Longitudinal relationship between social participation, depressive symptoms, and activity impairment among older patients with arthritis: a moderated mediation analysis.

BACKGROUND: Arthritis primarily affects older people and is a prominent cause of their activity impairment. This study aimed to examine the mediating role of depressive symptoms in the relationship between social participation and activity impairment, as well as to determine whether sex moderated the mediating effect. METHODS: A total of 2247 older patients with arthritis were included from the China Health and Retirement Longitudinal Study between 2015 and 2018. We first examined a simple mediation model where depressive symptoms were a mediator between social participation and activity impairment. Furthermore, sex was systematically integrated into the model as a moderator. The mediation model and moderated mediation model were analyzed using PROCESS macro. RESULTS: Mediation analysis revealed that the association between social participation and activity impairment was partially mediated by depressive symptoms (B = -0.10, 95% CI = [-0.14, -0.06]) with intermediary effect of 28.6%. Moderated mediation analysis indicated that mediation model was moderated by sex. The indirect effect of social participation on activity impairment among female patients (B = -0.15, 95% CI = [-0.21, -0.09]) was stronger than male patients (B = -0.04, 95% CI = [-0.09, -0.01]). CONCLUSION: Social participation was the key protective factor associated with depressive symptoms and activity impairment among arthritis patients. Encouraging arthritis patients to social participation and improving the depressive symptoms might avoid activity impairment, especially for female patients.

The association between team cohesion and performance: A network analysis of nurses.

Team cohesion, as a necessary condition for the cooperation and development of a team, has been shown to have a strong association with team performance. However, the mechanism of this internal correlation is unclear and more in-depth studies are lacking. The study aimed to explore the complex links between the dimensions of team cohesion and performance in nurses. A total of 1639 practice nurses from 118 nursing teams were included in this cross-sectional study. Data were collected using the Team Cohesion Scale (including consistency of affection, behavior, and cognition) and the Team Effectiveness Scale (including cooperation satisfaction, and task performance). Using network analysis, the team cohesion and performance network was constructed, and the strength and bridge strength of nodes were calculated. The results showed that the edges between team cohesion and performance dimensions were all positively correlated. Cooperation satisfaction and consistency of affection are the core variables in the network. Interventions targeting cooperation satisfaction and consistency of affection need to be developed at the team level to maximize team cohesion and performance among nurses.

Network Analysis on Family Resilience, Fear of Progression, and Quality of Life in Chinese Patients with Pulmonary Hypertension.

BACKGROUND: The long-term quality of life of Chinese patients with pulmonary hypertension has been seriously compromised. Interventions to enhance patient quality of life of are urgently required. OBJECTIVE: To investigate the relationship between quality of life and its influencing factors in patients through network analysis. METHOD: 247 patients with pulmonary hypertension in 3 hospitals in Jinan, Shandong Province, self-reported their immediate family resilience, fear of progression, and quality of life via questionnaires. A mixed graphical model was constructed to investigate the relationship among multidimensional structures of variables. RESULTS: A total of 247 patients (173 female and 74 male) were included (age 18-34, n=115; age 35-49, n=99; age 50-64, n=23; age > 65 years, n=10). "Family communication and problem solving" was at the center of the network, with serving as a bridge node. Within communities, the strongest edge was "Family communication and problem solving-maintaining a positive outlook." Across communities, the strongest edge between family resilience and quality of life was "Family communication and problem solving-environmental domain quality of life," and the strongest edge across the fear of progression and quality of life was "physiological health fear-psychological domain quality of life." CONCLUSIONS: Family resilience and fear of progression may affect the quality of life in patients with pulmonary hypertension. Developing a program with "family communication and problem solving" as a primary target may reduce patient fear of progression, enhance family resilience, and improve patient quality of life.

The mediation effect of social support between stigma and social alienation in patients with stroke.

Background: Social alienation is prevalent and causes adverse outcomes in stroke. Previous studies have linked stigma with social alienation. However, little is known about the mechanisms behind this relationship. This study explored the mediation effects of social support between stigma and social alienation. Methods: A cross-sectional design was used to study 248 patients with stroke admitted to a tertiary rehabilitation hospital in Beijing, China, from December 2022 to July 2023. Patients were assessed using a general information questionnaire, the Stroke Stigma Scale, the Social Support Rating Scale, and the Generalized Social Alienation Scale. The PROCESS macro in SPSS was used to examine the mediation model. Results: The results showed that stigma has a negative effect on social support (ß = -0.503, p<0.001); stigma has a positive effect on social alienation (ß = 0.768, p<0.001). Social support mediated the relationship between stigma and social alienation, with a mediation effect of 0.131 (95%CI: 0.060, 0.214), and indirect effects accounted for 17.06% of the total effect. Conclusion: Social support mediated the relationship between stigma and social alienation. These findings suggest that intervention targeting the enhancement of social support may prevent or reduce social alienation among patients with stroke.

