Objective To explore the effectiveness of the generative large language model MedGo in nursing decision-making for elderly patients with multimorbidity. Methods A quasi-randomized controlled trial study was conducted involving 6 junior nurses, 6 senior nurses and the MedGo model from January 1, 2025 to March 31, 2025 at the Emergency Internal Medicine Ward of Shanghai East Hospital Affiliated to Tongji University. Clinical data of 120 elderly patients with multimorbidity were analyzed to compare the performance of the three groups in four tasks (nursing diagnosis assessment, nursing intervention formulation, complication identification, and complication prevention) from three evaluation dimensions: decision-making time consumption, decision accuracy, and decision-making quality. Results In terms of decision-making time, the senior nurse group completed all four tasks faster than the junior nurse group (P＜0.01), and the MedGo group completed all four tasks faster than the junior nurse group (P＜0.001) and the senior nurse group (P＜0.001). In terms of decision-making accuracy, senior nurse group scored higher than junior nurse group in all four tasks (P＜0.001), while the MedGo group outperformed the senior nurse group only in complication identification (P＜0.001). In terms of decision-making quality, the MedGo group scored higher than junior nurse group (P＜0.001) and senior nurse group (P＜0.001) in all four tasks. Conclusions The MedGo model demonstrates advantages of high efficiency, accuracy, and quality in nursing decision-making for elderly patients with multimorbidity; senior nurses outperform junior nurses in decision-making, providing diverse references for clinical nursing decision-making.

Objective To investigate the microstructural changes of white matter in patients with relapsing-remitting multiple sclerosis(RRMS)and its correlation with clinical functional scores.Methods A total of 20 patients with RRMS(RRMS group)and 20 healthy controls(HC)(HC group)were selected and underwent diffusion tensor imaging(DTI)and expanded disability status scale(EDSS)scores.Patients with RRMS were categorized into two groups based on their EDSS scores,including MS-1 group(motor dysfunction with visual impairment)and MS-2 group(motor dysfunction).Image processing was performed via tract-based spatial statistics(TBSS).Group comparisons were executed using the t-test,while correlations were analyzed utilizing Spearman correlation.Results In the RRMS group,reduced fractional anisotropy(FA)values were accompanied by increased mean diffusivity(MD)and radial diffusivity(RD)values in the forceps major,forceps minor,bilateral cingulum,bilateral uncinate fasciculus,bilateral superior longitudinal fasciculus,bilateral inferior longitudinal fasciculus,bilateral inferior fronto-occipital fasciculus,bilateral corticospinal tract and bilateral anterior thalamic radiation compared with the HC group.Additionally,In the RRMS group,increased axial diffusivity(AD)values were noted in the forceps major,forceps minor,bilateral superior longitudinal fasciculus(temporal),right inferior fronto-occipital fasciculus,bilateral corticospinal tract and right anterior thalamic radiation compared with the HC group.Compared with the MS-2 group,the MS-1 group exhibited higher FA values in the right cingulum(cingulate gyrus part)and higher AD values in the left cingulum(cingulate gyrus part).Correlation analysis revealed negative correlations between the FA values of the forceps major,right superior longitudinal fasciculus and the motor function scores in RRMS group.Conversely,positive correlations were identified between the MD values of the forceps minor,right superior longitudinal fasciculus,right inferior fronto-occipital fasciculus,left corticospinal tract and the RD values of the forceps minor,right cingulum(hip-pocampus),right superior longitudinal fasciculus,and left corticospinal tract,as well as the motor function scores.Conclusion RRMS patients exhibit microstructural damage in white matter and are associated with motor dysfunction,which provides imaging support for the pathological mechanisms underlying motor dysfunction in RRMS patients.

Multiple myeloma(MM),a common malignancy of plasma cells,remains an incurable disease de-spite significant therapeutic advancements.A defining characteristic of MM is the recurrent occurrence of cytogenetic ab-normalities,particularly the gains of chromosome 1q21(1q21+),which are among the most frequently observed anoma-lies in this condition,affecting approximately 40%of patients with newly diagnosed MM.While numerous studies have identified 1q21+as an independent prognostic marker linked to poor outcomes in MM,its prognostic significance continues to be debated.An increasing number of national and international prognostic stratification systems classify 1q21+as a high-risk factor;however,its predictive value remains contentious.Variations in 1q21 copy numbers significantly impact genomic instability,drug resistance,and the likelihood of early disease progression,highlighting its growing importance in clinical management strategies.Despite the availability of various therapeutic approaches,such as autologous hemato-poietic stem cell transplantation,immunomodulatory drugs,and proteasome inhibitors,the adverse prognostic implica-tions of 1q21+persist unresolved.This review will explore the latest advancements in understanding the 1q21+in MM,fo-cusing on its pathogenesis,prognostic relevance,and implications for clinical management.

This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.

