ABSTRACT Background: Acute ischemic stroke is a major cause of cognitive dysfunction. Early identification of post‐stroke cognitive impairment (PSCI) is crucial for improving patient prognosis. While there has been extensive research on prognostic models for acute ischemic stroke, the selection of predictive factors remains heavily reliant on neuroimaging parameters. This study aims to create and compare the eXtreme gradient boosting (XGBoost) and logistic regression (LR) models based on serum biomarkers for predicting the risk of PSCI following acute ischemic stroke. Methods: The study enrolled 261 adult patients with acute ischemic stroke within 7 days of onset. Their baseline characteristics, serum markers, and scores anthe National Institutes of Health Stroke Scale (NIHSS) and the Montreal Cognitive Assessment (MoCA) were collected. Cognitive function assessment was completed 3 months (±2 weeks) after stroke, with PSCI diagnosis based on a MoCA score < 26. Patients were randomly assigned to the training dataset (n = 183) and testing dataset (n = 78) in a ratio of 7:3. Significant features for predicting the risk of PSCI were selected via LassoCV in R. The accuracy, F1 score, Cohen's kappa, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were measured to assess the accuracy of the XGBoost and LR prediction models. Finally, the performance of the optimal prediction model was evaluated by SHapley additive exPlanations (SHAP) beeswarm and force plots. Results: The incidence of PSCI and other baseline characteristics were comparable between the training and testing datasets (all P > 0.05). Vascular endothelial cadherin (VE‐Cad), NIHSS score, age, drink history, C‐reactive protein (CRP), and education years were features associated with the risk of PSCI. The XGBoost model was superior in accuracy, F1 score and sensitivity in predicting the risk of PSCI than the LR model. Beeswarm and force plots displayed the excellent ability of the XGBoost model in predicting the risk of PSCI in patients with acute ischemic stroke. Conclusion: Based on serum biomarkers, the XGBoost model can accurately predict the risk of PSCI in patients with acute ischemic stroke, with superior performance than the LR model, and may serve as a reliable tool for early identification to improve the diagnosis.From 261 acute ischemic stroke patients (training n = 183, testing n = 78), we collected demographic data, cognitive assessments, and serum indicators. LassoCV identified sensitive predictors including VE‐Cad, NIHSS score, CRP, age, drinking history, and education years. The XGBoost model demonstrated superior performance over LR in predicting PSCI risk. SHAP analysis revealed how these variables influenced model predictions. Based on serum biomarkers, the XGBoost model accurately predicts PSCI risk and may serve as a reliable tool for early identification to improve diagnosis.

Cognitive dysfunction (CD) is a frequent but often underrecognized clinical feature in systemic lupus erythematosus (SLE) patients. It markedly impairs their health-related quality of life. Investigating the risk associated with the onset of CD and establishing a prediction model are crucial for early detection of CD. This allows for timely intervention, potentially delaying or reversing the progression of CD. This study aimed to establish a predictive model for CD in SLE patients and evaluate its predictive efficacy. This study enrolled adult patients with SLE who underwent inpatient management at the Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University. Variables for analysis included demographic characteristics, physiological and psychological status, medication details, and laboratory examination. Key predictors were selected using the least absolute shrinkage and selection operator (LASSO) approach. A range of machine learning (ML) classification models were developed and evaluated to determine the best-performing model. The prediction accuracy of the best-performing model was evaluated using calibration curve analysis, and the clinical applicability of the model was further evaluated by decision curve analysis. Additionally, Shapley Additive exPlanations (SHAP) were applied to realize personalized risk assessment and enhance model interpretability. The study included 283 eligible patients, divided into a training set of 199 and a test set of 84. The eXtreme Gradient Boosting (XGBoost) model emerged as the optimal model. In the training set, the area under the curve (AUC) (95

