Objective:To explore the impact of multimorbidity on disability in older adults, providing a reference for formulating strategies for the management and nursing of multimorbidity and disability in older adults.Methods:Adopting the method of cross-sectional survey research, the data of 6 469 older adults (≥60 years old) were collected from the 2018 Chinese Longitudinal Healthy Longevity Survey database in July 2023, including basic information, chronic disease prevalence, and disability measured by basic activities of daily living (BADL), and instrumental activities of daily living (IADL). They were divided into multimorbidity and non-multimorbidity groups based on whether they had two or more chronic diseases. The propensity score matching (PSM) method was used to match the basic conditions of the two groups of older adults with the proportion of 1∶1. Binary logistic regression was applied to analyze the effects of multimorbidity on BADL disability and IADL disability.Results:Among 6 469 older adults, there were 2 882 males and 3 582 females, with 3 158 aged 60-84 years old and 3 311 aged over 84 years old. BADL disability accounted for 26.5% (1 712/6 469), while IADL disability accounted for 66.8% (4 324/6 469). There were 2 335 patients in the multimorbidity group and 4 134 patients in the non-multimorbidity group. Binary Logistic regression analysis showed that the risk of BADL disability in older adults in multimorbidity group was 1.511 times higher than that in the non-multimorbidity group (95% CI 1.317-1.734, P<0.01); the risk of IADL disability in older adults in the multimorbidity group was 1.618 times higher than that in the non-multimorbidity group (95% CI 1.426-1.835, P<0.01). Conclusions:Multimorbidity would increase the risk of disability in older adults. Relevant authorities should develop relevant interventions and nursing responses to enhance the prevention and management of multimorbidity and disability in older adults.

This article reported a patient who initially presented with insomnia complaints and was subsequently diagnosed with severe obstructive sleep apnea （OSA） on polysomnography （PSG）. The patient tried continuous positive airway pressure （CPAP）but gave up because wear the ventilator made it more difficult to fall asleep. Then the patient only received group cognitive behavioral therapy for insomnia （CBT-I）， which not only alleviated insomnia severity but also promoted severe OSA into mild status. Such case suggested that， firstly， due to the high comorbidity of insomnia and OSA， evaluation of OSA should be considered a part worth enough attention of the clinical diagnosis and treatment of insomnia patients. Secondly， by relieving insomnia， CBT-I can alleviate both nocturnal apnea and daytime somnolence in patients with comorbid insomnia and sleep apnoea （COMISA）， so the application of CBT-I should be emphasized in the treatment of such patients. ［Funded by the Central Government-guided Local Science and Technology Development Fund Project （number， 2022ZY0028）］

Objective To establish a universally applicable logistic risk prediction model for diabetes mellitus type 2(T2DM)in the middle-aged and elderly populations based on the results of a Meta-analysis,and to validate and confirm the efficacy of the model using the follow-up data of medical check-ups of National Basic Public Health Service.Methods Cohort studies evaluating T2DM risks were identified in Chinese and English databases.The logistic model utilized Meta-combined effect values such as the odds ratio(OR)to derive β,the partial regression coefficient,of the logistic model.The Meta-combined incidence rate of T2DM was used to obtain the parameter α of the logistic model.Validation of the predictive performance of the model was conducted with the follow-up data of medical checkups of National Basic Public Health Service.The follow-up data came from a community health center in Chengdu and were collected between 2017 and 2022 from 7 602 individuals who did not have T2DM at their baseline medical checkups done at the community health center.This community health center was located in an urban-rural fringe area with a large population of middle-aged and elderly people.Results A total of 40 cohort studies were included and 10 items covered in the medical checkups of National Basic Public Health Service were identified in the Meta-analysis as statistically significant risk factors for T2DM,including age,central obesity,smoking,physical inactivity,impaired fasting glucose,a reduced level of high-density lipoprotein cholesterol(HDL-C),hypertension,body mass index(BMI),triglyceride glucose(TYG)index,and a family history of diabetes,with the OR values and 95% confidence interval(CI)being 1.04(1.03,1.05),1.55(1.29,1.88),1.36(1.11,1.66),1.26(1.07,1.49),3.93(2.94,5.24),1.14(1.06,1.23),1.47(1.34,1.61),1.11(1.05,1.18),2.15(1.75,2.62),and 1.66(1.55,1.78),respectively,and the combined β values being 0.039,0.438,0.307,0.231,1.369,0.131,0.385,0.104,0.765,and 0.507,respectively.A total of 37 studies reported the incidence rate,with the combined incidence being 0.08(0.07,0.09)and the parameter α being-2.442 for the logistic model.The logistic risk prediction model constructed based on Meta-analysis was externally validated with the data of 7 602 individuals who had medical checkups and were followed up for at least once.External validation results showed that the predictive model had an area under curve(AUC)of 0.794(0.771,0.816),accuracy of 74.5%,sensitivity of 71.0%,and specificity of 74.7% in the 7 602 individuals.Conclusion The T2DM risk prediction model based on Meta-analysis has good predictive performance and can be used as a practical tool for T2DM risk prediction in middle-aged and elderly populations.

