Background: Assessment the impact of disability on mortality among the elderly is vital to healthy ageing. The present study aimed to assess the long-term influence of disability on death in the elderly based on a longitudinal study. Method: This study used the Chinese Longitudinal Healthy Longevity Study (CLHLS) data from 2002 to 2014, including 13,666 participants aged 65 years and older in analyses. The Katz ADL index was used to assess disability status and levels. Cumulative mortality rates were estimated by the Kaplan-Meier method. Cox proportional hazards models were conducted to estimate associations between disability and all-cause mortality for overall participants, two age groups as well as specific chronic disease groups. All reported results were adjusted by survey weights to account for the complex survey design. Results: During the 12-year follow-up, the death density was 6.01 per 100 person-years. The 3-years’ cumulative mortality rate of nondisabled elderly was 11.9% (95%CI: 10.9, 12.9%). As the level of disability increased, the cumulative mortality rate was from 28.1% (95%CI: 23.0, 33.1%) to 77.6% (95%CI: 63.8, 91.4%). Compared with non-disabled elderly, the multiple-adjusted hazard ratio of death due to disability was 1.68 (95% CI: 1.48, 1.90). The hazard ratios varied from 1.44 (95%CI: 1.23, 1.67) to 4.45 (95%CI: 2.69, 7.38) after classifying the disability levels. The hazard ratios of death in the young-old group (65–79 years) were higher than the old-old group (80 years and over) in both level B (HR = 1.58, 95%CI: 1.25, 2.00 vs. HR = 1.22, 95%CI: 1.06, 1.39, P = 0.029) and level G (HR = 24.09, 95%CI: 10.83, 53.60 vs. HR = 2.56, 95%CI: 1.75, 3.74, P < 0.001). For patients with hypertension, diabetes, heart disease, cerebrovascular disease as well as dementia, disability increases their relative risk of mortality by 1.64 (95%CI: 1.40, 1.93), 2.85 (95%CI: 1.46, 5.58), 1.45 (95%CI: 1.02, 2.05), 2.13 (95%CI: 1.54, 2.93) and 3.56 (95%CI: 1.22, 10.38) times, respectively. Conclusions: Disability increases the risk of all-cause death in the elderly, especially those with chronic diseases and the young-old group. Further studies are needed to better understand how to effectively prevent disability in the older population.

Objective: Previous studies have demonstrated an association between anxiety and metabolic syndrome (MetS). However, the association is still controversial. This updated meta-analysis aimed to reanalyze the association between anxiety and MetS.Methods: We comprehensively searched PubMed, Embase and Web of Science for all related studies published before January 23, 2023. Observational studies that informed effect size with 95% confidence interval (CI) for the association between anxiety and MetS were included. According to heterogeneity between studies, fixed or random effects models were applied to calculate the pooled effect size. Publication bias was examined by funnel plots.Results: The research included 24 cross-sectional studies: 20 studies used MetS as the dependent variable with a pooled OR of 1.07 (95% CI: 1.01–1.13) and four studies used anxiety as the dependent variable with a pooled OR of 1.14 (95% CI: 1.07–1.23). Three cohort studies were found: two studies detected the association of baseline anxiety with the risk of MetS, one of the studies demonstrated a significant association, but a similar result was not found in another study; one study showed no significant association between baseline MetS and the risk of anxiety.Conclusion: Cross-sectional studies indicated an association between anxiety and MetS. The results from cohort studies are still inconsistent and limited. More large-scale prospective studies are needed to further reveal the causal relationship of anxiety with MetS.

Background The association between antipsychotics and cardiovascular diseases (CVDs) remains significant yet unestablished, especially in Chinese populations. Objective To investigate the risk of CVDs associated with antipsychotics among Chinese individuals with schizophrenia. Methods We conducted a nested case–control study on individuals diagnosed with schizophrenia in Shandong, China. The case group included individuals diagnosed with incident CVDs between 2012 and 2020. Each case was randomly matched with up to three controls. We used weighted logistic regression models to assess the risk of CVDs associated with antipsychotics and restricted cubic spline analysis to explore the dose–response relationship. Findings In total, 2493 cases and 7478 matched controls were included in the analysis. Compared with non-users, any antipsychotics use was associated with higher risk of any CVDs (weighted OR=1.54, 95% CI 1.32 to 1.79), with the risk mainly driven by ischaemic heart diseases (weighted OR=2.26, 95% CI 1.71 to 2.99). Treatments with haloperidol, aripiprazole, quetiapine, olanzapine, risperidone, sulpiride and chlorpromazine were associated with increased risk of CVDs. A non-linear dose–response relationship between dosage of antipsychotics and risk of CVDs was observed, with a sharp increase in risk in the beginning and then flattening out with higher doses. Conclusions Use of antipsychotics was associated with increased risk of incident CVDs among individuals with schizophrenia, and the risk varied substantially among different antipsychotics and specific CVDs. Clinical implications Clinicians should consider the cardiovascular risk of antipsychotics and choose the appropriate type and dose of drugs in the treatment of schizophrenia.