OBJECTIVES:To assess the item-level psychometric properties of the Six-item Cognitive Impairment test (6-CIT) based on the item response theory (IRT) framework and explore the accuracy of the 6-CIT for mild cognitive impairment (MCI) screening among low-educated Chinese older adults. METHODS:This study included 232 older adults, with 130 low-educated individuals. IRT analysis evaluated item discrimination and threshold parameters of the 6-CIT items. Area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the 6-CIT in screening MCI, and the accuracy metrics including sensitivity, specificity, and clinical utility index (CUI) were calculated. RESULTS:The 6-CIT was transformed into two shortened instruments based on IRT results: the Five-item Cognitive Impairment Test (5-CIT) and the Four-item Cognitive Impairment Test (4-CIT). For the screening accuracy, the 5-CIT achieved balanced specificity (0.79) and sensitivity (0.65) in low-educated participants (AUC was 0.752.), outperforming the 6-CIT and 4-CIT. CUI values indicated strong ruling-out utility (CUI- = 0.719) of the 5-CIT. CONCLUSION:The 5-CIT excelled in ruling out non-MCI cases and could be regarded as supplementary assessment before the utility of complex screening instruments. This study supported the 5-CIT's usage in community settings among older adults with low educational attainment.

Background Intelligent eldercare has positive implications for maintaining social networks and improving the quality of life.The study aimed to examine spatio-temporal evolution characteristics of intelligent eldercare development in China, and provide recommendations for sustainable development. Methods Enterprise information was available from the TianYanCha website, and spatial analysis was employed to analyse the spatio-temporal evolution characteristics. We obtained policy documents from official websites and the PKULAW Database, and established a three-dimensional analytical framework to investigate structural characteristics of the policy system. Results A total of 4689 enterprises and 81 policy documents were included.The number of newly added enterprises per year showed an increasing trend. The kernel density analysis revealed that the distribution of enterprises has evolved from the core-area agglomeration structure to a multi-core distribution spreading to the surrounding areas. The distribution direction of enterprises was in the "Northeast-Southwest"direction. Hotspot areas and high-high cluster areas showed a trend of decreasing first and then increasing, and were concentrated in the central and eastern regions overall, indicating that there was a dense distribution of intelligent eldercare enterprises in these areas. Policy analysis indicated a disproportionate internal structure. The items with the largest proportion across each dimension are supply-side policy instruments (50.63%), product development and service supply (27.85%), and government departments (31.30%). Conclusions The development of intelligent eldercare enterprises showed an upward trend from 1982 to 2024, but the spatial distribution displayed regional imbalances. Intelligent eldercare enterprises were densely distributed in the central and eastern regions overall. Subsequent policies should balance the allocation of policy instruments and policy objectives, encourage the construction of cross-regional cooperation, and facilitate the sustained development of the industry.

Purpose: This retrospective study aimed to identify factors associated with postoperative cognitive dysfunction (POCD) in patients undergoing hepatectomy, with particular attention to liver disease-related characteristics and perioperative variables. A secondary aim was to develop a clinically applicable nomogram for individualized risk estimation in this population. Patients and Methods: A retrospective cohort study was conducted in 314 consecutive patients who underwent hepatectomy at Nanjing Drum Tower Hospital Affiliated to Nanjing University Medical School between January 2023 and December 2024. Patients were included if they had complete clinical data and underwent preoperative and postoperative cognitive assessment. Exclusion criteria included preoperative cognitive impairment (Montreal Cognitive Assessment [MoCA] score < 26), preexisting neurological or psychiatric disorders, and in-hospital death within 72 h after surgery. POCD was defined as a decline of ≥3 points in the MoCA score from baseline to postoperative day 5. Clinical, surgical, nutritional, and perioperative variables were analyzed, and a nomogram was constructed based on the final multivariable logistic regression model. Results: The overall incidence of POCD was 27.4% (86/314). The final multivariable model included sarcopenia, preoperative hemoglobin < 120 g/L, Child-Pugh classification, alcohol consumption, operative duration, and pain score on postoperative day 1. The nomogram incorporating these variables showed good discriminative ability, with an area under the curve of 0.87 (95% CI: 0.83-0.92). Conclusions: In this retrospective cohort of patients undergoing hepatectomy, several perioperative clinical factors were associated with POCD. The proposed nomogram may serve as a practical tool for perioperative risk estimation and support more individualized management in higher-risk patients.

