Construction and verification of risk prediction model of osteoporotic fractures in patients with osteoporosis in China.

Objective: To explore the influencing factors of osteoporotic fractures (OPF) in patients with osteoporosis, construct a prediction model, and verify the model internally and externally, so as to provide reference for early screening and intervention of OPF in patients with osteoporosis. Methods: Osteoporosis patients in the First Affiliated Hospital of Soochow University were selected, and the medical records of patients were consulted through the Hospital Information System (HIS) and the data management platform of osteoporosis patients, so as to screen patients who met the criteria for admission and discharge and collect data. SPSS 26.0 software was used for single factor analysis to screen statistically significant variables (p < 0.05). The influencing factors of OPF were determined by multivariate analysis, and a binary Logistic regression model was established according to the results of multivariate analysis. Hosmer-Lemeshow (H-L) goodness of fit and receiver operating characteristic curve (ROC) were used to test the model's efficiency, and Stata 16.0 software was used to verify the Bootstrap model, draw the model calibration curve, clinical applicability curve and nomogram. Results: In this study, the data of modeling set and verification set were 1,435 and 580, respectively. There were 493 (34.4%) cases with OPF and 942 (65.6%) cases without OPF in the modeling set. There were 204 (35.2%) cases with OPF and 376 (64.8%) cases without OPF. The variables with statistically significant differences in univariate analysis are Age, BMI, History of falls, Usage of glucocorticoid, ALP, Serum Calcium, BMD of lumbar, BMD of feminist neck, T value of feminist neck, BMD of total hip and T value of total hip. The area under ROC curve of the risk prediction model constructed this time is 0.817 [95%CI (0.794 ~ 0.839)], which shows that the model has a good discrimination in predicting the occurrence of OPF. The optimal threshold of the model is 0.373, the specificity is 0.741, the sensitivity is 0.746, and the AUC values of the modeling set and the verification set are 0.8165 and 0.8646, respectively. The results of Hosmer and Lemeshow test are modeling set: (χ2 = 6.551, p = 0.586); validation set: [(χ2 = 8.075, p = 0.426)]. The calibration curve of the model shows that the reference line of the fitted curve and the calibration curve is highly coincident, and the model has a good calibration degree for predicting the occurrence of fractures. The net benefit value of the risk model of osteoporosis patients complicated with OPF is high, which shows that the model is effective. Conclusion: In this study, a OPF risk prediction model is established and its prediction efficiency is verified, which can help identify the high fracture risk subgroup of osteoporosis patients in order to choose stronger intervention measures and management.

The role of depression between sleep disorders and frailty among elderly patients with chronic kidney disease (CKD) in China: a cross-sectional study.

OBJECTIVE: To investigate the correlation among sleep disorders, physical frailty, and depression in elderly patients with chronic kidney disease (CKD), and to explore the mediating role of depression. METHODS: This was a cross-sectional study, simple sampling was used to investigate the elderly CKD patients from one tertiary hospital in Shanghai. Those CKD patients who were diagnosed as CKD1-5 phase and were admitted to the Renal Medicine Ward from January to June 2022 and provided formal consent were considered for inclusion in our study. They were investigated with frailty phenotype (FP), Pittsburgh sleep quality index (PSQI), Center for Epidemiological Studies Depression Scale (CES-D), and self-made general information questionnaire. Linear regression was used to assess the associations between the variables, before this, PROCESS v4.1 was used to transform PSQI, CES-D and FP score to improve its normality, and conduct intermediary analysis. A difference of p < 0.05 was statistically significant. RESULTS: A total of 504 elderly patients with CKD completed the questionnaire survey, aged 60-91. The incidence of sleep disorders among elderly patients with CKD was 60%, and the incidence of physical frailty was 18%. The depression was positively correlated with physical frailty (r = 0.418, p < 0.01) and sleep disorders (r = 0.541, p < 0.01). Physical frailty was positively correlated with sleep disorders (r = 0.320, p < 0.01). The depression plays a significant mediating role in the model, and the effect ratio of depression is 52%. CONCLUSION: Depression is a mediating variable between sleep disorders and frailty. Improving depression in elderly patients with CKD accompanied by sleep disorders can help delay the occurrence of frailty.

Correlation among sleep quality, physical frailty and cognitive function of the older adults in China: the mediating role.

