This paper systematically reviewed the content,characteristics and application status of social integration assessment tools for patients with schizophrenia,so as to provide a basis for the development of social integration assessment tools for schizophrenia patients in China,and to provide some references for clinical practice and related intervention research.

OBJECTIVE:To develop and evaluate machine learning-based models for predicting fall risk within 6 months of stroke onset. METHODS:This prospective study enrolled acute stroke patients from three tertiary hospitals in Gansu Province, China. The study was conducted from December 2022 to October 2024. Participants were followed for 6 months. Two machine learning algorithms, decision tree (DT) and logistic regression (LR), were developed. Baseline data were collected within 72 h of admission. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), Brier score, accuracy, sensitivity, specificity, precision, F1-score. RESULTS:Of the 388 patients in the final analytic cohort, 286 (73.7%) were male and 102 (26.3%) were female, with a mean age of 64.27 ± 11.30 years. The incidence of falls within 6 months after stroke was 28.1% (109/388). The LR model achieved an AUC of 0.859, accuracy of 79.3%, sensitivity of 0.547, specificity of 0.890, precision of 0.663, F1-score of 0.599, and Brier score of 0.133. The DT model achieved an AUC of 0.863, accuracy of 81.4%, sensitivity of 0.618, specificity of 0.892, precision of 0.692, F1-score of 0.652, and Brier score of 0.132. The LR model was visualized as a nomogram. CONCLUSIONS:The LR and DT models showed comparable predictive performance for identifying patients at risk of falls within 6 months after stroke onset. These interpretable models may support early risk stratification. However, external validation is required to confirm their generalizability.

Background:Fear of progression (FoP) is a prevalent psychological issue among stroke patients. Previous studies failing to distinguish characteristics of patient groups with varying FoP levels. Latent profile analysis (LPA) classifies individuals into distinct subgroups via continuous FoP indicators, boosting classification accuracy by accounting for variable uncertainty. Given FoP's heterogeneity, investigating FoP profiles and their influencing factors in stroke patients is clinically significant for personalized psychological care and improved patient quality of life. Methods:A total of 366 stroke patients were selected as study subjects through convenience sampling, and a cross-sectional survey was conducted. FoP was assessed using the Fear of Progression Questionnaire-Short Form (FoP-Q-SF, 2 dimensions, 12 items). Independent variables included demographic characteristics, clinical indicators, the Recurrence Risk Perception Scale for Stroke patients (RRPSS), and the Medical Coping Modes Questionnaire (MCMQ). LPA was performed on the FoP-Q-SF items to identify subgroups. The R3STEP method was used to analyze influencing factors of subgroup membership, and the BCH method was applied to compare differences in distal outcomes across subgroups. Statistical significance was set at p < 0.05. Results:The study sample had a mean age of 63.93 ± 10.58 years, with 70.5% males and 65.0% first-ever stroke patients. Two latent profiles were identified: Low-FoP Adaptive Type (C1, 48.6%) and High-FoP Sustained Type (C2, 51.4%). The R3STEP showed that age 18-59 years (OR = 0.476, 95%CI = 0.245-0.924, p = 0.028), hypertension comorbidity (OR = 0.402, 95%CI = 0.237-0.683, p = 0.001), higher RRPSS score (OR = 0.971, 95%CI = 0.946-0.995, p = 0.022), MCMQ-confrontation (OR = 0.920, 95%CI = 0.863-0.982, p = 0.011), and MCMQ-avoidance (OR = 0.796, 95%CI = 0.723-0.876, p < 0.001) were significant influencing factors (all p < 0.05). BCH analysis indicated that C2 patients had higher RRPSS score (p < 0.001), higher NIHSS score (p = 0.002) and lower adaptive coping ability than C1. Conclusion:This study revealed significant heterogeneity in FoP among stroke patients. Age, hypertension comorbidity, excessive recurrence risk perception, MCMQ-confrontation, and MCMQ-avoidance were associated with high FoP. Healthcare providers should prioritize identifying high-risk individuals and develop tailored interventions to reduce FoP and improve rehabilitation outcomes.