Reproductive trauma refers to traumatic experiences related to adverse reproductive events, particularly preterm birth, infertility and fetal loss. These experiences negatively impact women’s physical health and often lead to long-lasting psychological burdens such as anxiety, depression, and stress. Expressive writing intervention (EWI) is a positive psychological tool characterized by its universality and portability. It has shown beneficial effects in populations with chronic illnesses. Recently, EWI has been applied to those experiencing reproductive trauma. However, the specific efficacy of EWI for patients with reproductive trauma on anxiety, depression and stress is not yet fully ascertained. The aim of this study was to assess the effectiveness of EWI as a psychological intervention for women with reproductive trauma. This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Six databases, including PubMed, EMBASE, Cochrane, Web of Science, CINAHL and PsycINFO, were searched from inception to June 8, 2026 for eligible studies. Two authors independently conducted literature screening, data extraction, and quality assessment according to the inclusion and exclusion criteria. Meta-analysis was performed using Review Manager software. Prespecified subgroup analyses examined the effects of intervention duration, control conditions, and population type. Exploratory meta-regression analyses were used to assess the association between intervention dose and outcomes. And publication bias and sensitivity analyses were conducted where appropriate. We also employed TSA to assess evidence conclusiveness, and certainty of evidence was rated via GRADE. Ten eligible studies with 838 participants were included in the final data set. Pooled analysis showed that EWI was not effective in reducing post-intervention anxiety and stress, whereas post-intervention depression showed a marginal effect (SMD = -0.35, 95

AIM:To provide a technical basis and evaluate usability and associated factors of Brain Health Promotion mHealth App. METHODS:Adults with Subjective Memory Complaints (SMC) and Mild Cognitive Impairment (MCI) participated in the study. Usability differences between them were assessed using a t-test, while regression analysis examined associated factors. Two-step clusters identified the multiple features of users matching the usability. RESULTS:The App's usability in adults with SMC and MCI were 43.45 ± 4.57 and 39.75 ± 3.06 (t = 4.356, p < 0.001). Usability was associated with objective cognition, e-Health literacy, and age, while education level emerged as the strongest predictor among four clusters of heterogeneous usability. CONCLUSION:Adults with SMC gave a high usability evaluation for the App and affirmed its value in brain health promotion. The intervention was feasible. However, multi-dimensional factors should be considered to realize efficient usability and multilevel optimization of the App.

BACKGROUND:Arousal threshold (ArTH) is associated with disease severity and sleep stability, but conventional PSG metrics cannot capture dynamic stage transitions. Hypnogram-based analysis provides information on the temporal structure of sleep. How variations in ArTH phenotype affect sleep architecture and transition dynamics remains unclear. METHODS:This retrospective study included 1792 patients with OSA stratified by arousal threshold. Hypnograms were converted into structured sleep-stage sequences using Python. After propensity score matching for age, gender, and BMI, group differences were evaluated using survival analysis for stage persistence, Poisson regression for transition frequency, and multistate Cox and semi-Markov models for transition dynamics. RESULTS:After propensity score matching, 580 OSA patients with a high arousal threshold and 580 with a low arousal threshold were analyzed. The High ArTH group showed longer N1 (80.6 ± 58.8 vs. 74.4 ± 54.5 min, p < 0.05), N2 (230.7 ± 76.3 vs. 216.8 ± 81.2 min, p < 0.01) and REM (68.9 ± 32.6 vs. 57.7 ± 35.9 min, p < 0.001), but lower N3 percentage (7.0 ± 7.4% vs. 8.2 ± 7.7%, p < 0.01). Transition analyses revealed unstable N2 with frequent NREM oscillations (N1→N2 RR = 1.076, p < 0.001; HR = 1.099, p < 0.001; N2→N1 RR = 1.219, p < 0.001; HR = 1.316, p < 0.001), reduced N3 progression (N2→N3 RR = 0.843, p < 0.01; HR = 0.837, p < 0.001), and lower NREM-to-wake probability (N1→Wake RR = 0.922, p < 0.05; HR = 0.911, p < 0.001; N2→Wake RR = 0.944, p < 0.05), indicating impaired sleep stability. CONCLUSIONS:High ArTH patients exhibit unstable N2 sleep, frequent NREM oscillations and reduced deep sleep progression, particularly in moderate and severe disease.