COMPARISONS BETWEEN DIGITAL-GUIDED AND NONDIGITAL PROTOCOL IN IMPLANT PLANNING, PLACEMENT, AND RESTORATIONS: A SYSTEMATIC REVIEW AND META-ANALYSIS OF RANDOMIZED CONTROLLED TRIALS.

OBJECTIVES: The present study aimed to systematically review the current randomized clinical trials (RCTs) with respect to computer-aided design/computer-aided manufactured (CAD/CAM) techniques in the process of implant planning, placement, and rehabilitation. MATERIALS AND METHODS: Four independent reviewers conducted an electronic and manual literature search using several databases, including the National Library of Medicine (MEDLINE-PubMed), Cochrane Central Register of Controlled Trials (CENTRAL), and EMBASE. Articles were included if they were RCTs involving the interventions regarding the computer-guided impression, placement, and manufacturing process. The outcomes of interest include clinical and patient-reported outcomes and time efficiency. A meta-analysis was conducted to evaluate the time efficiency, pain severity, accuracy of implant placement, and postsurgery marginal bone level. RESULTS: A total of 39 and 25 articles were included in the qualitative and quantitative analysis, respectively. The results of the meta-analysis showed that significantly less time was spent performing the digital impression procedure than the conventional impression (P = .002). In addition, the average adjustment time of the final prosthesis was significantly less than the nondigital fabricated prosthesis (P = .0005). Computer-guided groups reported significantly lower painkiller consumption compared to control groups (P = .03). CONCLUSIONS: Digital impressions and CAD/CAM procedures are time-saving and provide stable and predictable outcomes. Moreover, computer-guided surgery can effectuate an accurate implant placement and less postsurgery discomfort.

Pan-mediastinal neoplasm diagnosis via nationwide federated learning: a multicentre cohort study.

BACKGROUND: Mediastinal neoplasms are typical thoracic diseases with increasing incidence in the general global population and can lead to poor prognosis. In clinical practice, the mediastinum's complex anatomic structures and intertype confusion among different mediastinal neoplasm pathologies severely hinder accurate diagnosis. To solve these difficulties, we organised a multicentre national collaboration on the basis of privacy-secured federated learning and developed CAIMEN, an efficient chest CT-based artificial intelligence (AI) mediastinal neoplasm diagnosis system. METHODS: In this multicentre cohort study, 7825 mediastinal neoplasm cases and 796 normal controls were collected from 24 centres in China to develop CAIMEN. We further enhanced CAIMEN with several novel algorithms in a multiview, knowledge-transferred, multilevel decision-making pattern. CAIMEN was tested by internal (929 cases at 15 centres), external (1216 cases at five centres and a real-world cohort of 11 162 cases), and human-AI (60 positive cases from four centres and radiologists from 15 institutions) test sets to evaluate its detection, segmentation, and classification performance. FINDINGS: In the external test experiments, the area under the receiver operating characteristic curve for detecting mediastinal neoplasms of CAIMEN was 0·973 (95% CI 0·969-0·977). In the real-world cohort, CAIMEN detected 13 false-negative cases confirmed by radiologists. The dice score for segmenting mediastinal neoplasms of CAIMEN was 0·765 (0·738-0·792). The mediastinal neoplasm classification top-1 and top-3 accuracy of CAIMEN were 0·523 (0·497-0·554) and 0·799 (0·778-0·822), respectively. In the human-AI test experiments, CAIMEN outperformed clinicians with top-1 and top-3 accuracy of 0·500 (0·383-0·633) and 0·800 (0·700-0·900), respectively. Meanwhile, with assistance from the computer aided diagnosis software based on CAIMEN, the 46 clinicians improved their average top-1 accuracy by 19·1% (0·345-0·411) and top-3 accuracy by 13·0% (0·545-0·616). INTERPRETATION: For mediastinal neoplasms, CAIMEN can produce high diagnostic accuracy and assist the diagnosis of human experts, showing its potential for clinical practice. FUNDING: National Key R&D Program of China, National Natural Science Foundation of China, and Beijing Natural Science Foundation.