ObjectiveTo analyze and clarify the conceptual connotation of death anxiety in cancer patients,and to provide reference for medical staff to identify and intervene the death anxiety in cancer patients.MethodsA systematic search was conducted on databases including CNKI,WanFang database,VIP,SinoMed,PubMed,Web of Science,Scopus,EMbase,psycINFO,and CINAHL.Literatures were selected based on inclusion and exclusion criteria,and the concept of death anxiety was analyzed by using Walker and Avant conceptual analysis.ResultsA total of 35 articles were included to summarize the concept of death anxiety.Its conceptual attributes were determined to include self⁃esteem,psychological depression,disease complexity,and social coping styles.Pre⁃factors included demographic factors,disease factors,psychological factors,and social support.The consequences included the impact on the patient's psychological,physiological,and social aspects.ConclusionsThe connotation of death anxiety is complex and influenced by multiple factors,which could seriously affect the quality of life of cancer patients.Clinical medical staff should improve the recognition rate of death anxiety in cancer patients,make proactive nursing interventions,and reduce the adverse effects of death anxiety on patients.

Objective:To explore the longitudinal temporal relationship between family resilience and self-management behaviors in stroke patients. Methods:A longitudinal observational study was conducted with three time points. Family resilience and self-management were assessed at hospitalization (T0), 3 months (T1), and 6 months (T2) post-discharge in 206 stroke patients using validated Chinese scales. A cross-lagged panel model was applied. Results:Self-management initially increased then declined; family resilience initially increased then stabilized. Self-management at T0 positively predicted family resilience at T1 (β = 0.203, p < 0.001). Family resilience at T1 positively predicted self-management at T2 (β = 0.269, p < 0.001). Conclusion:A time-ordered interactive relationship exists. In early rehabilitation, fostering self-management promotes family resilience; in later stages, enhancing family resilience helps maintain self-management.

Climate change has evolved from an environmental issue into a global public health crisis, posing severe challenges to healthcare systems. Issues such as shifts in patient disease patterns, increased care demands for vulnerable populations, and insufficient resilience in nursing systems are becoming increasingly prominent. As the frontline of healthcare delivery, nursing practice directly confronts multiple health risks triggered by climate change. Under the Healthy China 2030 strategy, the role of nursing in addressing climate change cannot be overlooked. Therefore, this paper systematically reviewed the impacts of climate change on nursing practice and corresponding domestic and international strategies, and proposed recommendations for localized development pathways. First, strengthen climate health literacy in nursing education by integrating the climate change system into curricula and clinical practice. Second, promote nursing policy participation in global health governance to establish a climate-adaptive nursing policy system with Chinese characteristics. Finally, establish a multidisciplinary nursing research framework to foster integration among nursing science, climate science, public health, traditional Chinese medicine, and other relevant fields. This paper aims to provide theoretical foundations for constructing a climate-adaptive nursing system with Chinese characteristics, thereby advancing the coordinated development of Healthy China initiative and climate governance.

