A national study exploring the association between triglyceride-glucose index and risk of hyperuricemia events in adults with hypertension.

Background: The triglyceride-glucose (TyG) index has been recommended as a practical surrogate of insulin resistance (IR). However, the association between the TyG index and hyperuricemia among adults with hypertension remains to be elucidated. Methods: We included and analyzed 3134 HTN patients and 4233 non-HTN participants from the cross-sectional 2013-2018 U.S. National Health and Nutrition Examination Surveys (NHANES). Multivariable logistic regression and restricted cubic splines (RCS) were used to explore the association between the TyG index and hyperuricemia. Stratifed analyses were performed to assess the association in populations with different subgroups of hypertension. Results: The prevalence of hyperuricemia was higher in HTN patients (28.00 %) than in non-HTN participants (12.47 %). The multivariable logistic regression showed that the TyG index was significantly associated with hyperuricemia. After multivariable adjustment, higher TyG index levels were found to be associated with a higher prevalence of hyperuricemia in HTN patients (OR: 2.39, 95 % CI: 1.37-4.17, Ptrend < 0.001) and non-HTN participants (OR: 2.61, 95 % CI: 1.45-4.69, Ptrend < 0.001). Restricted cubic spline regression showed linearity of the associations between the TyG index and hyperuricemia (p-nonlinear > 0.05). In the subgroup analysis suggested that the positive association seemed to be strong among male, alcohol use, and diabetes group (P for interaction < 0.05). Conclusions: TyG index, a practical surrogate of IR, was linearly and positively associated with hyperuricemia in HTN and non-HTN participants. Proactive measures are needed to prevent the comorbidity of IR-driven hyperuricemia in the future.

Research on the supply and demand of elderly care service resources in China.

PURPOSE: This study aims to assess the current status and spatial distribution differences of elderly care service resources supply and demand in China. METHODS: Semi-structured qualitative interviews were utilized to gather participants' insights into the current demands for elderly care services, the status of resource allocation, and related indicators. The entropy weight method was employed to determine indicator weights, yielding objective demand and allocation indices for elderly care service resources. Kernel density estimation was used to illustrate the distribution characteristics of the demand and allocation indices. The coupling coordination degree model was applied to measure the coupling coordination level of China's elderly care service resource supply and demand system in 2020. RESULTS: The demand index ranks highest in Beijing (0.3291), Shanghai (0.2941), and Tianjin (0.2563), while the lowest are found in Tibet (0.1673), Guangxi (0.1727), and Guizhou (0.1737). Kernel density estimation shows that the demand index is concentrated in the range of 0.1800 to 0.2000. The top three regions for allocation index are Shanghai (184.0007), Qinghai (129.8177), and Beijing (109.5941), with the lowest in Liaoning (34.8558), Hainan (35.3168), and Yunnan (36.6366). Kernel density estimation indicates that the allocation index is concentrated in the range of 25-75. Calculations of coupling coordination degree show that Shanghai has high coordination quality (0.9368), Beijing has good coordination (0.8392), while Hainan and Yunnan experience severe imbalances (0.1990, 0.1831). CONCLUSIONS: There is a significant lack of coordination between the demand for elderly care services and the allocation of resources in Hainan and Yunnan provinces in China. Most provinces, with the exception of Beijing and Shanghai, exhibit some degree of misalignment. The Chinese government should address the varying needs of the elderly population in different regions, pay timely attention to regional disparities, enhance regional cooperation, and dynamically allocate elderly care resources in a rational manner.

Social integration and utilization of national basic public health services among China's internal migrants with chronic diseases: A structural equation modelling approach.