Relationship between quality of life, fear of disease progression, and coping styles in patients with pulmonary hypertension: A network analysis.

A poor quality of life (QoL) in patients with pulmonary hypertension (PH) is often associated with emotional disturbances and the ability to cope. Little is known, however, about the intrinsic links among the QoL, fear of disease progression (FoP), and coping styles in patients with PH. The purpose of this study was to elucidate the relationships among QoL, FoP, and coping styles in patients with PH. We conducted a cross-sectional survey of 247 patients from a tertiary hospital in Jinan, China and analyzed the relationships using network analysis. Participants completed the World Health Organization's Quality of Life Questionnaire, Fear of Disease Progression Questionnaire and Simple Coping Style Questionnaire during the survey period. The total QoL, positive coping, and negative coping scores were 46.55 ± 10.46, 31.75 ± 6.85, and 18.75 ± 4.66, respectively. The QoL psychological domain had the strongest centrality, deserving more attention than other domains. The coping styles were bridge nodes that connected the whole network, where negative coping and social family FoP, and positive coping and both social and psychological QoL had the strongest positive correlations. There were no significant sex-based or age-based differences in the networks. To improve QoL and psychological well-being in people with PH, healthcare professionals must focus on issues beyond the patient's physical health. Specifically, they should focus on positive coping styles, while developing interventions to promote positive coping and reduce negative coping styles.

The mediating effects of social support and depressive symptoms on activities of daily living and social frailty in older patients with chronic heart failure.

OBJECTIVES: To investigate the level of social frailty (SF) in older patients with chronic heart failure (CHF) and examine the mediating role of social support and depressive symptoms between activities of daily living and SF. METHODS: Using a convenience sampling method, 205 older patients with CHF were recruited from China between November 2021 and May 2022. Activities of daily living, social support, depressive symptoms, and SF were assessed using a self-administered questionnaire. Data were analyzed using structural equation modeling. RESULTS: The final model obtained a good fit. Activities of daily living in older patients with CHF were directly related to SF. The multiple mediation analysis revealed that the relationship between activities of daily living and SF was mediated by social support (effect: -0.010, 95% CI [-0.021, -0.003]) and depressive symptoms (effect: -0.011, 95% CI [-0.019, -0.005) separately, and serially (effect: -0.007, 95% CI [-0.012, -0.003). CONCLUSIONS: Social support and depressive symptoms are multiple mediating variables in the relationship between activities of daily living and SF. Activities of daily living can improve patients' SF through social support and depressive symptoms.

Effect of Exercise Rehabilitation in Patients With Acute Heart Failure: A Systematic Review and Meta-analysis.

BACKGROUND: Exercise rehabilitation is conducive to increasing functional ability and improving health outcomes, but its effectiveness in patients with acute heart failure (AHF) is still controversial. PURPOSE: In this study, our aim was to systematically examine the efficacy of exercise rehabilitation in people with AHF. METHODS: A search was conducted for randomized controlled trial studies on exercise rehabilitation in patients with AHF up to November 2021. Two investigators conducted literature selection, quality assessments, and data extractions independently. The primary outcome was 6-minute walk distance, and the secondary outcomes were left ventricular ejection fraction, quality of life, Short Physical Performance Battery, readmission, and mortality. RevMan (version 5.3) software was used for the meta-analysis. RESULTS: Twelve studies with 1215 participants were included. Exercise rehabilitation significantly improved the 6-minute walk distance (mean difference [MD], 33.04; 95% confidence interval [CI], 31.37-34.70; P < .001; I2 = 0%), quality of life (MD, -11.57; 95% CI, -19.25 to -3.89; P = .003; I2 = 98%), Short Physical Performance Battery (MD, 1.40; 95% CI, 1.36-1.44; P < .001; I2 = 0%), and rate of readmission for any cause (risk ratio, 0.48; 95% CI, 0.26-0.88; P = .02; I2 = 7%), compared with routine care. However, no statistically significant effects on left ventricular ejection fraction (MD, 0.94; 95% CI, -1.62 to 3.51; P = .47; I2 = 0%) and mortality (risk ratio, 1.07; 95% CI, 0.64-1.80; P = .79; I2 = 0%) were observed. CONCLUSIONS: Compared with routine care, exercise rehabilitation improved functional ability and quality of life, reducing readmission in patients with AHF.

