Accurate optic disc and optic cup segmentation plays an important role for diagnosing glaucoma. However, most existing segmentation approaches suffer from the following limitations. On the one hand, image devices or illumination variations always lead to intensity inhomogeneity in the fundus image. On the other hand, the spatial prior knowledge of optic disc and optic cup, e.g., the optic cup is always contained inside the optic disc region, is ignored. Therefore, the effectiveness of segmentation approaches is greatly reduced. Different from most previous approaches, we present a novel locally statistical active contour model with the structure prior (LSACM-SP) approach to jointly and robustly segment the optic disc and optic cup structures. First, some preprocessing techniques are used to automatically extract initial contour of object. Then, we introduce the locally statistical active contour model (LSACM) to optic disc and optic cup segmentation in the presence of intensity inhomogeneity. Finally, taking the specific morphology of optic disc and optic cup into consideration, a novel structure prior is proposed to guide the model to generate accurate segmentation results. Experimental results demonstrate the advantage and superiority of our approach on two publicly available databases, i.e., DRISHTI-GS and RIM-ONE r2, by comparing with some well-known algorithms.

Stress hyperglycemia ratio (SHR) has emerged as a potential prognostic marker in critical illness, but its association with mortality in cardiovascular disease remains incompletely characterized. This study investigated the relationship between SHR and all-cause mortality in critically ill patients with cardiovascular disease, adjusting for a variety of confounding factors using propensity score matching (PSM). A cohort of 3,352 critically ill patients with cardiovascular disease was stratified by SHR quartiles (Q1–Q4). Baseline characteristics, comorbidities (e.g., heart failure, diabetes), and severity scores (OASIS, APSIII, SOFA) were extracted from a large database containing de-identified health data patients admitted to the intensive care units (ICUs) of Beth Israel Deaconess Medical Center. PSM (670 matched pairs) balanced covariates between high (SHR > 1.355) and low SHR groups. The associations between SHR and mortality risk (in-hospital, 28-day, 90-day, 365-day) were evaluated using Cox models, restricted cubic spline (RCS) analysis, and Kaplan-Meier survival curves. Cox proportional hazards models were implemented with three sequential adjustment levels: Model 1 (unadjusted); Model 2 (adjusted for demographic factors and comorbidities); and Model 3 (fully adjusted). Predictive performance of SHR combined with severity scores was assessed via area under the curve (AUC) improvement. Higher SHR quartiles exhibited greater comorbidity burden (e.g., acute kidney injury: 84.6% in Q4 vs. 79.7% in Q1, P < 0.001) and severity scores (P < 0.001). Unadjusted analysis showed a significant association between SHR and mortality, with Q4 having the highest in-hospital (Q4: 16.3% vs. Q1–Q3: 5.1–6.4%, P < 0.001) and 365-day mortality (Q4: 29.2% vs. Q1–Q3: 15.7–16.9%, P < 0.001). The RCS analysis revealed a U-shaped mortality risk, with average optimal SHR cutoffs of 1.355. After PSM, cox proportional hazard models confirmed that high SHR (Q4) remained associated with early mortality (in-hospital HR = 2.117, [95% CI: 1.223–3.665], P = 0.007; 28-day HR = 1.859, [95% CI: 1.100-3.141], P = 0.020) but not long-term outcomes (90-day mortality, P = 0.127; 365-day mortality, P = 0.123) in the Model 1. Similar trends were obtained after adjusting for demographic factors and comorbidities (Model 2) and in the fully adjusted model (Model 3). Adding SHR improved short-term mortality prediction performance (e.g., OASIS AUC: +0.034 for in-hospital, P < 0.001), though benefits diminished post-PSM (e.g., OASIS: +0.012 for in-hospital, P = 0.009). However, incorporating SHR did not enhance the predictive performance of OASIS and SAPSII for 90-day and 365-day mortality prediction after PSM. Elevated SHR contributes to early mortality in patients with cardiovascular disease, even after rigorous confounder adjustment. The incremental predictive value of SHR support its utility for risk stratification, particularly for short-term outcomes, but its prognostic value fades for long-term mortalities. These findings highlight SHR as a favorable biomarker for clinical decision-making in acute cardiovascular care.