Amyloid-related imaging abnormalities(ARIA),intracranial signal abnormalities observed in magnetic resonance imaging(MRI),represent one of the main adverse events associated with treating Alzheimer's disease(AD)with anti-amyloid-β(anti-Aβ)monoclonal antibodies.In severe cases,patients'lives may be threatened.As the first anti-Aβ antibody was approved for use in China,clinical departments are now confronted with an increased likelihood of encountering ARIA in real-world scenarios.Accurate pre-treatment risk assessment,timely identification during medication,and severity evaluation of ARIA are of great significance in guiding clinical decisions.The identification and assessment of ARIA can be conducted from two perspectives—imaging and clinical symptoms.This article focuses on imaging.We reviewed the pathophysiological mechanisms,epidemiological and clinical characteristics,and imaging protocols and assessment of ARIA.We also stated at the end of the review that most current research data on ARIA came from clinical drug trials involving Caucasian populations,and that there was a lack of treatment experience in the real-world application of anti-Aβ monoclonal antibodies in Chinese populations.Many issues concerning pre-treatment risk assessment still need to be explored.Additionally,whether there are other clinical factors and imaging indicators that can help predict drug risks,and whether using different imaging protocols can help make a difference in patient management in the real world all require further investigation.

Antiviral therapy is an effective means of curing chronic hepatitis C (CHC) and a key focus of preventing the spread of hepatitis C. By analyzing domestic and foreign literature, this paper provides an overview of the estimation of the antiviral treatment rate for CHC, the current situation of antiviral treatment for CHC both domestically and internationally, and the factors that affect acceptance of antiviral treatment. At present, the antiviral treatment rate for CHC cases is relatively low both domestically and internationally. The treatment status of CHC cases is related to factors such as the general situation of the case, knowing their HCV status or self-perceived condition, concurrent presence of other diseases or conditions, knowledge of hepatitis C prevention and treatment, and social interaction and behavioral guidance. In response to the relevant difficulties, in-depth research or more support is needed to improve the antiviral treatment rate of CHC cases and achieve the goal of eliminating hepatitis C by 2030. Efforts should be made to strengthen policy support, improve the diagnosis of hepatitis C, prevent and control multiple diseases together, conduct targeted publicity and education, and enhance social support.

Antiviral therapy is an effective means of curing chronic hepatitis C (CHC) and a key focus of preventing the spread of hepatitis C. By analyzing domestic and foreign literature, this paper provides an overview of the estimation of the antiviral treatment rate for CHC, the current situation of antiviral treatment for CHC both domestically and internationally, and the factors that affect acceptance of antiviral treatment. At present, the antiviral treatment rate for CHC cases is relatively low both domestically and internationally. The treatment status of CHC cases is related to factors such as the general situation of the case, knowing their HCV status or self-perceived condition, concurrent presence of other diseases or conditions, knowledge of hepatitis C prevention and treatment, and social interaction and behavioral guidance. In response to the relevant difficulties, in-depth research or more support is needed to improve the antiviral treatment rate of CHC cases and achieve the goal of eliminating hepatitis C by 2030. Efforts should be made to strengthen policy support, improve the diagnosis of hepatitis C, prevent and control multiple diseases together, conduct targeted publicity and education, and enhance social support.

Objective:To explore the association of different obesity measurement indexes on serum C-reactive protein (CRP) in Chinese adult women.Methods:The data were obtained from baseline and follow-up surveys of the urban Breast Cancer Screening Program in Shuangliu District, Chengdu. A total of 441 adult women were included in the study. A questionnaire survey, physical examination, and laboratory testing were conducted on the subjects. Multivariate logistic regression model, two-level mixed effects logistic regression model, and restricted cubic spline method were used to investigate the linear and nonlinear correlation between different obesity measurement indexes and serum CRP in adult women.Results:For every 1 unit increase in BMI, waist circumference (WC), and adiposity, the risk of elevated serum CRP or exacerbation of chronic low-grade inflammation in adult women increased by 16.5%, 5.0%, and 11.1% ( P<0.05), respectively. Both BMI and adiposity were nonlinear correlated with serum CRP. Using BMI=24.0 kg/m 2 as the reference point, serum CRP level increased with the increase of BMI when BMI >24.0 kg/m 2. Using adiposity=30% as the reference point, serum CRP level increased with the increase of adiposity when adiposity >30%. Conclusions:Overall, obesity reflected by BMI had the strongest association with serum CRP in adult women, followed by body fat content reflected by adiposity, and central obesity reflected by WC had the weakest association with CRP. Adult women with BMI >24.0 kg/m 2 or adiposity >30% are at high risk for obesity-related inflammatory manifestations.