Internal migrants with chronic diseases (IMCDs) are a specific subgroup of the internal migrants, but few studies have focused on health service utilization among this group. Social integration is an essential element in the maintenance of health and well-being in migrants. However, the measurement of social integration remains inconsistent. This study aimed to measure social integration more comprehensively and evaluate the association between social integration and National Basic Public Health Services (NBPHS) utilization among IMCDs in China, thereby providing theoretical support for health promotion among IMCDs. The data of this study were obtained from the China Migrants Dynamic Survey (CMDS) in 2017. A total of 9272 internal migrants who self-reported hypertension and/or type 2 diabetes were included in the analysis. Four factors were extracted through exploratory factor analysis to measure the social integration of IMCDs: psychological identity, community involvement, social security, and sociocultural adaptation. The results show the IMCDs underutilized NBPHS, with 26.80 % stating that they have not used any of the services in the NBPHS. We confirmed the positive association between social integration and NBPHS use among IMCDs. The social integration of IMCDs in developed regions was relatively worse than in developing regions, further exacerbating the underutilization of NBPHS in developed regions. Therefore, targeted government measures and supportive policies are necessary, especially in developed regions, to encourage IMCDs to participate in social organizations and community activities and stimulate their active participation in the NBPHS.

Predictive value of machine learning on fracture risk in osteoporosis: a systematic review and meta-analysis.

OBJECTIVES: Early identification of fracture risk in patients with osteoporosis is essential. Machine learning (ML) has emerged as a promising technique to predict the risk, whereas its predictive performance remains controversial. Therefore, we conducted this systematic review and meta-analysis to explore the predictive efficiency of ML for the risk of fracture in patients with osteoporosis. METHODS: Relevant studies were retrieved from four databases (PubMed, Embase, Cochrane Library and Web of Science) until 31 May 2023. A meta-analysis of the C-index was performed using a random-effects model, while a bivariate mixed-effects model was used for the meta-analysis of sensitivity and specificity. In addition, subgroup analysis was performed according to the types of ML models and fracture sites. RESULTS: Fifty-three studies were included in our meta-analysis, involving 15 209 268 patients, 86 prediction models specifically developed for the osteoporosis population and 41 validation sets. The most commonly used predictors in these models encompassed age, BMI, past fracture history, bone mineral density T-score, history of falls, BMD, radiomics data, weight, height, gender and other chronic diseases. Overall, the pooled C-index of ML was 0.75 (95% CI: 0.72, 0.78) and 0.75 (95% CI: 0.71, 0.78) in the training set and validation set, respectively; the pooled sensitivity was 0.79 (95% CI: 0.72, 0.84) and 0.76 (95% CI: 0.80, 0.81) in the training set and validation set, respectively; and the pooled specificity was 0.81 (95% CI: 0.75, 0.86) and 0.83 (95% CI: 0.72, 0.90) in the training set and validation set, respectively. CONCLUSIONS: ML has a favourable predictive performance for fracture risk in patients with osteoporosis. However, most current studies lack external validation. Thus, external validation is required to verify the reliability of ML models. PROSPERO REGISTRATION NUMBER: CRD42022346896.

Couples' Cognition, Intimacy, and Activity Engagement: An Actor-Partner Interdependence Model Analysis.

OBJECTIVES: This study examines the actor and partner effects of cognition on activity engagement and the potential mediating role of intimate relationship in older couple dyadic context. METHODS: Data for this study were obtained from heterosexual couples who participated in the 2020 wave of the Health and Retirement Study. Constructing a dyadic model of couples' cognitions, activity engagement, and intimacy using structural equation modeling to analyze the relationship between variables and mediating effects. RESULTS: At the actor level, cognition was positively correlated with their activity participation. At the partner level, wives' cognition and husbands' activity engagement were positively correlated. Husband's cognitive score affect wife's subjective feelings about intimacy. The mediation effect of Wife's intimacy on the relationship between husband's cognition and wife's activity engagement was significant. CONCLUSIONS: In older couples, cognition influences activity engagement at a binary level, and this association is influenced by the level of intimacy. Improving intimacy can help increase activity engagement in older couples, which in turn promotes health. Clinical Implications Maintaining cognition helps older people enjoy good marriage and participation in activities. For women, the closer the partnership, the higher the frequency of participating in various activities.

The association between the Short Physical Performance Battery and longitudinal trajectories of depressive symptoms among Chinese older adults.