OBJECTIVES:This study aims to examine how inhibitory control affects working memory updating and investigate the neuromodulation effect of transcranial direct current stimulation (tDCS) on inhibitory control in individuals with mild cognitive impairment (MCI). METHODS:Experiment 1 included 15 MCI and 16 cognitively normal (CN) participants performing a Flanker-Nback task with low-conflict and high-conflict conditions (LCT/HCT). Experiment 2 employed a randomized, single-blind, sham-controlled tDCS study design (7 MCI/group). RESULTS:In Experiment 1, frontal P3 showed lower amplitude in the HCT than LCT, while CN individuals demonstrated smaller congruency effect of amplitude (CE-AM) in the HCT than LCT under the Flanker-2back condition. Frontal P2 exhibited prolonged latency in the HCT than LCT, while MCI group showed smaller CE of latency (CE-LA) in the HCT than LCT for the Flanker-1back condition. Parietal N2 demonstrated lower amplitude in the HCT than LCT, and both groups demonstrated smaller CE-AM in the HCT during the Flanker-2back condition. In Experiment 2, compared to sham tDCS group, active group showed higher post-stimulation P3 amplitude for the Flanker task, with reduced N2 amplitude in congruent trials and trends toward an increased P3 amplitude in incongruent trials after stimulation. CONCLUSIONS:Baseline cognition and task load modulated inhibitory control's impact on working memory updating, with MCI individuals demonstrating an "optimized inhibitory control - maintained or improved working memory updating" pattern. TDCS modulated the general attention control instead of inhibition based on the CE, which further corroborated this supportive function as evidence by the "synchronized non-optimization" of both inhibition and updating.

Autosomal dominant tubulointerstitial kidney disease -UMOD is characterized by progressive renal interstitial inflammation and fibrosis. However, its underlying mechanisms remain unclear. Here, we identify a large ADTKD pedigree harboring a novel UMOD p.H36Y mutation. Using CRISPR/Cas9 technology, we generated a UmodH36Y/+ mouse model that recapitulates the key phenotypes observed in affected individuals, including renal dysfunction, cyst formation, and interstitial inflammation. Multi-omics analyses in kidneys from male UmodH36Y/+ mice revealed marked macrophage pyroptosis. Mechanistically, the Umod p.H36Y variant activated the amyloid precursor protein (App)-Cd74 axis which mediated the crosstalk between renal mutant tubular cells and macrophages. This axis sustains NF-κB pathway activation in macrophages, initiating pyroptosis and pro-inflammatory cytokine release. The same mechanism is recapitulated in the UMOD p.Trp31Cys cell model. Notably, Pharmacologic inhibition using ARN2966, a small-molecule App inhibitor, attenuated renal injury in male UmodH36Y/+ mice. Collectively, these findings uncover a targetable pathway in ADTKD-UMOD.