Objective: To explore the correlation among sleep quality, physical frailty, and cognitive function in the older adults in community, and to explore the mediating role of sleep quality. Methods: A total of 1,182 community-based older adults were investigated with frailty phenotype (FP), Pittsburgh sleep quality index (PISQI), Montreal cognitive assessment (MoCA) and self-made general information questionnaire. Results: The incidence of physical frailty among the older adults in the community was 25.8% and the incidence of cognitive decline was 19.5%. Cognitive function was negatively correlated with physical frailty (r = -0.236, p < 0.01) and sleep quality (r = -0.558, p < 0.01). Sleep quality was positively correlated with physical frailty (r = 0.337, p < 0.01). Conclusion: The physical frailty of the older adults has a direct prediction effect on cognitive function, and is regulated by the mediating role of sleep quality. Sleep quality partially mediates the relationship between cognitive dysfunction and physical frailty, which is a new insight into the study of cognition and physical frailty in the older adults. In the future, we can take measures to improve the sleep quality of the older adults, so as to reduce the occurrence of cognitive dysfunction and physical frailty of the older adults.

Predicting the relationship between anxiety and health-related quality of life in post-stroke patients: The role of sleep duration.

OBJECTIVES: Sleep and psychological disorders are common complaints in stroke survivors. The effectiveness of sleep duration in post-stroke on mental well-being and health outcomes has been reported recently. This study aimed to investigate the mediating effect of sleep duration on the relationship between anxiety and health-related quality of life in Chinese post-stroke; MATERIALS AND METHODS: We conducted a quantitative, cross-sectional study with participants recruited through a multistage, stratified, probability proportional to size sampling method. Anxiety, health-related quality of life, and sleep duration were measured by Zung Self-rating Anxiety Scale, World Health Organization Quality of Life Questionnaire, and a self-administered, structured questionnaire. A multiple linear regression analysis was conducted to identify the association between anxiety, sleep duration, and quality of life. The direct and indirect effects of sleep duration on health-related quality of life was assessed using the bootstrap method via Model 4 (parallel mediation) of SPSS PROCESS macro; RESULTS: A total of 856 post-stroke patients participated in the study, and incidence of anxiety symptom amongst post-stroke was 33.53%. Sleep duration mainly plays partial mediating roles in the relationship between mild-to-moderate anxiety and quality of life in physical, psychological, and environment domains, with sleep duration of 7-8h playing a major role; CONCLUSIONS: A significant relationship among anxiety, sleep duration, and quality of life in post-stroke was found in this study. The sleep duration partially mediated the association between anxiety and quality of life. Suitable prevention methods and early interventions for sleep duration may improve the quality of life for post-stroke anxiety.

Quality of life and associated factors among community-dwelling adults with multimorbidity in Shanghai, China: A cross-sectional study.

AIM: To compare the quality of life of patients with and without multimorbidity and investigate potential factors related to the quality of life in patients with multimorbidity. DESIGN: A descriptive cross-sectional study. METHODS: This study included 1778 residents with chronic diseases, including single disease (1255 people, average age: 60.78 ± 9.42) and multimorbidity (523 people, average age: 64.03 ± 8.91) groups, who were recruited from urban residents of Shanghai through a multistage, stratified, probability proportional to size sampling method. The quality of life was measured using the World Health Organization Quality of Life Questionnaire. The socio-demographic data and psychological states were measured using a self-made structured questionnaire, Self-rating Anxiety Scale, and Self-rating Depression Scale. Differences in demographic characteristics were estimated using Pearson's chi-squared test, and independent t-test or one-way ANOVA followed by S-N-K test was used to compare the mean quality of life. Multiple linear regression analysis was conducted to identify risk factors for multimorbidity. RESULTS: There were differences in age, education, income, and BMI between single-disease and multimorbidity groups, but no differences in gender, marriage, and occupation. Multimorbidity had lower quality of life, reflected in all four domains. Multiple linear regression analyses showed that low level of education, low income, number of diseases, depression, and anxiety were negatively related to quality of life in all domains.

Construction and validation of cognitive frailty risk prediction model for elderly patients with multimorbidity in Chinese community based on non-traditional factors.