Heterogeneous trajectories of kinesiophobia and their effects on rehabilitation outcomes after total knee arthroplasty: a prospective cohort study.

BACKGROUND: Kinesiophobia is one of the most common and aversive psychological phenomena among patients after total knee arthroplasty (TKA). This study aimed to identify trajectories of kinesiophobia, examine factors distinguishing these trajectories, and clarify the association between trajectories of kinesiophobia and rehabilitation outcomes. METHODS: In this prospective cohort study, the patients who underwent TKA were recruited between December 2021 and April 2022 from three orthopedic wards of a tertiary hospital in China. Kinesiophobia was measured using the Tampa Scale for Kinesiophobia at baseline (T0), and then at 1 month (T1) and 3 months (T2) after TKA to perform latent class growth analysis. Meanwhile, rehabilitation outcomes were assessed at 3 months after TKA, using the Kessler Psychological Distress Scale, the Hospital for Special Surgery-Knee Scale, Barthel Index, and the Impact on Participation and Autonomy questionnaire. RESULTS: The four kinesiophobia trajectories identified were as follows: low stable group (n = 120), rapid recovering group (n = 31), slow recovering group (n = 48), and stable moderate group (n = 58). Body mass index, employment status, heart disease, and pain degree significantly predicted trajectory groups (all p < 0.05). Analysis of variance revealed significant differences between the four kinesiophobia trajectories concerning all rehabilitation outcomes, except for the activities of daily living. CONCLUSION: Distinct kinesiophobia trajectories were identified, and nurses should assess the kinesiophobia of patients after TKA in the early phase. Patients in the slow recovering group are worthy of a specific focus because of their poor recovery after undergoing TKA. As important sources of psychosocial care, nurses need to customize psychological interventions for patients after TKA depending on each kinesiophobia trajectory.

Construction and Validation of Machine Learning Algorithms to Predict Chronic Post-Surgical Pain Among Patients Undergoing Total Knee Arthroplasty.

BACKGROUND: Chronic post-surgical pain (CPSP) is a common but undertreated condition with a high prevalence among patients undergoing total knee arthroplasty (TKA). An effective model for CPSP prediction has not been established yet. AIMS: To construct and validate machine learning models for the early prediction of CPSP among patients undergoing TKA. DESIGN: A prospective cohort study. PARTICIPANTS/SUBJECTS: A total of 320 patients in the modeling group and 150 patients in the validation group were recruited from two independent hospitals between December 2021 and July 2022. They were followed up for 6 months to determine the outcomes of CPSP through telephone interviews. METHODS: Four machine learning algorithms were developed through 10-fold cross-validation for five times. In the validation group, the discrimination and calibration of the machine learning algorithms were compared by the logistic regression model. The importance of the variables in the best model identified was ranked. RESULTS: The incidence of CPSP in the modeling group was 25.3%, and that in the validation group was 27.6%. Compared with other models, the random forest model achieved the best performance with the highest C-statistic of 0.897 and the lowest Brier score of 0.119 in the validation group. The top three important factors for predicting CPSP were knee joint function, fear of movement, and pain at rest in the baseline. CONCLUSIONS: The random forest model demonstrated good discrimination and calibration capacity for identifying patients undergoing TKA at high risk for CPSP. Clinical nurses would screen out high-risk patients for CPSP by using the risk factors identified in the random forest model, and efficiently distribute preventive strategy.

A novel nomogram for predicting risk of malnutrition in patients with heart failure.

Background and aims: This study aimed to explore the risk factors of malnutrition in patients with heart failure and construct a novel nomogram model. Methods and results: A cross-sectional study based on the STROBE checklist. Patients with heart failure from July 2020 to August 2021 were included. Patients were divided into a malnutrition group and a normal nutrition group based on the Society's recommended AND-ASPEN standard. Logistic regression was used to analyze the independent risk factors for malnutrition. A new prediction model of nomogram was constructed based on the risk factors, and its fit and prediction performance were evaluated. Of 433 patients, 66 (15.2%) had malnutrition and 367 (84.8%) had normal nutrition, Logistic regression analyses showed that the risk factors for malnutrition were total protein, hemoglobin, triglyceride, and glucose levels. The regression model based on the above four variables showed an area under the curve of 0.858. The novel nomogram model had a sensitivity of 78.5% and a specificity of 77.3%. After 2000 bootstrap resampling iterations, AUC was 0.852. Conclusions: The novel nomogram model can predict the odds of malnutrition in patients with heart failure at the early stage of admission, and can provide a reference for nursing staff to optimize nutritional care for inpatient with heart failure and to develop a discharge nutritional care plan.

