Objective To analyze survival outcomes and influencing factors among patients with colorectal cancer in Yunnan Province. Methods Clinical data were retrospectively collected from 4 892 patients with colorectal cancer. Survival data were obtained through follow-up. Overall survival (OS) was calculated by using the Kaplan-Meier method. Univariate analysis was performed by applying the log-rank test. Meanwhile, multivariate analysis employed the Cox proportional hazards regression model. Results The 1-, 3-, 5-, and 10-year OS rates for the entire cohort were 91.90%, 74.40%, 64.40%, and 28.70%, respectively. Univariate analysis revealed that age, ethnicity, region, differentiation grade, TNM stage, clinical stage, metastatic status, histological type, and treatment modality (chemotherapy, radiotherapy, and surgery) were associated with patient prognosis (all P<0.05). Multivariate analysis identified age (HR=1.250), region (HR=1.262), differentiation grade (HR=0.761), clinical stage (HR=3.128), and treatment modality (chemotherapy, HR=0.644; radiotherapy, HR=1.605; surgery, HR=0.384) as independent factors affecting survival prognosis in patients with colorectal cancer (all P<0.001). Conclusion Age, region, clinical stage, and treatment modality are independent factors influencing survival among patients with colorectal cancer in Yunnan Province. In clinical practice, these factors should be integrated to develop individualized prevention and treatment strategies, thereby improving patient outcomes.

Objective To quantitatively evaluate the structure and content of the long-term care insurance(LTCI)policy in China's deeply aging areas.Methods Using the Policy Modeling Consistency(PMC)index model indicator design method,a LTCI policy evalua-tion index system was constructed,consisting of nine primary indicators and 34 secondary indicators.A total of 123 provincial-level LTCI policies issued in deeply aging regions of China between June 1,2014,and October 1,2024 were analyzed.High-frequency word extraction was performed using ROSTCM 6.0,and a social network diagram of LTCI policies was created.The policy structure and content were quantitatively evaluated and ana-lyzed based on the established policy evaluation index system.Results The main content of LTCI policies in deeply aging areas of China covered services,institutions and assessment.The highest policy score was 7.28,and the lowest was 2.20,with an average score of 5.00.There were 25 perfect policies,63 excellent policies,28 good policies and seven qualified policies.In the dimension of policy content,the indexes of five primary indicators of policy evaluation,policy target groups,policy nature,policy perspective and policy tools were 0.60 or more;while the indexes of four primary indicators of policy content,incentives and constraints,policy timeliness,and policy level were 0.50 or less.Conclusion LTCI policies issued in China's deeply aging areas provide comprehensive coverage in aspects such as poli-cy evaluation,policy target groups and policy nature,and need to be improved in policy tool selection and the construction of incentive and constraint mechanisms.

Anhedonia is one of the core features of major depressive disorder (MDD) and is associated with poor functional outcomes in MDD patients. Psychosocial functional recovery is an important goal for achieving MDD remission. Although longitudinal studies have found association between anhedonia and impaired psychosocial function, there is still a lack of neurobiological biomarkers that can indicate this relationship. In this review, brain structural and functional changes associated with anhedonia and impaired psychosocial function in MDD patients are reviewed from the perspective of magnetic resonance imaging. It finds that anhedonia and psychosocial dysfunction in MDD may share common neuroimaging changes, manifested in abnormal brain regions such as the nucleus accumbens, caudate nucleus, putamen nucleus, orbitofrontal cortex, insula, amygdala, anterior cingulate cortex, dorsolateral prefrontal cortex, superior parietal lobe, inferior frontal gyrus and temporal lobe. These findings help to better understand the pathophysiology of the disease and offer potential insights for developing new treatment strategies.

In the field of healthcare service,it is crucial to optimize medical innovation services by combining the preferences of health service providers and demanders(i.e.,stakeholders).The best-worst scaling(BWS)method is a recently developed stated preference method for assessing preferences with distinctive advantages.Nevertheless,there is a lack of a comprehensive introduction to stakeholder preference assessment using BWS,thus constraining its applications and promotion.This paper introduces the process of using BWS to assess service providers'preferences for the Shared Medical Appointment for diabetes(SMART),an integrated healthcare service of medicine and health management,in the hope of providing reference for researchers for promoting the use of BWS in implementation research.

An overview of the application of association rule mining(ARM)in real-world study(RWD)on drug safety to inform pharmacovigilance real-world data analysis.The applications of ARM in RWD of drug safety were divided into single drug/vaccine signal detection,combined medication risk mining,multidimensional risk factor analysis and adverse drug event occurrence characterization based on passive monitoring data;medication characterization pattern analysis,auxiliary epidemiological study design and risk mining of the whole dataset based on active monitoring data.In general,foreign scholars pay more attention to method rule setting,performance evaluation and application research,while domestic scholars pay more attention to multidimensional risk factor analysis,adverse drug event occurrence pattern,and clinical drug use characteristics research.With the accumulation of medical data and the continuous development of data mining technology,ARM may provide new ideas for RWD on drug safety.