Brain metastasis significantly worsens prognosis in late-stage cancer., with Its treatment hindered by the blood-brain barrier (BBB) and an immunosuppressive tumor microenvironment. Within this environment, tumor-associated macrophages (TAMs) represent the predominant immune population. Through their roles in immune modulation, angiogenesis, and tumor invasion, TAMs are critical drivers of disease progression. TAMs are highly heterogeneous. While traditionally categorized into M1 (anti-tumor) or M2 (pro-tumor) phenotypes, this dichotomy is an oversimplification. Recent single-cell studies have revealed a spectrum of functional subpopulations, such as lipid-associated, interferon-responsive, and pro-angiogenic TAMs, with M2-like states typically prevailing to mediate immunosuppression. This review explores the diversity and functions of TAMs in brain metastasis. We first detail their biological characteristics, including origins, heterogeneous subtype classifications (e.g., lipid-associated macrophages that extend beyond the simple M1/M2 dichotomy), and polarization states. We further discuss how polarization is regulated by signaling pathways (e.g., STAT, NF-κB) and microenvironmental factors (e.g., hypoxia, metabolic reprogramming). We examine TAM roles from pre-metastatic niche formation to tumor colonization, using breast and lung cancer brain metastases to illustrate how TAMs disrupt the BBB and facilitate immune evasion through molecules like ANGPTL4 (angiopoietin-like 4) and MMP9. Key pathways of TAM-tumor cell interactions, including neuro-cancer interactions, immune-metabolic regulation, and exosome-mediated communication, are also discussed. Targeting TAMs offers promising therapeutic avenues. These strategies include reprogramming TAMs (e.g., using CSF1R inhibitors), combining TAM-targeted therapy with immune checkpoint inhibitors, and developing novel approaches such as nanotechnology and CAR-macrophages. However, several challenges remain, including TAM heterogeneity, lack of targeting specificity, and the obstacle of BBB delivery. Future research should leverage technologies like single-cell sequencing and spatial transcriptomics to decode TAM heterogeneity, and develop personalized treatments based on biomarkers such as GPNMB and TRAIL, aiming to improve patient outcomes in brain metastasis.

ObjectiveThis study seeks to develop and compare four machine learning models using the MIMIC-IV database to identify predictive variables associated with invasive mechanical ventilation (MV) requirement in patients with embolic cerebral infarction.MethodsThis study included 568 patients with embolic cerebral infarction from the MIMIC-IV database. Data collected encompassed demographic information, vital signs, laboratory results, and other relevant variables. The dataset was randomly split into a development set and a validation set in a 7:3 ratio. Feature selection was performed using univariable and multivariable analyses. Four prediction models, namely decision tree (DT), logistic regression (LR), eXtreme Gradient Boosting (XGB), and Light Gradient Boosting Machine (LGBM), were developed. Model performance was assessed using receiver operating characteristic (ROC) curve analysis. Calibration was evaluated through calibration curves and Brier scores. Clinical utility was examined using decision curve analysis (DCA), and Shapley additive explanations (SHAP) were used to interpret model predictions. ICU admission was t0 and predictors were summarized over the first 24 h. Because exact MV-initiation times were unavailable, robustness analyses addressed optimism, class imbalance, and temporal ambiguity using repeated nested cross-validation, an all-MV benchmark, inverse-frequency weighting, and exclusion of pneumonia and log input amount.ResultsAmong 568 patients, 438 received invasive MV. XGB achieved an AUROC of 0.839 (95% CI, 0.796–0.883) in the development set and 0.720 (95% CI, 0.637–0.801) in the validation set; repeated nested cross-validation yielded 0.713 (95% CI, 0.665–0.757). The all-MV benchmark had a specificity of 0 and 0.500 balanced accuracy, whereas XGB achieved 0.700 and 0.659, respectively. Excluding pneumonia and log input amount reduced the nested-CV AUROC to 0.654 (95% CI, 0.595–0.703). SHAP analysis identified pneumonia, hematocrit, INR, weight, heart failure, log input amount, and glucose as the highest-importance features.ConclusionThis study developed four machine learning models to assess the necessity of mechanical ventilation support in patients with embolic cerebral infarction and compared their performance. XGB showed the most favorable overall validation profile but requires time-stamped external validation before clinical use.

Cardiac rehabilitation (CR) reduces mortality and morbidity in coronary heart disease (CHD). Globally, CHD is the most common reason for referral to exercise-based cardiac rehabilitation (ExCR). However, diabetes mellitus (DM) is a major risk factor for CHD. We aimed to assess ExCR’s efficacy in patients with both DM and CHD. A systematic literature search was conducted from inception to December 13, 2025, in the following electronic databases: PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Database, and Chinese Biomedical Database (CBM). This review was registered with PROSPERO (Registration No: CRD42024592143). Data synthesis was performed using Stata SE and RevMan 5.3. Pooled estimates were calculated using both fixed-effect and random-effects models; the random-effects model was adopted as the primary analysis when substantial heterogeneity was present (I² ≥ 50

[This corrects the article DOI: 10.3389/fimmu.2026.1756299.].