Prevalence of cognitive frailty among older adults in China: a systematic review and meta-analysis.

OBJECTIVE: This study aimed to investigate the prevalence of cognitive frailty among older adults in China. DESIGN: Systematic review and meta-analysis. METHODS: We searched the Cochrane Library, PubMed, Web of Science, Embase, China National Knowledge Infrastructure(CNKI), Wanfang, Chinese Biomedical Literature and Weipu (VIP) databases to collect information on the epidemiology of cognitive frailty among older adults in China. The study period was from the establishment of the database to March 2022. Two researchers independently screened the literature, extracted the data and assessed the risk of bias in the included studies. All statistical analyses were performed using Stata V.15.0. RESULTS: We screened 522 records, of which 28 met the inclusion criteria. The results of the meta-analysis showed that the prevalence of cognitive frailty among older adults in China was 15%(95%CI (0.13%,0.17%)). The prevalence of cognitive frailty was higher in hospitals and nursing homes than in communities. Moreover, the prevalence of cognitive frailty was higher in women than in men. Furthermore, the prevalence rates of cognitive frailty in North China Hospital, older adults aged≥80 years, and illiterate individuals were 25%, 29%, and 55%, respectively. CONCLUSIONS: In conclusion, in China, the prevalence of cognitive frailty is higher among older adults, is higher in women than in men, is higher in hospitals and nursing homes than in communities, and is higher in North China than other regions. Moreover, the higher the educational level, the lower the prevalence of cognitive frailty. Multimodal interventions for cognitive frailty, including increased exercise, nutritional support, increased socialisation opportunities and multifactorial strategies, may be effective in preventing cognitive frailty. These findings have important implications for adjusting healthcare and social care systems. PROSPERO REGISTRATION NUMBER: CRD42023390486.

The association between team resilience and team performance in nurses during COVID-19 pandemic: a network analysis.

BACKGROUND: Compared to other healthcare workers, nurses are more vulnerable to the potentially devastating effects of pandemic-related stressors. Studies have not yet investigated the deeper characteristics of the relationship between team resilience and team performance among nurses during the COVID-19 pandemic. This study aimed to elucidate the characteristics of team resilience and performance networks among nurses during the pandemic. METHODS: A cross-sectional study involving 118 nursing teams comprising 1627 practice nurses from four tertiary-A and secondary-A hospitals in Shandong Province, China, was conducted. Analyzing and Developing Adaptability and Performance in Teams to Enhance Resilience Scale and the Team Effectiveness Scale were used to measure team resilience and performance, respectively. The estimation of the network model and calculation of related metrics, network stability and accuracy, and network comparison tests were performed using R 4.0.2. RESULTS: Node monitoring had the highest centralities in the team resilience and performance network model, followed by node anticipation, cooperation satisfaction, and cooperation with other departments. Moreover, node cooperation satisfaction and learning had the highest levels of bridge centrality in the entire network. CONCLUSION: Monitoring, anticipation, cooperation satisfaction, cooperation with other departments, and learning constituted core variables maintaining the team resilience-performance network structure of nurses during the pandemic. Clinical interventions targeting core variables may be effective in maintaining or promoting both team resilience and performance in this population.

Longitudinal Trajectories of Depressive Symptoms Among Patients With Knee Osteoarthritis: The Role of Pain Intensity.