Question Collective evidence for the bidirectional association between depression and autoimmune diseases (ADs) is scarce, especially for subgroups of patients with specific ADs. We conducted a meta-analysis to determine the incidence rates and relative risks (RRs) of depression among patients with ADs, and vice versa. Study selection and analysis PubMed, Embase, Web of Science, Ovid, PsycNet and Cochrane were searched up to 10 September 2024. Cohort studies evaluating longitudinal risks between ADs and depression were included. Incidence rates and RRs of depression among patients with ADs and vice versa were pooled. Findings The analysis included 47 studies, involving over 40.77 million participants. The pooled incidence rate of depression among patients with ADs was 6.71% (95% CI 5.10% to 8.77%), with an RR of 1.85 (95% CI 1.57 to 2.19), higher in patients aged over 45 (2.30; 95% CI 1.62 to 3.26) and females (1.88; 95% CI 1.61 to 2.20). Conversely, the pooled incidence rate of ADs among depression was 0.54% (95% CI 0.24% to 1.19%), with an RR of 1.84 (95% CI 1.10 to 3.09). The incidence rate and RRs also varied across subgroups with the highest incidence rate in the musculoskeletal system and connective tissue (1.36; 95% CI 0.50 to 3.63) and RR in the genitourinary system (2.23; 95% CI 1.98 to 2.51). Conclusions This study identified a bidirectional association between depression and ADs, with higher RRs among patients aged over 45 and females. Especially higher risks were also found for specific types of ADs including endocrine, nutritional, and metabolic diseases, genitourinary system, and skin and subcutaneous tissue. PROSPERO registration number CRD42024541053.

Background: The mortality rate of acute respiratory distress syndrome (ARDS) increases with age (≥ 65 years old) in critically ill patients, and it is necessary to prevent mortality in elderly patients with ARDS in the intensive care unit (ICU). Among the potential risk factors, dynamic subphenotypes of respiratory rate (RR), heart rate (HR), and respiratory rate-oxygenation (ROX) and their associations with 28-day mortality have not been clearly explored. Methods: Based on the eICU Collaborative Research Database (eICU-CRD), this study used a group-based trajectory model to identify longitudinal subphenotypes of RR, HR, and ROX during the first 72 h of ICU stays. A logistic model was used to evaluate the associations of trajectories with 28-day mortality considering the group with the lowest rate of mortality as a reference. Restricted cubic spline was used to quantify linear and nonlinear effects of static RR-related factors during the first 72 h of ICU stays on 28-day mortality. Receiver operating characteristic (ROC) curves were used to assess the prediction models with the Delong test. Results: A total of 938 critically ill elderly patients with ARDS were involved with five and 5 trajectories of RR and HR, respectively. A total of 204 patients fit 4 ROX trajectories. In the subphenotypes of RR, when compared with group 4, the odds ratios (ORs) and 95% confidence intervals (CIs) of group 3 were 2.74 (1.48–5.07) (P = 0.001). Regarding the HR subphenotypes, in comparison to group 1, the ORs and 95% CIs were 2.20 (1.19–4.08) (P = 0.012) for group 2, 2.70 (1.40–5.23) (P = 0.003) for group 3, 2.16 (1.04–4.49) (P = 0.040) for group 5. Low last ROX had a higher mortality risk (P linear = 0.023, P nonlinear = 0.010). Trajectories of RR and HR improved the predictive ability for 28-day mortality (AUC increased by 2.5%, P = 0.020). Conclusions: For RR and HR, longitudinal subphenotypes are risk factors for 28-day mortality and have additional predictive enrichment, whereas the last ROX during the first 72 h of ICU stays is associated with 28-day mortality. These findings indicate that maintaining the health dynamic subphenotypes of RR and HR in the ICU and elevating static ROX after initial critical care may have potentially beneficial effects on prognosis in critically ill elderly patients with ARDS.