BACKGROUND:Stroke sleep disorders have negative effects on physiological function, readmission rate and mortality. However, the effects on cognitive function were inconsistent. This study aims to identify the impact of sleep disorders on cognitive functions in stroke, and the relationship between types of sleep disorders and cognitive disorders. METHODS:This systematic review and meta-analysis searched PubMed, the Cochrane Library, Web of Science, Embase, Chinese Biomedical Database (CBM), CNKI, Wanfang and VIP Database from inception until October 13, 2024. Using Revman 5.3 software to combine the odds ratios (ORs) and standardized mean differences (SMDs) reported in the study separately. Quality assessment, heterogeneity, and sensitivity analyses were also involved. RESULTS:There were 6 longitudinal studies and 10 cross-sectional studies involving 5,779 patients. Longitudinal studies showed that stroke patients with sleep disorders were more likely to have cognitive impairment [OR = 2.35, 95% CI (1.67, 3.31), I2 = 0%, p > .1]. Cross-sectional studies showed the same results [OR = 2.45, 95% CI (1.77, 3.40), I2 = 65%, p < .1], and the results did not change much [OR = 2.62, 95% CI (2.15, 3.20), I2 = 0%, p > .1] after the deletion of the literature that caused high heterogeneity. Age has a significant effect on cognition in stroke patients with sleep disorders (p < .1). Egger's test showed no significant publication bias (p > .1). CONCLUSIONS:Sleep disorders are associated factors affecting cognitive impairment in stroke patients, and the older the age, the greater the negative effect.

Background/Objectives:Evidence on postoperative nutritional dynamics in Chinese gastric cancer (GC) patients is currently limited. This study employs Group-Based Trajectory Modeling (GBTM) to identify Prognostic Nutritional Index (PNI) trajectory patterns and their factors among GC patients under early oral feeding (EOF) management. Methods:This retrospective study analyzed 124 GC patients undergoing total gastrectomy (2019-2024). PNI trajectories were identified using GBTM, and their associated factors were analyzed via multinomial logistic regression. Results:Three distinct trajectories emerged: "High nutritional status" (41.9%), "Rapidly declining" (7.3%), and "Decline-Recovery" (50.8%). Compared with the high nutritional status (49.99 ± 4.50), the baseline PNI of the decline-recovery group was lower (44.34 ± 3.57). High Morse Fall Scale (MFS) score (β = 0.092, p = 0.010), low activities of daily living (ADL) (β = -0.655, p = 0.009), AJCC Cancer Stage (β = 2.238, p = 0.002) and vascular and nerve invasion (β = 3.540, p < 0.001) influence unfavorable trajectories. Conclusion:Postoperative nutritional trajectories in GC patients managed with EOF are different. Functional impairment (e.g., low ADL, high MFS) and advanced pathological conditions were key determinants of unfavorable nutritional trajectories highlighting the need for targeted monitoring and individualized nutritional interventions for high-risk sub-groups.

ObjectiveThis study explored latent profiles of Health Information-Seeking Behavior (HISB) among stroke patients and analyzed its influencing factors.MethodsIn this cross-sectional study, 311 stroke participants from two tertiary care hospitals in Gansu Province, China, were recruited between January and May 2025 using convenience sampling. Data were collected using a general information questionnaire, the Health Information-Seeking Behavior Scale, and the Health Behavior Decision-Making Assessment Scale for Stroke Patients. Latent profile analysis (LPA) was employed to identify distinct HISB profiles.ResultsThree latent profiles were identified: the high-demand low-barrier positive group, the moderate-balanced group, and the low-demand high-barrier negative group. Key predictors of profile membership included age, education level, monthly personal income, and the presence of comorbid chronic diseases.ConclusionThe identification of three distinct HISB trait types provides an evidence-based foundation for developing personalized health education and tailored decision support interventions. Healthcare professionals can leverage this classification system to customize communication strategies for patients with different traits, deliver tiered information support, and ultimately empower patients to achieve better health behaviors and health outcomes.