BACKGROUND: Pain is the primary symptom of knee osteoarthritis (KOA), significantly associated with depressive symptoms. Whether the early pain intensity could distinguish different trajectories of depressive symptoms is not well understood among patients with KOA. AIMS: To identify heterogeneous depressive symptoms trajectories among patients with KOA, and investigate the association between depressive symptoms subgroups and pain intensity. DESIGN: Secondary analysis of a cohort sample. SETTING: Three waves of data from the China Health and Retirement Longitudinal Study was collected in 28 provinces across China. PARTICIPANTS: 702 patients with KOA aged ≥ 45 years completed the Center for Epidemiologic Studies Depression Scale biennially from 2011 to 2015. METHODS: Latent class growth analysis was performed to identify the optimal trajectory shape and number of classes. Multinomial logistic regression analysis was conducted to compare pain intensity across the trajectories. RESULTS: Four distinct trajectories were identified as follows: no depressive symptoms, highly stable, decreasing, and increasing. In multivariate analysis, compared with the "no depressive symptoms" class, patients in the "highly stable" class and "increasing" class were more likely to report moderate pain (p < 0.05) and severe pain (p < 0.05). In addition, there was no significant difference in pain intensity between "no depressive symptoms" class and "decreasing" class (p > 0.05). CONCLUSIONS: These results suggest important heterogeneity in depressive symptom trajectories among patients with KOA. Pain intensity could predict different depressive symptom trajectories in patients with KOA. Efforts to improve the depressive symptoms in patients with KOA must incorporate strategies to address pain.

Predictive mutation signature of immunotherapy benefits in NSCLC based on machine learning algorithms.

Background: Developing prediction tools for immunotherapy approaches is a clinically important and rapidly emerging field. The routinely used prediction biomarker is inaccurate and may not adequately utilize large amounts of medical data. Machine learning is a promising way to predict the benefit of immunotherapy from individual data by individuating the most important features from genomic data and clinical characteristics. Methods: Machine learning was applied to identify a list of candidate genes that may predict immunotherapy benefits using data from the published cohort of 853 patients with NSCLC. We used XGBoost to capture nonlinear relations among many mutation genes and ICI benefits. The value of the derived machine learning-based mutation signature (ML-signature) on immunotherapy efficacy was evaluated and compared with the tumor mutational burden (TMB) and other clinical characteristics. The predictive power of ML-signature was also evaluated in independent cohorts of patients with NSCLC treated with ICI. Results: We constructed the ML-signature based on 429 (training/validation = 8/2) patients who received immunotherapy and extracted 88 eligible predictive genes. Additionally, we conducted internal and external validation with the utility of the OAK+POPLAR dataset and independent cohorts, respectively. This ML-signature showed the enrichment in immune-related signaling pathways and compared to TMB, ML-signature was equipped with favorable predictive value and stratification. Conclusion: Previous studies proposed no predictive difference between original TMB and modified TMB, and original TMB contains some genes with no predictive value. To demonstrate that fewer genetic tests are sufficient to predict immunotherapy efficacy, we used machine learning to screen out gene panels, which are used to calculate TMB. Therefore, we obtained the 88-gene panel, which showed the favorable prediction performance and stratification effect compared to the original TMB.

Symptom burden, family resilience, and functional exercise adherence among postoperative breast cancer patients.

Objective: This study examines the relationships among family resilience, functional exercise adherence, and symptom burden in postoperative breast cancer patients. Methods: In this cross-sectional study, participants consisted of 192 women with breast cancer who had undergone breast cancer surgery in two hospitals in Shandong Province, China. Family resilience, functional exercise adherence, and symptom burden were measured using the 32-item shortened Chinese version of the Family Resilience Assessment Scale (FRAS-C), Postoperative Functional Exercise Compliance Scale for Breast Cancer Patients, and the Chinese version of the M. D. Anderson Symptom Inventory (MDASI-C), respectively. Structural equation modeling was conducted to examine the path relationships among family resilience, functional exercise adherence, and symptom burden. Results: Family resilience and its subscales were significantly negatively correlated with symptom burden (r â€‹= â€‹-0.17 to -0.14, P â€‹< â€‹0.05), whereas positively correlated with functional exercise adherence (r â€‹= â€‹0.64 to 0.69, P â€‹< â€‹0.01). Functional exercise adherence was significantly positively correlated with symptom burden (r â€‹= â€‹-0.32 to -0.35, P â€‹< â€‹0.01). Family resilience indirectly affected symptom burden through functional exercise adherence (ߠ​= â€‹-0.319, 95% CI: -0.491, -0.169). Conclusions: Family resilience, as a positive psychological factor, could indirectly impact postoperative breast cancer patients' physical function. Specifically, family resilience can alleviate the patients' symptom burden by strengthening their functional exercise adherence. In addition to improving functional exercise adherence, nurses can also improve family resilience when helping to alleviate the symptom burden of postoperative breast cancer patients. Family resilience-based interventions could be implemented to alleviate the symptom burden among such patients.