BACKGROUND: In this study, the long-term trajectories of depressive symptoms in a 7-year prospective survey cohort of Chinese older adults were explored. Additionally, the study examined whether there was an independent association between scores on the Short Physical Performance Battery (SPPB) and the different trajectories of depressive symptoms. METHODS: A total of 2177 elderly individuals had their depressive symptoms assessed based on the Center for Epidemiological Studies-Depression (CES-D) scale in the years 2011, 2013, 2015, and 2018. In addition, their demographic characteristics, chronic diseases, and lifestyle factors were also assessed. The trajectories of depressive symptoms were analysed using the group-based trajectories analysis model. Furthermore, the relationship between the objectively measured SPPB scores and the long-term trajectory of depressive symptoms was explored using multinomial logistic regression. RESULTS: The group-based trajectory analysis model categorized the trajectories of depressive symptoms across four waves into four groups: persistent low depressive symptoms, increasing depressive symptoms, decreased depressive symptoms, and persistent high depressive symptoms. After controlling for confounding factors, it was observed that a higher baseline SPPB score was associated with an increased likelihood of persistent high depressive symptoms, OR (95% CI) = 0.724 (0.644, 0.814), for the persistent high depressive symptoms versus the persistent low depressive symptoms. CONCLUSIONS: Low levels of SPPB score are associated with persistent high depressive symptoms in older adults. Conversely, improving physical performance as measured by the SPPB can help reduce the risk of major depressive disorder and persistent depressive disorder in the elderly.

Construction of predictive model for osteoporosis related factors among postmenopausal women on the basis of logistic regression and Bayesian network.

Osteoporosis is a prevalent chronic disease that often goes unnoticed in postmenopausal women. Early identification of risk factors for osteoporosis in postmenopausal women is essential. This study aimed to develop predictive models for osteoporosis-related factors among postmenopausal women in the U.S. and explore the influencing factors. In this cross-sectional study, we included 4417 postmenopausal women from the NHANES (2009-2010, 2013-2014, and 2017-2020). Through multiple regression analysis, we found that age, minutes of sedentary activity, prednisone or cortisone usage, arthritis, bone loss around teeth, and trouble sleeping were risk factors for osteoporosis after menopause. Conversely, height, BMI, and age at the last menstrual period were identified as protective factors. The findings from the Bayesian network analysis indicated that several factors influenced osteoporosis, including age, BMI, bone loss around teeth, prednisone or cortisone usage, arthritis, and age at the last menstrual period. On the other hand, minutes of sedentary activity and height might have indirect effects, while trouble sleeping may not have a significant impact. Both logistic regression and Bayesian network models demonstrated good predictive capabilities in predicting osteoporosis among postmenopausal women. In addition, Bayesian networks offer a more intuitive depiction of the intricate network risk mechanism between diseases and factors.

Prognostic models for breast cancer: based on logistics regression and Hybrid Bayesian Network.

BACKGROUND: To construct two prognostic models to predict survival in breast cancer patients; to compare the efficacy of the two models in the whole group and the advanced human epidermal growth factor receptor-2-positive (HER2+) subgroup of patients; to conclude whether the Hybrid Bayesian Network (HBN) model outperformed the logistics regression (LR) model. METHODS: In this paper, breast cancer patient data were collected from the SEER database. Data processing and analysis were performed using Rstudio 4.2.0, including data preprocessing, model construction and validation. The L_DVBN algorithm in Julia0.4.7 and bnlearn package in R was used to build and evaluate the HBN model. Data with a diagnosis time of 2018(n = 23,384) were distributed randomly as training and testing sets in the ratio of 7:3 using the leave-out method for model construction and internal validation. External validation of the model was done using the dataset of 2019(n = 8128). Finally, the late HER2 + patients(n = 395) was selected for subgroup analysis. Accuracy, calibration and net benefit of clinical decision making were evaluated for both models. RESULTS: The HBN model showed that seventeen variables were associated with survival outcome, including age, tumor size, site, histologic type, radiotherapy, surgery, chemotherapy, distant metastasis, subtype, clinical stage, ER receptor, PR receptor, clinical grade, race, marital status, tumor laterality, and lymph node. The AUCs for the internal validation of the LR and HBN models were 0.831 and 0.900; The AUCs for the external validation of the LR and HBN models on the whole population were 0.786 and 0.871; the AUCs for the external validation of the two models on the subgroup population were 0.601 and 0.813. CONCLUSION: The accuracy, net clinical benefit, and calibration of the HBN model were better than LR model. The predictive efficacy of both models decreased and the difference was greater in advanced HER2 + patients, which means the HBN model had higher robustness and more stable predictive performance in the subgroup.

