Health data science最新文献

Background: Cardiovascular diseases (CVDs) continue to be the leading cause of morbidity and mortality globally, indicating a major global health burden. Glycosylation, one of the key posttranslational modifications of proteins, plays an important role in the onset and progression of CVDs. This study employed bibliometric analysis to examine the research on glycosylation and CVDs, aiming to identify the evolution and hotspots in this field. Methods: A total of 1,441 publications published from 2010 January 1 to 2024 December 31 were extracted from the Web of Science Core Collection. The analysis included a visual and descriptive examination of publication trends, countries/regions, institutions, keywords, and references. Results: The United States is the most productive country/region in this field, followed closely by China. The University of Alabama at Birmingham has made the most important contribution to this area. Key research hotspots include "O-GlcNAcylation", "biomarkers", "angiogenesis", "α-dystroglycan", "potassium channel", "heart failure", "gene expression", "glycosylation", and "cardiac glycosides". Conclusion: Research on glycosylation in CVDs has shown a steady increase in recent years. Among these studies, O-GlcNAcylation plays a pivotal role in this field. This comprehensive bibliometric analysis of glycosylation and CVDs provides researchers with valuable, objective insights to support future investigations.

Background: Nonsuicidal self-injuries (NSSIs) are an important contributing factor to adolescent suicide, and various shared factors influence the risk of both NSSIs and suicide attempts (SAs). Both are important predictors of suicide and are part of a continuum of suicidal behaviors. Further exploration of the relationship between adolescent NSSI and SA may facilitate suicide prevention efforts. Methods: An online survey was conducted among 9,140 participants. Network analysis methods were used to explore expected influence (EI), bridge expected influence (BEI), edge weights, and differences between adolescents that have and have not attempted suicide (NSSI-SA and NSSI-NoSA, respectively). Results: Of the 9,140 participants, 7,030 completed the questionnaire, yielding a participation rate of 76.91%. Participants with at least one NSSI were retained, with 2,496 (35.50%) included in the network analysis. The strongest EI node for both networks was "emotion regulation strategies" (E = 1.389 and 1.393), and that for BEI was "personal distress" (Interpersonal Reactivity Index-personal distress; E = 0.497 and 0.492). Network comparisons revealed significant differences in NSSI 4 ("intentionally hitting walls, tables, and other hard objects"; E _(Δ) = -0.384, P < 0.001), significant differences in BEI with regard to "perspective taking" (Interpersonal Reactivity Index-perspective taking; E _(Δ) = -0.215, P < 0.001), and significant differences in edge weights between NSSI 4 and NSSI 5 ("intentionally hurting oneself by hitting with a fist, palm, or hard object"; E _(Δr) = -0.173, P < 0.001). Conclusions: Our study suggests that interventions in the form of emotion regulation strategies can alleviate symptoms throughout the entire network. Attention should be paid to instances when NSSI 4 and NSSI 5 behaviors co-occur frequently.

Background: Accurate mortality prediction for liver transplant candidates with hepatocellular carcinoma (HCC) remains a critical challenge. Traditional scoring systems, including Child-Pugh, Albumin-Bilirubin, Model for End-Stage Liver Disease (MELD), MELD-Na, MELD 3.0, and Alpha-fetoprotein scores, are widely used but often fail to provide precise risk assessments. This limitation arises from the dual burden of liver dysfunction and tumor progression, which complicates prognosis. Consequently, there is a need for a comprehensive approach addressing both considerations to better manage HCC patients. Methods: We propose an advanced machine learning-based scoring system exploiting Ensemble Learning and SHapley Additive exPlanations (SHAP) for a better understanding of key mortality risk factors. SHAP offers valuable insights into the decision-making process by providing both global and local explanations. By embedding SHAP values in the Uniform Manifold Approximation and Projection space, we perform supervised clustering to infer latent subgroups, providing a higher granularity on the contribution of key variables for mortality risk assessment. Results: Our system based on LightGBM outperforms conventional scores leveraging only 8 relevant variables selected by SHAP analysis. These variables respond to the challenging dual risk problem set in this work. With supervised clustering, we uncover 7 subgroups showing an increasing mortality risk level and a fine assessment of risk factors' contribution. Conclusion: By contrast to existing studies, our approach offers an integrative data-driven framework for handling the dual risk challenge set by HCC patients with liver dysfunction. Also, it provides a valuable tool for a more precise risk evaluation that may guide treatment decisions and help monitoring patient progression.

Background: China has the largest population with Alzheimer's disease and related dementias (ADRDs) globally, and rapid population aging is expected to drive a substantial increase in cases. This study projects ADRD prevalence and associated economic burdens across provinces in China from 2025 to 2060. Methods: Using data from the China Health and Retirement Longitudinal Study (CHARLS) supplemented by national demographic and provincial statistics, we projected the prevalence and care costs of ADRD for each of the 31 provinces in China from 2025 to 2060. Cost projections included formal care expenses and informal caregiving valued through replacement cost methods. We conducted uncertainty analysis to provide robust estimates for ADRD prevalence and costs. Results: By 2060, ADRD cases in China are projected to reach approximately 49.89 million, with the highest prevalence and economic burden concentrated in provinces such as Shandong, Sichuan, Jiangsu, Henan, and Guangdong. Formal care costs alone are expected to exceed $1 trillion annually, while the total economic value-including informal caregiving-could surpass $5 trillion. Geographic disparities highlight that Eastern and Central regions, with a higher proportions of older adults, will bear disproportionate costs. Informal caregiving is projected to constitute 60% to 80% of total ADRD-related costs. Conclusion: China faces an unprecedented rise in ADRD-related economic burden over the next 4 decades, with substantial regional disparities. Strengthening long-term care infrastructure, expanding financial and social support for caregivers, and implementing regionally tailored healthy aging policies are essential to ensuring equitable and sustainable ADRD care across China.