BACKGROUND AND OBJECTIVES: Early identification of risk factors and timely intervention can reduce the occurrence of cognitive frailty in elderly patients with multimorbidity and improve their quality of life. To explore the risk factors, a risk prediction model is established to provide a reference for early screening and intervention of cognitive frailty in elderly patients with multimorbidity. METHODS: Nine communities were selected based on multi-stage stratified random sampling from May-June 2022. A self-designed questionnaire and three cognitive frailty rating tools [Frailty Phenotype (FP), Montreal Cognitive Assessment (MoCA), and Clinical Qualitative Rating (CDR)] were used to collect data for elderly patients with multimorbidity in the community. The nomogram prediction model for the risk of cognitive frailty was established using Stata15.0. RESULTS: A total of 1200 questionnaires were distributed in this survey, and 1182 valid questionnaires were collected, 26 non-traditional risk factors were included. According to the characteristics of community health services and patient access and the logistic regression results, 9 non-traditional risk factors were screened out. Among them, age OR = 4.499 (95%CI:3.26-6.208), marital status OR = 3.709 (95%CI:2.748-5.005), living alone OR = 4.008 (95%CI:2.873-5.005), and sleep quality OR = 3.71(95%CI:2.730-5.042). The AUC values for the modeling and validation sets in the model were 0. 9908 and 0.9897. Hosmer and Lemeshow test values for the modeling set were χ2 = 3.857, p = 0.870 and for the validation set were χ2 = 2.875, p = 0.942. CONCLUSION: The prediction model could help the community health service personnel and elderly patients with multimorbidity and their families in making early judgments and interventions on the risk of cognitive frailty.

Job burnout and its influencing factors in Chinese medical staffs under China's prevention and control strategy for the COVID-19 pandemic.

OBJECTIVE: This study aimed to investigate the influencing factors of burnout among grassroots medical staff in China so as to provide a reference for improving their physical, psychological, and social statuses under China's prevention and control strategy for the COVID-19 pandemic and ensuring the sustainable supply of high-quality medical resources. METHODS: This study was performed on medical staff in five primary hospitals in Jiangsu Province, China, from May 1, 2022, to June 1, 2022, using a general information questionnaire and Maslach Burnout Inventory Scale. SPSS 25.0 and Stata 15.0 were used for two-track data entry and analysis. The OLS regression model was established to analyze the influencing factors for the job burnout of health care personnel. RESULTS: Two hundred seventy valid questionnaires were analyzed. The total score of job burnout was (30.16 ± 10.99). The scores of emotional exhaustion, depersonalization, and self-achievement were (9.88 ± 3.839), (11.99 ± 5.68), and (8.29 ± 5.18), respectively. Feeling depressed and stressed after the pandemic, days working over the past week, and work hours per shift had a positive impact on the Maslach Burnout total score. Increased income and hours working every week had a negative impact on the Maslach Burnout total score. However, sex, age in years, degree, professional title, job category, workplace, marital status, years in practice, health status, active management of health, idea of resignation, and promotion after the pandemic did not affect the Maslach Burnout total score. CONCLUSION: The job burnout of medical staff is affected by health conditions, working conditions, the psychological consequences of a pandemic, wages and marital status. Hospital managers should formulate incentive measures according to different psychological changes in medical staff to create a good medical working environment under the normalization of COVID-19 pandemic prevention and control.

The effects of physical activity on depression and quality of life in Chinese perimenopausal women.