The role of cognitive function in the relationship between surrogate markers of visceral fat and depressive symptoms in general middle-aged and elderly population: A nationwide population-based study.

BACKGROUND: The relationship between obesity and depressive symptoms is well documented, but not visceral fat, especially among Chinese adults are scarce. We aimed to investigate the association between visceral fat and depressive symptoms and the mediation of cognitive function. METHODS: A total of 19,919 and 5555 participants from the China Health and Retirement Longitudinal Study were enrolled in the cross-sectional and follow-up analyses. Depressive symptoms were measured by the Center of Epidemiological studies depression scale (CES-D). Visceral fat measured by the waist circumference triglyceride (WT) index [calculated as waist circumference (cm)* triglyceride (mmol/L)]. The relationship between the WT index and depressive symptoms was analyzed by binary logistics and Poisson regression. The mediated role of cognitive ability was examined by intermediary analysis. RESULTS: In the cross-sectional study, higher visceral fat was associated with a lower risk of depressive symptoms. But in the follow-up study, individuals in quintile 2 to quintile 4 of the WT index have a reduced risk of depressive symptoms after four years. Compared with the lower index, quintile 2 of the WT index protected from difficulty concentrating (RR [95%CI]: 0.90 [0.82,0.98], p = 0.023), feeling scared (RR [95%CI]: 0.86 [0.73,0.98], p = 0.030) and feeling that life could not go on (RR [95%CI]: 0.85 [0.74,0.98], p = 0.023). Moreover, cognitive ability explained 11.52 % of the association between visceral fat and depressive symptoms. CONCLUSIONS: Our findings show that moderate visceral fat was associated with a lower risk of depressive symptoms in middle-aged and older Chinese, partly mediated by cognitive function.

The association between longitudinal changes in depressive symptoms and cognitive decline among middle-aged and older Chinese adults.

OBJECTIVE: Depression is associated with cognitive impairment and dementia, but few studies have been done on Chinese adults. This study evaluates the relationship between depressive symptoms status and cognitive function in middle-aged and elderly Chinese adults. METHODS: We included 7,968 participants from the Chinese Health and Retirement Longitudinal Survey (CHRALS) with a follow-up of 4 years. Using the Center for Epidemiological Studies Depression Scale to measure depressive symptoms, with a score of 12 or more indicating elevated depressive symptoms. Adjust covariance analysis and generalized linear analysis were used to investigate the relationship between depressive symptoms status (never, new-onset, remission and persistence) and cognitive decline. Restricted cubic spline regression was used to performed the potential nonlinear associations between depressive symptoms and the change scores of cognitive functions. RESULTS: During the 4-year follow-up, 1148 participants (14.41%) reported persistent depressive symptoms. The participants who have persistent depressive symptoms with more declines in total cognitive scores (least-square mean = -1.99, 95% CI: -3.70 to -0.27). Compared with never depressive symptoms, participants with persistent depressive symptoms experienced a faster decline in cognitive scores (ß = -0.68, 95%CI: -0.98 to -0.38), and small difference (d=0.29) at follow-up. But females with new-onset depression had more cognitive decline than those with persistent depression (least-square mean new-onset - least-square mean persistent=-0.10), its differences in males (least-square mean new-onset - least-square mean persistent=0.03). CONCLUSIONS: Participants with persistent depressive symptoms experienced a faster decline in cognitive function, but differently in men and women.

Psychotherapy for advanced cancer patients: A meta-analysis of the quality of life and survival assessments.