Background/Objectives: This study aimed to explore the association between internet use and executive function among older adults and the mediating role of social participation and loneliness in internet use and executive function. Methods: A cross-sectional study was conducted among 439 community-dwelling older adults (≥60 years) in Nanjing, China, from September to December 2022. Participants were selected using simple random sampling and assessed with four standardized instruments: the Internet Use Questionnaire, the Social Participation Capacity Assessment, the six-item UCLA Loneliness Scale (ULS-6), and the Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A). Data were analyzed with the SPSS 21.0 software for descriptive statistics and correlation analysis and the AMOS 23.0 software for structural equation modeling to test the chain mediation effects. Model fit was evaluated using Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), and Weighted Root Mean Square (WRMR), with bootstrap resampling for indirect effect estimation. Results: The results showed that internet use was positively correlated with loneliness (r = 0.203, p < 0.01), social participation impairment (r = 0.193, p < 0.01), and executive function (r = 0.420, p < 0.01). Structural equation modeling showed that greater internet use was significantly associated with poorer executive function (β = 0.306, p < 0.01). These associations were partially explained by pathways involving social participation and loneliness through three indirect pathways: internet use via social participation (indirect effect = 0.087, 18.3% of the total effect); internet use via loneliness (indirect effect = 0.049, 10.3%); and internet use via social participation and then loneliness in sequence (indirect effect = 0.035, 7.1%). Conclusions: In community-dwelling older adults, more frequent internet use was associated with greater executive function impairment through mechanisms involving reduced social participation and increased loneliness. Therefore, there is a need to limit excessive internet use while promoting social participation and reducing isolation, which can have the greatest benefits for executive functioning in older adults.

The accelerated aging of the global population, projected to include 1.5 billion people over 60 by 2050, poses significant challenges to conventional eldercare systems. While aging in place is widely advocated for preserving independence, traditional home care models often struggle to meet complex needs. This gap is exacerbated by the diminishing capacity of informal support networks. Smart home technologies offer a viable pathway to augment care; however, their widespread adoption is impeded by a confluence of usability challenges, privacy concerns, and socioeconomic barriers. This scoping review aimed to examine how smart home technologies could meet the diverse needs of older adults aging in place, identify the key determinants influencing their adoption and sustained use. This scoping review was conducted in accordance with the Joanna Briggs Institute (JBI) methodology and reported following the PRISMA-ScR guidelines. To ensure comprehensive coverage, a systematic search was performed across eleven databases (PubMed, Web of Science, Embase, CINAHL, Cochrane Library, APA PsycInfo, CNKI, Wanfang, VIP, SinoMed, and OpenGrey) targeting literature published between January 2008 and December 2024. Studies were included if they investigated smart home technologies used by older adults (aged 60 and above) living at home and examined relevant needs and adoption determinants. Study selection and data extraction were guided by the Population–Concept–Context (PCC) framework. Thematic analysis was applied to synthesize findings and identify core themes, adoption determinants, and existing gaps in the evidence base. A total of 24 studies met the inclusion criteria, with most published after 2015 and primarily conducted in China, the United States, and European countries. The technologies examined ranged from basic sensor-based systems to integrated smart aging platforms. Older adults expressed three core priorities for technology use: health management, safety and emergency support, and support for independent living. Together, these accounted for more than 60 percent of the identified needs. Key facilitators of adoption included strong social support, better digital skills, and a clear perception of usefulness. In contrast, adoption was often limited by challenges such as complex user interfaces, affordability issues, privacy concerns, and cultural resistance. Notably, few studies addressed long-term usage patterns or sustainable implementation models, and the needs of socioeconomically vulnerable groups were insufficiently represented in the current evidence base. This review highlighted three primary demands among older adults: health management, safety and emergency support, and the ability to live independently. The adoption of smart aging technologies is influenced by supportive factors such as perceived usefulness and social support, as well as obstacles including usability difficulties, limited digital skills, and privacy concerns. Addressing existing evidence gaps call for a shift from technology-centered approaches to context-aware, user-driven systems grounded in older adults’ everyday experiences. Open Science Framework Registration: https://doi.org/10.17605/OSF.IO/E27KH