Prevalence and impact of malnutrition on readmission among hospitalized patients with heart failure in China.

AIMS: Malnutrition is common in patients with heart failure (HF) and is associated with poorer quality of life and increased mortality; however, an effective screening tool for malnutrition and its impact on the readmission of patients with HF is uncertain. Our objectives were to study (i) the nutritional status of Chinese hospitalized patients with HF and its impact on readmission and (ii) the validity of seven malnutrition screening tools. METHODS AND RESULTS: In this study, univariate and multivariate analyses of Cox proportional hazards regression were used to determine important predictors of readmission. The endpoint was readmission due to HF or non-HF. A total of 402 patients were included (66.4% male, median age 62 years [range: 20-92 years], median NT-proBNP 5,229 ng/L). During a median follow-up of 159 days, 150 patients (37%) were readmitted to the hospital. After adjusting for confounders, only malnutrition assessed using the Controlling Nutritional Status (CONUT) nutrition score was independently associated with readmission (P = 0.0293). A base model for predicting readmission with a C-statistic of 0.680 and subsequent addition of various nutritional screening tools improved its performance over the base model. Patients with malnutrition had a twofold increased risk of readmission. CONCLUSIONS: We found that the prevalence of malnutrition among hospitalized patients with HF in China is very high and that malnutrition significantly increases the risk of readmission in these patients. CONUT is a validated screening tool for malnutrition and may provide valuable prognostic information.

Validation of a Chinese version of the Analysing and Developing Adaptability and Performance in Teams to Enhance Resilience Scale in nurses in China.

AIM: This study examined the validity and reliability of the Analysing and Developing Adaptability and Performance in Teams to Enhance Resilience (ADAPTER) Scale in a sample of Chinese nurses. BACKGROUND: Nurse shortage caused by job stress in China is becoming more acute, while research on team resilience training among nurses is still rising. To accurately and consistently describe team resilience status prior to training and evaluate the effects of resilience interventions at the team level among nurses, it is critical to develop a valid and reliable Chinese measure. METHODS: This was a cross-sectional study of 838 nurses. The scale was translated into Chinese according to Brislin's guidelines. Validity was evaluated by content validity, discriminative validity, exploratory and confirmatory factor analyses and convergent validity. Reliability was estimated by item-to-total correlations, internal consistency and test-retest reliability. RESULTS: Exploratory and confirmatory factor analyses revealed a four-factor model. Content validity was good and discriminative validity showed a significant discriminative ability. The concurrent validity was acceptable. The reliability was demonstrated with item-to-total correlations of greater than .40, Cronbach's alpha of .97 and intraclass correlation coefficients of .946. CONCLUSIONS: The Chinese version of the scale is a valid and reliable instrument. IMPLICATIONS FOR NURSING MANAGEMENT: The scale can provide insight into nurses' team resilience and thereby inform the development of specific interventions aimed at improving the team resilience of nurses.

Depression and Opioid Misuse in Elderly Individuals With Chronic Pain: A Latent Class Analysis.

BACKGROUND: Chronic pain patients tend to have comorbid depressive symptoms, and empirical data investigating differences related to depressive symptoms classes and opioid misuse are scant. AIMS: The aim of this study was to identify heterogeneous depressive symptoms trajectories in elderly individuals with chronic pain who take opioids, and investigate the association between depressive symptoms subgroups and opioid misuse. DESIGN: Secondary data analysis of a cross-sectional study. SETTINGS: Twelve communities were selected from a city in Shandong Province, China, using multi-stage cluster sampling. PARTICIPANTS/SUBJECTS: Individuals aged ≥60 years with self-reported chronic pain lasting more than one year and who took opioids under prescription were screened. METHODS: Latent class analysis was used to identify homogeneous depressive symptoms groups within the elderly population with chronic pain. Multinomial logistic regression, and one-way analysis of variance were also performed. RESULTS: The best-fitted model suggested three depressive symptoms subgroups: "Impaired Memory," "Perceived Stress in Life and Work," and "Low Mood." Age, education level, and marital status were depression risk factors. The odds of opioid misuse varied among the depressive symptoms subgroups. CONCLUSIONS: These findings may help improve depressive symptoms and chronic pain management by identifying high-risk elderly individuals for early intervention and personalizing treatment according to the depressive symptoms subgroup and severity of opioid misuse.