OBJECTIVES: A meta-analysis has explored the effect of psychotherapy on the quality of life (QOL) but has not explored the effect on advanced cancer patients' survival, which is highly debated. Therefore, we consider the survival days and QOL as the primary outcomes in our analysis. METHODS: Eligible studies were collected from four databases (PubMed, Embase, Cochrane Library, and Web of Science) until February 20, 2021. The pooled effect sizes were presented as weighted mean difference (WMD) or relative risk (RR) with 95% confidence intervals (CIs). Publication bias was evaluated by Egger's test, and I2 statistics was used to assess the heterogeneity. RESULTS: Thirty-three studies were finally included, containing 2,159 patients in the psychotherapy group and 2,170 patients in the control group. McGill Quality of Life Questionnaire (MQOL) and European Organization for Research and Treatment of Cancer Quality of Life-C15-Palliative (EORTC-QLQ-C15-Pal) supported that QOL of the psychotherapy group was significantly higher than that of the control group, and WMD value was 0.42 (95% CI: 0.12-0.71) and 17.26 (95% CI: 11.08-23.44), respectively. No significant difference was observed between the two groups regarding to the survival time (WMD: 17.85, 95% CI: -8.79, 44.49, P = 0.189). Moreover, the levels of anxiety, depression, confusion, pain, and suffering were lowered in psychotherapy group (all P < 0.05). SIGNIFICANCE OF RESULTS: Psychotherapy could improve the QOL of advanced cancer patients but not affect the survival time.

Longitudinal association between muscle strength and depression in middle-aged and older adults: A 7-year prospective cohort study in China.

BACKGROUND: Evidence regarding the associations between muscle strength in different parts of the body and depression is lacking. This study examined whether poor muscle strength is associated with a higher incidence of depression in a large cohort of middle-aged and older adults. METHODS: In total, 5,228 middle-aged and older adults from the China Health and Retirement Longitudinal Study without depression at baseline were followed for 7 years. Their demographic characteristics, chronic diseases and lifestyle behaviors were assessed. After adjusting for relevant variables, a Cox regression was used to determine the relationship between muscle strength and incident depression. RESULTS: Over 32,544 person-years of follow-up, 1,490 participants developed depression. Low muscle strength at baseline was associated with a higher 7-year incident of depression, even after excluding those who developed depression within 2 years. After adjusting for confounding factors, it was found that a higher baseline relative handgrip strength was a protective factor against depression (HR [95% CI]=0.575 [0.430-0.768] for the lowest quartile vs. the highest quartile; p<0.001). Longer times on the 5TSTS test were a risk factor for depression (HR [95% CI]=1.321 [1.077-1.621] for the lowest quartile vs. the highest quartile; p = 0.007). When the strengths of the upper and lower limbs were considered together, the hazard ratio for depression in people with relatively greater muscle strength was 0.463 (95% CI=0.307-0.699; p<0.001). CONCLUSIONS: Muscle strength could be predictive of depression, and the combined measurement of upper and lower limb muscle strength can improve the predictive ability.

The association between pulmonary function and depression in middle-aged and elderly people in China: The role of cognitive ability and sleep time.

BACKGROUND: Depression is a common mental disorder in middle-aged and elderly people, which seriously affects their physical health and life quality.So far, whether pulmonary function is a factor in depression has not been tested.The purpose of this study was to test whether pulmonary function was independently associated with depression and to assess the effects of cognitive ability and sleep time on this association. METHODS: In this analysis, 5,235 participants from the Chinese Longitudinal Study of Health and Retirement were included. Participants were registered in 2015 and followed up in 2018. The relationship between pulmonary function and depression was estimated by binary logistic regression model. The mediated role of cognitive ability was examined by intermediary analysis, and the interaction between pulmonary function and sleep time on depression was discussed. RESULTS: After adjusting for confounding factors, it was found that higher baseline pulmonary function was the protective factor of depression (OR [95%CI]=0.524 [0.394-0.697] for the lowest quantile vs the highest quantile). Cognitive ability explained 14.55% of the association between pulmonary function and depression, pulmonary function and sleep time on the effects of depression have a combined interaction, RERI (95%CI) = 0.545 (0.053-1.038). CONCLUSIONS: High baseline pulmonary function is independently associated with a lower risk of depression, which is partly mediated by cognitive ability. Pulmonary function and sleep time have synergy with the effects of depression. These findings show that pulmonary function, cognitive ability and sleep time are reliable predictors of depression.

The relationships between step count and all-cause mortality and cardiovascular events: A dose-response meta-analysis.