OBJECTIVES:To conceptualize the concept of dementia friendly communities. METHODS:Walker and Avant's method of concept analysis was used to identify the concept, antecedents, attributes and consequences of dementia friendly communities. RESULTS:Four dimensions of dementia friendly communities' attributes were identified around target population, social life involvement, socio-cultural environment, living space and physical environment. Antecedents of dementia friendly communities were reduced physical and mental health, increased stigma and social isolation of people with dementia and caregivers, required dementia-supportive physical environment and mismatch between supply and demand of care resources. Consequences of dementia friendly communities were increased personal empowerment, reduced financial burden, promotion of dementia inclusion and healthy aging. CONCLUSION:The result of the analysis provided a clearer definition of dementia friendly communities, which can be further tested and used to develop guide future research and interventions.

BACKGROUND:Given the paucity of appropriate patient-reported outcome measure (PROM) to assess the multidimensional rehabilitation status of people with schizophrenia in day rehabilitation centres (DRCs) in China, the present study aimed to develop a PROM specifically designed for people with schizophrenia in DRCs (SDRC-PROM) and evaluate its psychometric properties. METHODS:The development process of the SDRC-PROM was in accordance with the guideline established by the US Food and Drug Administration and the guideline outlined in the COnsensus-based Standards for the selection of health status Measurement INstruments (COSMIN) checklist. Participants with schizophrenia were recruited from six DRCs in Nanjing, China. The conceptual framework and item pool were determined through literature review, semistructured interview with 14 participants, and two rounds of Delphi method with 16 experts. The comprehensibility and feasibility of the measure were assessed through a pilot test with another 12 participants. Psychometric properties of the SDRC-PROM were evaluated in a formal survey containing 127 participants. The discrimination ability of items was estimated through the item analysis with the critical ratio, item-total correlation, corrected item-total correlation, Cronbach's α if item deleted, communality and factor loading. The construct validity was assessed through exploratory factor analysis (EFA). The internal consistency reliability, the test-retest reliability, measurement error and responsiveness were used to evaluate the reliability of the measure. RESULTS:The final SDRC-PROM comprised four domains with 40 items. Delphi consultations showed acceptable degree of concentration and coordination of experts' opinions. There were 10 ineligible items deleted during the item analysis. EFA supported a four-domain construct related to the psychological, physiological, social and therapeutic domain, and four domains explained 70.7% of the total variance. The Cronbach's α coefficient of the overall measure was 0.911, which of the four domains ranged from 0.814 to 0.907. The intraclass correlation coefficient (ICC) of the measure was 0.902, that of four domains varied from 0.853 to 0.913. The SDRC-PROM also indicated acceptable measurement error based on the illustration of standard error of measure (SEM), and smallest detectable change (SDC). Meanwhile, the responsiveness was also confirmed by the less SDC than the minimum important change (MIC). CONCLUSIONS:The SDRC-PROM is a reliable and valid measure with sufficient responsiveness to assess various aspects of rehabilitation status of people with schizophrenia from DRCs, which is conducive to optimising the evaluation system and ameliorating psychiatric rehabilitation care services for people with schizophrenia in DRCs in China.

OBJECTIVES:To explore negative affective prosody production patterns in older adults with mild cognitive impairment (MCI) and identify acoustic features as objective biomarkers for cognitive performances. METHODS:We recruited 42 older adults with MCI and 29 healthy controls (HC). The cognitive performances were assessed with the auditory verbal learning test-HuaShan version, the Trail Making Test A, the Digit Span-Forward, and the Digit Span-Backward. Acoustic features were extracted with the PRAAT software. RESULTS:There were significant differences between older adults with MCI and HC on anger sentences (t=-2.14, p=0.036, Cohen's d=0.52) and disgust sentences (Z=1.97, p=0.049, |r|=0.23). Duration in fearful sentences (β=-0.511, p=0.002) and degree of voice breaks in angry sentences (β=0.423, p=0.009) were identified as objective biomarkers for predicting verbal memory. CONCLUSIONS:Older adults with MCI have deficits in the production pattern of angry and disgusted prosody. Clinicians could assess verbal memory decline by temporal features in negative emotional prosody.