Background and Objectives: Total hip arthroplasty in China expanded rapidly post-2019. The length of hospital stay in these procedures reflects healthcare quality standards. This study analyzed the correlation between preoperative clinical factors and the length of hospital stay in total hip arthroplasty patients managed via an enhanced recovery after surgery protocol. Methods: Preoperative clinical variables were collected from total hip arthroplasty patients in an accelerated rehabilitation program. One-way ANOVA and other statistical methods analyzed correlations between these data and hospitalization time. Results: A total of 408 patients were included, with a mean length of stay of 12.01 +/- 4.281 days. Right lower extremity strength (t = 2.794, p = 0.005), activities of daily living score (t = -3.481, p = 0.001), C-reactive protein (t = -2.514, p = 0.016), thrombin time (t = -2.393, p = 0.019), and prothrombin activity (t = 2.582, p = 0.013) can directly affect the length of stay in patients with total hip arthroplasty. Also, age (F = 1.958, p = 0.006) and erythrocyte sedimentation rate (t = -2.519, p = 0.015) were found to affect the length of hospital stay indirectly. Conclusions: This study demonstrated that right lower extremity strength, activities of daily living score, C-reactive protein, thrombin time, and prothrombin activity significantly influence the length of hospital stay in enhanced recovery after surgery-managed total hip arthroplasty patients. Therefore, early interventions should be made to address the above factors.

Background:Increasing evidence suggests that checklist plays an important role in chronic disease. This study aims to use bibliometric methods to explore the evolving global research trends, hotspots, and emerging frontiers of the application of checklist in chronic disease research, providing deeper insights into the current research landscape and guiding future chronic disease management development efforts. Methods:Bibliometrics analysis was performed utilizing RStudio and VOSviewer software. This atlas analyzed the global research trends, hotspots and emerging trends. Results:In total, there were 408 publications authored by 2398 authors from 784 institutions and 53 countries, published in 274 journals. The USA led in publication numbers, international cooperation and societal impact. The leading core journal was Archives of Pathology & Laboratory Medicine. The first highly cited document was published in Psychological Assessment by Bovin MJ et al. Chronic disease management, and the validity of treatment and recovery were the hotspots and potential trends. Conclusion:This study provides a comprehensive bibliometric analysis of the application of checklist in chronic disease research, uncovering global research trends and current hotspots while offering valuable insights and references for future research directions.

Diabetic wounds are therapeutically challenging because of the complex and adverse microenvironment that impedes healing. Unlike conventional wound dressings, hydrogels provide antibacterial, anti-inflammatory, and repair-promoting functions. In this study, we developed a light-responsive and injectable chitosan methacryloyl (CSMA) hydrogel, incorporating soy isoflavones (SIs) and gold nanoparticles (AuNPs). Transmission electron microscopy (TEM), Fourier transform infrared (FTIR) spectroscopy, and proton nuclear magnetic resonance (1H NMR) spectroscopy analyses confirmed the successful synthesis of the CSMA/SI/AuNP hydrogels. In vitro experiments demonstrated that this hydrogel exhibited exceptional biocompatibility and enhanced the migration of human umbilical vein endothelial cells (p < 0.05), thereby underscoring its potential for promoting angiogenesis. In vivo studies have indicated that hydrogels significantly enhance the rate of wound healing (p < 0.001). Moreover, they facilitate angiogenesis (p < 0.01) and diminish the inflammatory response at the wound site (p < 0.05). Additionally, hydrogels promote collagen deposition and the regeneration of skin appendages. These findings substantiate the hydrogel’s therapeutic potential for diabetic wound care, highlighting its promise for regenerative medicine. CSMA/SI/AuNP represents a significant advancement in diabetic wound treatment, addressing key challenges in wound healing by offering a multifaceted therapeutic approach with broad clinical implications for enhancing patient outcomes in chronic wound management.