Intrinsic Capacity (IC) is a crucial measure of the comprehensive physiological and psychological capabilities of older adults, playing a key role in assessing healthy aging. This systematic review aims to explore the trajectories of IC in older adults, as well as the associated determinants and health outcomes. By searching through PubMed, Embase, Ovid, and Web of Science databases, we identified 13 studies that met our inclusion criteria. To ensure the rigor of the review, the Newcastle-Ottawa Scale (NOS) critical appraisal tool for cohort studies and the Guidelines for Reporting on Latent Trajectory Studies were employed to assess the quality of the studies included. When IC is represented as a single composite value, there are primarily three trajectory types: declining trajectory (characterized by a sharp, moderate, or mild decline from baseline IC), stable trajectory (little change compared to baseline IC), and high trajectory (high baseline IC with an increasing trend). When IC is broken down into individual dimensions, these trajectories primarily reflect the degree of impairment in different domains and changes in IC status. The trajectories can be divided into robust status (no impaired domains, stable IC status), mild impairment (impairment in 1–2 domains, mild IC impairment), and severe impairment (impairment in multiple domains, severe IC impairment). Factors influencing IC trajectories include age, gender, education level, ethnicity, number of chronic diseases, marital status, perceived financial adequacy, economic assistance status, self-assessed health status, and inflammatory biomarkers (such as IL-6, TNFR-1, and GDF-15). Adverse IC trajectory patterns are associated with increased mortality, quality of life, disability, frailty, and fall risk. Future research should focus on changes in IC at the end of life, increase the number of assessment time points, use objective measurement methods, and consider experimental designs to better understand the mechanisms behind IC trajectories, providing a scientific basis for targeted interventions.

Lung cancer has one of the highest cancer mortality rates in the world and threatens people’s health. Timely and accurate diagnosis can greatly reduce the number of deaths. Therefore, an accurate diagnosis system is extremely important. The existing methods have achieved significant performances on lung cancer diagnosis, but they are insufficient in fine-grained representations. In this paper, we propose a novel attentive method to differentiate malignant and benign pulmonary nodules. Firstly, the residual attention network (RAN) and squeeze-and-excitation network (SEN) were utilized to extract spatial and contextual features. Secondly, a novel multi-scale attention network (MSAN) was proposed to capture multi-scale attention features automatically, and the MSAN integrated the advantages of the spatial attention mechanism and contextual attention mechanism, which are very important for capturing the salient features of nodules. Finally, the gradient boosting machine (GBM) algorithm was used to differentiate malignant and benign nodules. We conducted a series of experiments on the Lung Image Database Consortium image collection (LIDC-IDRI) database, achieving an accuracy of 91.9%, a sensitivity of 91.3%, a false positive rate of 8.0%, and an F1-score of 91.0%. The experimental results demonstrate that our proposed method outperforms the state-of-the-art methods with respect to accuracy, false positive rate, and F1-Score.

Venous thromboembolism (VTE) is major problem after hip fracture surgery with substantial morbidity and mortality. This study aimed to assess the postoperative compliance of thromboprophylaxis in elderly patients undergoing hip fracture surgery and to confirm the correlation between compliance and VTE risk. This retrospective cohort study included consecutive elderly hip fracture patients who undergoing surgery. According to the thromboprophylaxis regimens, patients were divided into non-compliant group (<14days), poor compliant group (14–27days) and good compliant group (≥28days). The primary outcome was the incidence of symptomatic DVT, PE within 6weeks postoperatively. Between 2008 and 2012, 1214 eligible patients were included in this study. 761 (64.7%) patients were non-compliant, 224 (19.0%) patients were poor compliant, and 192 (16.3%) patients were good compliant. The overall VTE rate was 7.9% (73/1177), PE rate was 0.3% (4/1177). The VTE rate in good compliant group was lowest among three groups (4.2 vs. 5.4 vs. 9.6%, P=0.013), but the PE rates showed no significant differences (0 vs. 0.9 vs. 0.3%, P=0.241). The multivariate analysis showed that non-compliance was an independent risk factor of suffering VTE undergoing hip fracture surgery. In this study we found fewer than 1 in 5 patients maintained compliant with thromboprophylaxis guidelines after discharge following hip surgery. This is particularly concerning because those who were non-compliant had a higher risk of VTE postoperatively compared with those who were good compliant.

Purpose: Resilience is considered as a protective factor that can assist individuals to reduce post-traumatic stress reactions. In recent years, armies in many countries have widely implemented resilience training programs before deployment to prevent or reduce post-deployment combat stress reactions. Therefore, this study aims to review what is known about resilience interventions for military personnel in pre deployment. Methods: Based on Arskey and O’Malley’s framework, a scoping review was completed. This review was performed through searching databases including PubMed, Embase, Web of Science, Medline and the Cochrane Library, and screening literature to extract data, finally summarizing the findings. Results: A total of 25 studies focusing on resilience interventions for military personnel in pre deployment were involved and analyzed using intervention approaches, outcome measures, intervention effects, and so on. Conclusion: Based on the existing evidence in this review, it is cautiously believed that the resilience intervention program for military personnel before deployment is effective. However, there is no single effective best method even the same type intervention can make different effects in different situations and populations. Therefore, the population differences and context should be fully considered in constructing and implementing program to build military personnel resilience.