BACKGROUND: Women are more likely to experience depressive symptoms and poor quality of life (QoL) during perimenopause. The effectiveness of physical activity (PA) in perimenopause on mental well-being and health outcomes has been frequently reported. This study aimed to investigate the mediating effect of PA on the relationship between depression and QoL in Chinese perimenopausal women. METHODS: A cross-sectional study was performed, and participants were recruited through a multistage, stratified, probability proportional to size sampling method. Depression, PA, and QoL were measured by Zung Self-rating Depression Scale, Physical Activity Rating Scale-3, and World Health Organization Quality of Life Questionnaire. The direct and indirect effects of PA on QoL were analyzed by PA in a mediation framework. RESULTS: 1100 perimenopausal women participated in the study. PA mainly plays partial mediating roles in the relationship between depression and physical (ab = -0.493, 95 % CI: -0.582 to -0.407; ab = -0.449, 95 % CI: -0.553 to -0.343) and psychological (ab = -0.710, 95 % CI: -0.849 to -0.578; ab = -0.721, 95 % CI: -0.853 to -0.589; ab = -0.670, 95 % CI: -0.821 to -0.508) domains of QoL. Additionally, intensity (ab = -0.496, 95 % CI: -0.602 to -0.396; ab = -0.355, 95 % CI: -0.498 to -0.212) and duration (ab = -0.201, 95 % CI: -0.298 to -0.119; ab = -0.134, 95 % CI: -0.237 to -0.047) intermediated the relationship between moderate-to-severe depression and physical domain; frequency (ab = -0.130, 95 % CI: -0.207 to -0.066) only had a mediation influence between moderate depression and physical domain; intensity (ab = -0.583, 95 % CI: -0.712 to -0.460; ab = -0.709, 95 % CI: -0.854 to -0.561; ab = -0.520, 95 % CI: -0.719 to -0.315), duration (ab = -0.433, 95 % CI: -0.559 to -0.311; ab = -0.389, 95 % CI: -0.547 to -0.228; ab = -0.258, 95 % CI: -0.461 to -0.085), and frequency (ab = -0.365, 95 % CI: -0.493 to -0.247; ab = -0.270, 95 % CI: -0.414 to -0.144) all interceded between the psychological domain and all levels of depression, except for the frequency between severe depression and psychological domain; in terms of social relationship and environment domains, intensity (ab = -0.458, 95 % CI: -0.593 to -0.338; ab = -0.582, 95 % CI: -0.724 to -0.445), duration (ab = -0.397, 95 % CI: -0.526 to -0.282; ab = -0.412, 95 % CI: -0.548 to -0.293), and frequency (ab = -0.231, 95 % CI: -0.353 to -0.123; ab = -0.398, 95 % CI: -0.533 to -0.279) were mediators only on mild depression. LIMITATIONS: The cross-sectional study and self-reported data are major limiting factors. CONCLUSION: PA and its components partially mediated the association between depression and QoL. Suitable prevention methods and interventions for PA may improve the QoL for perimenopausal women.

Mediating effects of sleep duration on the association between natural menopause and stroke risk among Chinese women.

Background: Sleep disturbance is commonly reported by menopausal women. Stroke risk and poor stroke outcomes in women have usually been attributed to menopause. This study aimed to investigate the mediating effect of sleep duration on relationship between menopause and risk of stroke in natural menopause women. Materials and methods: A cross-sectional study was performed, and participants were recruited through a multistage, stratified, probability proportional to size sampling method in this research. The stroke risk was measured using the risk assessment form for high-risk stroke population. The average sleep duration was calculated by adding up night sleep and afternoon nap duration. Multivariate regression analysis was conducted to identify the association between menopause, sleep duration, and stroke risk. The direct and indirect effects of menopause on stroke risk were analyzed by using the sleep duration in a mediation framework. Results: Perimenopause, menopause, average sleep duration, and night sleep duration were significantly associated with stroke risk (P < 0.001), after adjusting for covariates. Perimenopause and menopause were significantly related to average sleep duration (P < 0.001) and night sleep duration (P < 0.001). The average sleep duration (ab = 0.016, 95% CI: 0.003, 0.030; ab = -0.048, 95% CI: -0.070, -0.027) partially mediated the relationship between menopause and stroke risk. And night sleep duration (ab = 0.024, 95% CI: 0.009, 0.040; ab = -0.054, 95% CI: -0.077, -0.033) played a major mediating role, in which night sleep duration of ≤5 h mediated the link between both perimenopause (ab = 0.707, 95% CI: 0.392, 1.021) and menopause (ab = -0.787, 95% CI: -1.096, -0.478) and stroke risk; both night sleep duration of >8-9 h (ab = 0.079, 95% CI: 0.010, 0.193) and >9 h (ab = 0.379, 95% CI: 0.086, 0.712) had mediating effects on perimenopause and stroke risk. Conclusion: A significant relationship between menopause and stroke risk factors among natural menopausal status was found in this study. The average sleep duration, especially night sleep duration, partially mediated the association between menopause and stroke risk, which is a novel insight to the progression of stroke risk in Women. Suitable prevention methods and interventions for sleep in menopausal women may reduce the risk of stroke.