BACKGROUND: A goal of 10,000 steps per day is widely advocated, but there is little evidence to support that goal. Our purpose was to examine the dose-response relationships between step count and all-cause mortality and cardiovascular disease risk. METHODS: Cochrane Central Register of Controlled Trials, EMBASE, OVID, PubMed, Scopus, and Web of Science databases were systematically searched for studies published before July 9, 2021, that evaluated the association between daily steps and at least 1 outcome. RESULTS: Sixteen publications (12 related to all-cause mortality, 5 related to cardiovascular disease; and 1 article contained 2 outcomes: both all-cause death and cardiovascular events) were eligible for inclusion in the meta-analysis. There was evidence of a nonlinear dose-response relationship between step count and risk of all-cause mortality or cardiovascular disease (p = 0.002 and p = 0.014 for nonlinearity, respectively). When we restricted the analyses to accelerometer-based studies, the third quartile had a 40.36% lower risk of all-cause mortality and a 35.05% lower risk of cardiovascular event than the first quartile (all-cause mortality: Q1 = 4183 steps/day, Q3 = 8959 steps/day; cardiovascular event: Q1 = 3500 steps/day, Q3 = 9500 steps/day; respectively). CONCLUSION: Our meta-analysis suggests inverse associations between higher step count and risk of premature death and cardiovascular events in middle-aged and older adults, with nonlinear dose-response patterns.

Prediction models for cardiovascular disease risk in the hypertensive population: a systematic review.

OBJECTIVE: The aim of this study was to identify, describe, and evaluate the available cardiovascular disease risk prediction models developed or validated in the hypertensive population. METHODS: MEDLINE and the Web of Science were searched from database inception to March 2019, and all reference lists of included articles were reviewed. RESULTS: A total of 4766 references were screened, of which 18 articles were included in the review, presenting 17 prediction models specifically developed for hypertensive populations and 25 external validations. Among the 17 prediction models, most were constructed based on randomized trials in Europe or North America to predict the risk of fatal or nonfatal cardiovascular events. The most common predictors were classic cardiovascular risk factors such as age, diabetes, sex, smoking, and SBP. Of the 17 models, only one model was externally validated. Among the 25 external validations, C-statistics ranged from 0.58 to 0.83, 0.56 to 0.75, and 0.64 to 0.78 for models developed in the hypertensive population, the general population and other specific populations, respectively. Most of the development studies and validation studies had an overall high risk of bias according to PROBAST. CONCLUSION: There are a certain number of cardiovascular risk prediction models in patients with hypertension. The risk of bias assessment showed several shortcomings in the methodological quality and reporting in both the development and validation studies. Most models developed in the hypertensive population have not been externally validated. Compared with models developed for the general population and other specific populations, models developed for the hypertensive population do not display a better performance when validated among patients with hypertension. Research is needed to validate and improve the existing cardiovascular disease risk prediction models in hypertensive populations rather than developing completely new models.

The efficiency analysis and spatial implications of health information technology: A regional exploratory study in China.

The new adoption of healthcare information technology is costly, and effects on healthcare performance can be questionable. This nationwide study in China investigated the efficient performance of healthcare information technology and examined its spatial correlation. Panel data were extracted from the Annual Investigation Report on Hospital Information in China and the China Health Statistics Yearbook for 2007 through 2015 (279 observations). Stochastic frontier analysis was employed to estimate the technical efficiency of healthcare information technology performance and related factors at the regional level. Healthcare information technology performance was positively associated with electronic medical records, total input, and cost of inpatient stay, while picture archiving and communication systems and net assets were negatively related. Local Indicators of Spatial Association showed that there existed significant spatial autocorrelation. Governmental policies would best make distinctions among different forms of healthcare information technology, especially between electronic medical records and picture archiving and communication systems. Policies should be formulated to improve healthcare information technology adoption and reduce regional differences.

Effect of community-based lifestyle interventions on weight loss and cardiometabolic risk factors in obese elderly in China: A randomized controlled trial.