Background:Atrial fibrillation (AF), the most prevalent cardiac arrhythmia, can significantly increase stroke risk, heart failure, and reduce quality of life. Despite growing evidence on the benefits of exercise for AF patients, data heterogeneity and the lack of comparative studies on different exercise modalities limit the accuracy of clinical recommendations. Objective:To compare the effects of different exercise regimens on AF and determine the most effective type of exercise for the treatment of AF. Methods:We systematically searched PubMed/Medline, Embase, the Cochrane Library, and Web of Science for randomized controlled trials of exercise interventions in patients with AF aged 18 years and older. The Cochrane Collaboration Risk of Bias tool (RoB 2) was utilized to assess the risk of bias. We used R software to perform a network meta-analysis. The protocol has been registered with PROSPERO (Number CRD42024628296). Results:A total of 1,477 participants from 16 randomized controlled trials were included in this network meta-analysis. The results indicated that mind-body exercise (MB) was the most effective in improving general health [mean difference (MD) = 12.26, 95% credible intervals (95% Crl): 6.47 to 18.04, surface under the cumulative ranking curve (SUCRA) = 76.31%] and 6-min walk test (MD = 104.80, 95% Crl: 44.25 to 165.10, SUCRA = 99.60%). Additionally, aerobic exercise (AE) was the most effective in increasing vitality (MD = 7.73, 95% Crl: 6.40 to 9.07, SUCRA = 88.07%). Conclusion:This network meta-analysis found that MB had superior effects on general health and exercise capacity. AE significantly improved vitality, social functioning, and mental health, with particular benefits in improving vitality. Systematic review registration:https://www.crd.york.ac.uk/prospero, identifier (CRD42024628296).

Previous clinical practice suggests that prolonged fasting could negatively impact their hemodynamic stability and lead to children’s dissatisfaction with the perioperative experience. Fasting guidelines for children are frequently updated. This study aims to explore the status of pre-operative fasting time in children and observe the practice of guidelines in clinical practice. A comprehensive search was conducted until 27 March 2024 in English. We used Stata14.0 for meta-analysis. We used the JBI cross-sectional study quality assessment tool to evaluate the quality. We applied a random effects model to conduct a separate meta-regression analysis on the age and the sample size. Our meta-analysis included 10 studies, with 1694 and 3527 children respectively included in solid and liquid fasting time. The effect magnitude of pre-operative solids fasting time was 12.694 [95

BACKGROUND:Posttraumatic epilepsy (PTE) is a major concern after traumatic brain injury (TBI). OBJECTIVE:This systematic review and meta-analysis estimated the global prevalence of PTE in TBI patients. METHODS:The study systematically searched relevant studies published from inception to September 20, 2024, using PubMed, Embase, Cochrane Library and Web of Science. The effects of publication bias were assessed using funnel plots and Egger tests. RESULTS:The review included 24 studies (n = 505,720) from 10 countries. We found that the pooled prevalence of PTE in TBI patients was 9 % (95 %CI, 8-11 %). Subgroup analyses were conducted, and the results showed that the prevalence of PTE was higher in studies that used the diagnostic criteria of the International League Against Epilepsy was 15 % (95 %CI, 11-20 %). Studies focused on severe PTE had a prevalence of 16 % (95 %CI, 8-25 %), while those focused on early post-traumatic seizures had a prevalence of 14 % (95 %CI, 8-20 %). The prevalence of PTE was also higher in studies that included men, with a prevalence of 10 % (95 %CI, 7-14 %). The prevalence of PTE was found to be highest in studies conducted in Europe (12 %, 95 %CI, 7-17 %) and North America (12 %, 95 %CI, 8-15 %). The leave-one-out analysis revealed that no individual study substantially affected the final prevalence estimates. CONCLUSION:This meta-analysis indicated that PTE is a common complication following TBI. Therefore, medical professionals should enhance their focus on the early screening of PTE in high-risk groups and provide information on its prevention in the future.