Objective::To examine the impact of hypertensive disorders of pregnancy (HDP) on offspring metabolomics.Methods::We searched five databases: PubMed, Ovid Embase, MEDLINE, Web of Science, and China National Knowledge Infrastructure, and included studies that reported metabolomics among human offspring born to HDP-complicated pregnancies.Results::Database search yielded 4054 articles, and after full-text screening, ten observational studies met inclusion criteria. Half of the studies had a sample size of less than 100 and were all observational studies in preeclampsia (PE) and gestational hypertension.Neonates were the most focused group in all included studies. Offspring born to HDP-complicated pregnancies exhibited statistically significant variations in blood metabolomics compared to their counterparts, characterized by amino acids, lipids, carnitine, and others (e.g., 1α,25-(OH) 2-D). Most studies reported a significant increase in differential metabolites of offspring born to HDP-complicated pregnancies. Four studies ( n = 1109) measured lipids-related metabolites, and all consistently showed that offspring born to PE-complicated pregnancies had significantly higher concentrations than non-PE exposed offspring. Conclusion::The existing evidence suggests an intergenerational effect of HDP on offspring metabolomics. Long-term follow-up studies are needed to advance the health effects of related adverse health outcomes and inform the prevention of offspring’s health.

Anhedonia is one of the core features of major depressive disorder (MDD) and is associated with poor functional outcomes in MDD patients. Psychosocial functional recovery is an important goal for achieving MDD remission. Although longitudinal studies have found association between anhedonia and impaired psychosocial function, there is still a lack of neurobiological biomarkers that can indicate this relationship. In this review, brain structural and functional changes associated with anhedonia and impaired psychosocial function in MDD patients are reviewed from the perspective of magnetic resonance imaging. It finds that anhedonia and psychosocial dysfunction in MDD may share common neuroimaging changes, manifested in abnormal brain regions such as the nucleus accumbens, caudate nucleus, putamen nucleus, orbitofrontal cortex, insula, amygdala, anterior cingulate cortex, dorsolateral prefrontal cortex, superior parietal lobe, inferior frontal gyrus and temporal lobe. These findings help to better understand the pathophysiology of the disease and offer potential insights for developing new treatment strategies.

Objective::To examine the impact of hypertensive disorders of pregnancy (HDP) on offspring metabolomics.Methods::We searched five databases: PubMed, Ovid Embase, MEDLINE, Web of Science, and China National Knowledge Infrastructure, and included studies that reported metabolomics among human offspring born to HDP-complicated pregnancies.Results::Database search yielded 4054 articles, and after full-text screening, ten observational studies met inclusion criteria. Half of the studies had a sample size of less than 100 and were all observational studies in preeclampsia (PE) and gestational hypertension.Neonates were the most focused group in all included studies. Offspring born to HDP-complicated pregnancies exhibited statistically significant variations in blood metabolomics compared to their counterparts, characterized by amino acids, lipids, carnitine, and others (e.g., 1α,25-(OH) 2-D). Most studies reported a significant increase in differential metabolites of offspring born to HDP-complicated pregnancies. Four studies ( n = 1109) measured lipids-related metabolites, and all consistently showed that offspring born to PE-complicated pregnancies had significantly higher concentrations than non-PE exposed offspring. Conclusion::The existing evidence suggests an intergenerational effect of HDP on offspring metabolomics. Long-term follow-up studies are needed to advance the health effects of related adverse health outcomes and inform the prevention of offspring’s health.

Objective To quantitatively evaluate the structure and content of the long-term care insurance(LTCI)policy in China's deeply aging areas.Methods Using the Policy Modeling Consistency(PMC)index model indicator design method,a LTCI policy evalua-tion index system was constructed,consisting of nine primary indicators and 34 secondary indicators.A total of 123 provincial-level LTCI policies issued in deeply aging regions of China between June 1,2014,and October 1,2024 were analyzed.High-frequency word extraction was performed using ROSTCM 6.0,and a social network diagram of LTCI policies was created.The policy structure and content were quantitatively evaluated and ana-lyzed based on the established policy evaluation index system.Results The main content of LTCI policies in deeply aging areas of China covered services,institutions and assessment.The highest policy score was 7.28,and the lowest was 2.20,with an average score of 5.00.There were 25 perfect policies,63 excellent policies,28 good policies and seven qualified policies.In the dimension of policy content,the indexes of five primary indicators of policy evaluation,policy target groups,policy nature,policy perspective and policy tools were 0.60 or more;while the indexes of four primary indicators of policy content,incentives and constraints,policy timeliness,and policy level were 0.50 or less.Conclusion LTCI policies issued in China's deeply aging areas provide comprehensive coverage in aspects such as poli-cy evaluation,policy target groups and policy nature,and need to be improved in policy tool selection and the construction of incentive and constraint mechanisms.

A high level of self-compassion can effectively relieve stress, reduce the psychological distress, and improve mental health. This paper reviews the conception, measurement tools, influencing factors, and intervention measures of self-compassion among caregivers for elderly dementia patients. It analyzes the deficiencies in current research and puts forward feasible suggestions, aiming to provide a reference for future related research.