. Residual confounding by unmeasured neurologic stroke severity (because NIHSS was unavailable), treatment eligibility, and goals of care, together with the absence of adjudicated bleeding outcomes, precludes causal, safety, or dose-prescriptive conclusions. Multicenter prospective studies and adequately powered randomized controlled trials are required before definitive clinical recommendations can be made.
Coats disease is a rare idiopathic retinal vascular disorder characterized by telangiectatic and aneurysmal retinal vessels, intraretinal and subretinal lipid exudation, and variable progression to exudative retinal detachment, secondary glaucoma, and severe visual loss. This narrative review summarizes the clinical spectrum, diagnostic evaluation, imaging features, and contemporary management of Coats disease, with emphasis on areas of diagnostic uncertainty and treatment controversy. The disease most commonly affects young males and is classically unilateral; however, rare bilateral presentations and Leber miliary aneurysms should be recognized within the broader spectrum of idiopathic retinal telangiectatic disease. Modern multimodal imaging, including wide-field photography, fluorescein angiography, optical coherence tomography, and optical coherence tomography angiography, has improved detection of peripheral nonperfusion, macular edema, subfoveal lipid, photoreceptor damage, and vascular abnormalities with prognostic implications. Management remains stage-dependent. Laser photocoagulation and cryotherapy remain the foundation of treatment, while anti-vascular endothelial growth factor therapy, corticosteroids, photodynamic therapy, and surgery have selective roles as adjunctive or advanced-stage interventions. The evidence base is limited by heterogeneous retrospective series, small case reports, and scarce comparative prospective data. Further multicenter studies are needed to define treatment algorithms, imaging biomarkers, long-term safety, and functional outcomes.
This paper proposes a local meshless collocation method based on global radial basis function (G-RBF) for one-dimensional convection-diffusion equations. The method transforms the equation into a steady-state form through time forward Euler discretization and uses local G-RBF interpolation with only three adjacent collocation points for spatial approximation. Numerical experiments have shown that this method has significant advantages in solving problems with different Péclet numbers. It not only has high accuracy, but also exhibits stable performance against numerical perturbations. It can effectively alleviate undesired numerical oscillations, notably reduce the condition number of discrete equations and cut down computational overhead, delivering a numerically reliable tool with competitive computational resource utilization for high-precision simulation of complex transport processes.