Chinese patent medicines, produced using advanced pharmaceutical techniques and available in various forms, including powders, granules, tablets, pills, and capsules, finds extensive utilization among Western medicine practitioners in primary healthcare (WMP-PHC). However, the inappropriate overprescribing of these medicines has led to significant resource waste and raised considerable concerns. Therefore, we aim to address related knowledge gaps by employing unannounced standardized patients (USPs) as a method, for both measurement and intervention research. Specifically, in this paper, we present a study protocol that aims to develop and evaluate the effectiveness of brief verbal interventions (BVI) delivered by USPs, with the objective of improving the appropriate prescription of Chinese patent medicines. The study aims to equip patients with simple and easily implementable interventions to enhance the appropriate prescription of Chinese patent medicines. Furthermore, The findings from this study will provide valuable insights for policymakers, enabling them to comprehend the current levels of inappropriate Chinese patent medicines prescription and develop targeted policy interventions. We will record a total of 576 encounters in primary healthcare (PHC) facilities across two cities in China. The data will be randomized using a 2 × 2 × 2 × 2 factorial design randomized controlled trial (RCT), which includes factors such as financial incentives, knowledge and skills, prescribing habits, and patient expectation. USPs will collect data, including retrieving prescriptions and documenting the process of medical encounters. The primary outcome evaluation focuses on the appropriateness of Chinese patent medicines prescriptions. Secondary outcomes include the quality of the consultation process, patient satisfaction, cost information, service time, and appropriateness of antibiotic prescriptions. Descriptive analysis will be performed for the survey results, and the difference in outcomes between interventions and control providers will be compared and statistically tested using generalized linear mixed model (GLMM). The study has been registered at the China Clinical Trials Registry (ChiCTR2300077913) on 23 November 2023. • To the best of our knowledge, this study is the first to offer evidence of interventions aimed at addressing inappropriate prescription of Chinese patent medicines in primary healthcare institutions in China. • Brief verbal intervention as a method of communication-based intervention during medical consultations, focus on prescription adjustments from the patient’s perspective, rather than relying on policies that are difficult to change. This approach empowers healthcare consumers in a context of information asymmetry, effectively encouraging doctors to modify their prescribing behaviors. Although this study specifically examines the effect of brief verbal interventions from the patient’s perspective on the prescription of Chinese patent medicines by primary care Western physicians, this approach can be expanded. The prescription of Chinese patent medicines serves as a particular context, but the broader concept of brief verbal intervention can be applied to influence Western practitioners’ medical decision-making and improve the quality of care they provide. • The utilization of USPs, which is a method where individuals are trained to depict patients in a standardized manner within medical scenarios, is becoming more prevalent in low-income countries for evaluating the quality of medical care. Research focusing on Chinese patent medicines reveals several advantages to employing this approach. Firstly, USPs can exhibit consistent symptoms, medical history, and emotions, while adhering to predefined standards for consultation, diagnosis, and treatment. This ensures a more objective evaluation of Chinese patent medicines appropriateness. Secondly, USPs are well-suited for introducing BVI, because of the researcher’s ability to vary verbal presentation (scripted lines) by the USP, allowing for measuring the effectiveness of the varied intervention while keeping other patient-side confounding factors constant. Lastly, USPs serve as a form of unannounced visits, minimizing the Hawthorne effect and providing researchers with direct and reliable information on appropriate Chinese patent medicines prescriptions. • The factorial design RCT enables the evaluation of multiple intervention components simultaneously, including the individual effects (main effects) and combined effects (interaction effects) of multiple BVIs. This design ensures robust research evidence and effective control over research costs. • This study also has limitations. Although we designed different scripted lines for USPs as proxy variables to reflect potential mechanisms such as financial incentives, knowledge and skills, prescribing habits and patient expectation, it should be noted that these scripted lines may not fully capture the mechanisms. Despite our efforts to minimize bias through the inclusion of expert groups and stakeholders in the development of lines, it is important to acknowledge this limitation.