Objective To analyze the latent classes of social alienation in colorectal cancer patients and further explore the influencing factors and cumulative effects of risk factors across different classes,thereby providing a reference for individualized interventions.Methods Convenience sampling was used to select colorectal cancer patients hospitalized in the gastrointestinal surgery and oncology departments of 3 tertiary-level hospitals in Shandong Province from January to June 2023 as the study subjects.A questionnaire survey was conducted using the General Information Questionnaire,Social Avoidance Scale,Social Anxiety Scale,UCLA Loneliness Scale,Sense of Coherence Scale,Family Cohesion Scale,and Social Support Rating Scale.Data analysis was performed using latent profile analysis and multivariate logistic regression analysis.Results A total of 292 questionnaires were distributed,with 270 valid responses collected,yielding a response rate of 92.47％.The results of the latent profile analysis indicated that social alienation among colorectal cancer patients could be categorized into 3 latent groups:the"low alienation group"(42.59％),the"high alienation-high social avoidance group"(14.08％),and the"moderate alienation-high social anxiety group"(43.33％).Results of logistic regression analysis revealed that employment status,stoma status,metastasis,sense of coherence,family cohesion,and social support were influencing factors across different categories.Moreover,a cumulative effect of sense of coherence,family cohesion,and social support on distinct categories was observed(P＜0.05).Conclusion Social alienation among colorectal cancer patients exhibits group heterogeneity.Healthcare professionals should identify the characteristic differences among patients,prioritise those with multiple risk factors,and develop targeted intervention measures to help them better integrate into society.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.

Objective:To describe the prevalence of preserved ratio impaired spirometry (PRISm) in participants from the China Kadoorie Biobank (CKB) and explore the influencing factors.Methods:The CKB project conducted the baseline survey, the first and the second resurvey in 2004-2008, 2008, and 2013-2014, respectively. Based on the lung function tests, the participants were categorized into three groups: regular, PRISm, and airflow obstruction. The prevalence of PRISm was reported by gender, age, and region at the baseline survey. The secular trend in the prevalence of PRISm was described during the three surveys. Finally, we used the multiple logistic regression model to examine the factors related to PRISm in the baseline survey.Results:After standardization for gender, age, and region according to the sixth national census data in 2010, the overall prevalence of PRISm and airflow obstruction among the 434 760 participants at baseline was 24.8% and 6.1%, respectively. The prevalence of PRISm was higher in rural (25.4%) than that in urban areas (24.3%). Of the 10 study regions, Gansu had the highest prevalence of PRISm (56.0%), while Henan had the lowest (15.4%). After standardization for gender, age, and region according to the baseline population, the prevalence of PRISm decreased from 24.9% at baseline to 15.7% in the second resurvey, and the prevalence of airflow obstruction increased from 5.9% to 21.4%. Unmarried status, current smoking, using solid fuels for cooking, low body weight, being overweight, obesity, and central obesity were associated with an increased risk of PRISm. In contrast, higher education attainments, increased household income, and maintaining a specific degree of physical activity were associated with a reduced risk of PRISm.Conclusions:The prevalence of PRISm was high in adults aged 40 years and above in China, and it varied by sociodemographic and lifestyle factors.

Objective:To explore the impacts of smoking on the need for respiratory support and mortality in patients hospitalized with pneumonia.Methods:A total of 24 367 patients hospitalized with pneumonia from 2009 to 2017 in the China Kadoorie Biobank, were included. Smoking status was self-reported, and data regarding respiratory support during hospitalization and mortality during follow-up were obtained from medical claims and death registries, respectively. OR, HR, and 95% CI were calculated and adjusted for potential confounders using logistic regression models and Cox proportional hazards regression models, respectively. Results:Among males, current smokers or those who quit smoking due to illness had higher risks of requiring respiratory support ( OR=1.15, 95% CI: 1.03-1.29), 1-year mortality ( HR=1.66, 95% CI: 1.32-2.08), and 5-year mortality ( HR=1.32, 95% CI: 1.13-1.54) following pneumonia hospitalization compared to nonsmokers. Male smokers who started smoking at a younger age or with longer smoking duration had the highest mortality risks (trend test both P<0.05). Female current smokers or those who quit smoking due to illness had higher risks of 1-year mortality ( HR=1.62, 95% CI: 1.17-2.23) and 5-year mortality ( HR=1.33, 95% CI: 1.06-1.67). We found no statistically significant difference in 90-day mortality between current smokers/those who quit smoking due to illness and nonsmokers. Conclusions:Smoking was associated with higher risks of requiring respiratory support and mortality in patients hospitalized with pneumonia, especially among males and heavy smokers. These findings highlight the need for targeted strategies to promote smoking cessation in patients hospitalized with pneumonia.

Objective:To identify individuals with accelerated aging under the frailty index (FI) as a proxy indicator of biological age, and to investigate the associations of age at menarche, age at menopause, and reproductive lifespan with frailty status and multi-timepoint FI trajectories among Chinese adult women.Methods:The current study included 302 471 women from the China Kadoorie Biobank 2004-2008 baseline survey data. Their age at menarche and menopause were self-reported, and the duration of reproductive lifespan was calculated by subtracting the two ages. The baseline FI was constructed using 28 baseline variables, including diseases, symptoms, and anthropometric measurements. Frailty status was categorized into three groups: non-frail (FI≤0.10), pre-frail (0.10