PURPOSE: We aimed to assess the effect of community-based lifestyle interventions on weight loss and cardiometabolic risk factors among obese older adults, and to explore the potential factors that impede weight loss during lifestyle interventions. MATERIALS AND METHODS: A 2-arm parallel randomized controlled trial was conducted from 2013 through 2016 in the community health service centers in Nanjing, China. Four hundred and eighty obese older adults were randomly assigned to receive a 24-month lifestyle intervention (242 participants) or usual care (238 participants). The intervention group received a community-based behavioral lifestyle intervention program, which targeted weight loss through dietary changes and increased physical activity, with a combination mode of intervention delivery. RESULTS: Weight loss was statistically significant at the end of the intervention with a mean reduction of 0.03 ±â€¯2.51 kg in the control group and 3.22 ±â€¯3.43 kg in the intervention group (p < .001). In the intervention group, 41.1% of participants achieved the target of 5% weight loss significantly (p < .001). Participants in the intervention group had significantly greater improvements in cardiometabolic risk factors. Multivariable logistic regression showed that female, living alone, and having more comorbidities were barriers to weight loss during the intervention. CONCLUSIONS: This study demonstrated that community-based lifestyle interventions are effective for managing weight and improving cardiometabolic risk factors in obese older adults.

Group cognitive behavioural therapy of physical and psychological menopausal symptoms of Chinese women, delivered via Internet and mobile phone versus face to face: A protocol for a randomized non-inferiority trial.

BACKGROUND: Menopause syndrome generally includes psychological problems. Group treatment delivered via the Internet and mobile phone (imGT) may improve women's physiological and psychological conditions. OBJECTIVE: To investigate the efficacy of group cognitive behavioural therapy of menopause-related mood swings and quality of life, delivered face to face or via the Internet and mobile phone. METHODS: This protocol is for a randomized controlled clinical trial with a sample of 140 menopausal women divided into 2 groups: imGT and face-to-face group treatment (ffGT). The primary outcome will be the improvement in the menopausal symptoms of the two groups, as assessed by the Greene Climacteric Scale. The secondary outcomes will be: quality of life, assessed by the Short Form 36 Health Survey Questionnaire; insomnia, assessed by the Pittsburgh Sleep Quality Inventory; anxiety, assessed by the Hamilton Anxiety Rating Scale; and therapeutic alliance, assessed by the Working Alliance Inventory-Short Revised and Client Sat-is-fac-tion Qes-tion-naire-8. imGT will be performed once a week for 1.5 h for 10 weeks with a daily 'Punched-in' on the WeChat app; ffGT will be performed once a week for 1.5 h for 10 weeks. All outcomes will be assessed at baseline, at a post-intervention evaluation (week 10), and at a follow-up evaluation (week 22). DISCUSSION: This study will be the first clinical trial to examine the effects of imGT on menopausal women in China. If imGT is found to be non-inferior to ffGT, it will facilitate access to menopausal health services.

An interactive nomogram to predict healthcare-associated infections in ICU patients: A multicenter study in GuiZhou Province, China.

OBJECTIVE: To develop and validate an interactive nomogram to predict healthcare-associated infections (HCAIs) in the intensive care unit (ICU). METHODS: A multicenter retrospective study was conducted to review 2017 data from six hospitals in Guizhou Province, China. A total of 1,782 ICU inpatients were divided into either a training set (n = 1,189) or a validation set (n = 593). The patients' demographic characteristics, basic clinical features from the previous admission, and their need for bacterial culture during the current admission were extracted from electronic medical records of the hospitals to predict HCAI. Univariate and multivariable analyses were used to identify independent risk factors of HCAI in the training set. The multivariable model's performance was evaluated in both the training set and the validation set, and an interactive nomogram was constructed according to multivariable regression model. Moreover, the interactive nomogram was used to predict the possibility of a patient developing an HCAI based on their prior admission data. Finally, the clinical usefulness of the interactive nomogram was estimated by decision analysis using the entire dataset. RESULTS: The nomogram model included factor development (local economic development levels), length of stay (LOS; days of hospital stay), fever (days of persistent fever), diabetes (history of diabetes), cancer (history of cancer) and culture (the need for bacterial culture). The model showed good calibration and discrimination in the training set [area under the curve (AUC), 0.871; 95% confidence interval (CI), 0.848-0.894] and in the validation set (AUC, 0.862; 95% CI, 0.829-0.895). The decision curve demonstrated the clinical usefulness of our interactive nomogram. CONCLUSIONS: The developed interactive nomogram is a simple and practical instrument for quantifying the individual risk of HCAI and promptly identifying high-risk patients.