This study is to develop and validate a robust risk prediction model for mild cognitive impairment (MCI) in patients with malignant haematological diseases after haematopoietic stem cell transplantation (HSCT). In this study, we analysed the clinical data of the included patients. Logistic regression analysis was used to identify independent risk factors for cognitive impairment after HSCT in patients with malignant haematological diseases, and a risk prediction model was constructed. Multiple cohorts of patients with haematological malignancies after HSCT (282 cases) from the Affiliated Hospital of Xuzhou Medical University and the First People’s Hospital of Yancheng City between April 2019 and February 2022, and patients from the Affiliated Huaian No.1 People’s Hospital of Nanjing Medical University between March 2022 and July 2023 were used for external validation. Logistic regression analysis was performed to develop the predictive model. The predictive value and consistency of the model were evaluated using the area under the curve (AUC) and calibration method, respectively. Decision curve analysis (DCA) was performed to access the utility of the model. Approximately half (52.26

AimsIn light of the escalating global incidence of Parkinson’s disease and the dearth of therapeutic interventions that can alter the disease’s course, there exists an urgent necessity to comprehensively elucidate and quantify the disease’s global burden.MethodsThis study analyzed the incidence, prevalence, and disability-adjusted life years (DALYs) of Parkinson’s disease at global, regional, and national levels based on the Global Burden of Disease Study 2021. Bayesian age-period cohort (BAPC) analysis was used to predict the burden in Parkinson’s disease from 2022 to 2035.ResultsIn 2021, 11.77 million people worldwide had Parkinson’s disease. Age-standardized rates of incidence, prevalence, and DALYs increased to 15.63/100,000, 138.63/100,000, and 89.59/100,000. The burden of Parkinson’s disease were higher in males than in females, and showed an increase and then a slight decrease with age. The disease burden was highest in East Asia. BAPC projection showed an increase in all metrics by 2035 except for a slight decrease in the age-standardized DALYs rates.ConclusionThe global burden of Parkinson’s disease has risen over the past 32 years, and there is a need to focus on key populations, as well as to improve health policies to prevent and treat Parkinson’s disease.

Background Stroke is a leading cause of disability among older adults worldwide, often resulting in significant physical, cognitive and emotional impairments that require long-term care. With ageing populations and increasing stroke prevalence, the demand for appropriate and sustainable long-term care is growing. However, designing care models that align with the complex needs and preferences of elderly patients who had a stroke remains a challenge. This study employs a discrete choice experiment (DCE) to measure and quantify patients’ preferences for long-term care. The primary objectives of this study are as follows: (1) identify and examine the key attributes and levels of long-term care that are most valued by this patient population, (2) assess patients’ preferences for long-term care and explore the role of each attribute on overall preference and (3) explore heterogeneity in preferences based on participants’ characteristics through subgroup analyses.Methods The research was conducted in accordance with the design programme of the DCE study. Seven attributes were developed through a systematic literature review, in-depth interviews and experts consultation. A partial factorial survey design was generated through an orthogonal experimental design to optimise the choice scenario sets. We plan to conduct a DCE questionnaire survey in Suzhou, Jiangsu Province, China, and recruit at least 500 participants. The final data will be analysed through a mixed logit model and a latent class model to explore the preference of elderly patients who had a stroke with disabilities for long-term care.Ethics and dissemination This study was approved by the Ethics Committee of Nanjing Medical University-Affiliated Suzhou Hospital (K-2024-096 K01). All participants will be required to provide informed consent. The findings of this study will be disseminated and shared with interested patient groups and the general public through a variety of channels, including online blogs, policy briefs, national and international conferences, and peer-reviewed journals.