Journal of the American Medical Directors Association最新文献

Objectives: To examine the independent and combined associations of handgrip strength (HGS) and knee extension strength (KES) with global cognition in community-dwelling older adults.

Design: Cross-sectional analysis of baseline data from a prospective cohort.

Setting and participants: A total of 279 community-dwelling adults aged 65 years or older living independently (mean age 76.8 ± 5.9; 26.5% men).

Methods: Low strength was defined as the sex-specific lowest quartile (Q1). Multiple linear regression estimated differences in Mini-Mental State Examination (MMSE) scores adjusting for age, sex, education, and depressive symptoms (GDS-15). We examined (1) HGS and KES together, (2) 4 exclusive groups (low KES only, low HGS only, both low, neither), and (3) sensitivity analyses including skeletal muscle index and sex-stratified analyses using weight-normalized KES.

Results: Low KES related to lower MMSE (Model 1 B, -0.882; 95% CI, -1.542 to -0.223, P = .009; Model 2 B, -0.892; 95% CI, -1.564 to -0.219; P = .010). Low HGS was not significant (P ≥ .27). When both were included, low KES remained significant (B, -0.814; 95% CI, -1.509 to -0.119; P = .022) but low HGS did not. In 4-group analysis, both low KES and HGS vs neither showed lower MMSE (B, -1.054; 95% CI, -1.984 to -0.112; P = .027). Associations for KES persisted after adjusting for skeletal muscle index (B, -0.842; 95% CI, -1.522 to -0.161; P = .016). In sex-stratified models, weight-normalized KES was associated with MMSE in men (B, 6.598; 95% CI, 2.258 to 10.939; P = .004) but not in women.

Conclusions and implications: Lower KES shows a consistent and independent association with global cognition; combined weakness in upper and lower limbs signals greater cognitive deficit. Adding KES to community screening may improve early detection of cognitive vulnerability.

Objectives: Loss of a spouse increases risk for cognitive and functional decline in older age. However, literature examining bereavement effects on cognition and daily functioning in veterans is limited. This study therefore examined differences in cognitive and functional trajectories after spousal loss in older male veterans.

Design: Retrospective cohort study.

Setting and participants: Participants included 3339 male, community-dwelling veterans in the Health and Retirement Study aged >51 years who were married/partnered at enrollment and remained married (n = 2849) or became widowed (n = 490).

Methods: Participants completed biannual cognitive testing (Telephone Interview of Cognitive Status) and basic activities of daily living (ADL) and instrumental activities of daily living (IADL) questionnaires, and reported medical comorbidities and marital status. A generalized additive mixed-effects model compared annual rates of cognitive decline between married and widowed participants. Negative binomial regression evaluated associations between widowhood, ADLs, and IADLs. Poisson regression tested associations between widowhood and medical comorbidities. All models adjusted for age, race, ethnicity, years of education, depression, recent hospitalization, medical comorbidities, body mass index, years worked, income, and mortality.

Results: Results indicated greater cognitive decline after spousal loss between ages 64 to 76 years and after aged 84 years. Widowhood was associated with greater IADL difficulty [incidence rate ratio (IRR), 1.20; 95% CI, 1.01-1.43] and requiring IADL assistance (IRR, 1.38; 95% CI, 1.14-1.68). No associations were found between widowhood and basic ADL difficulty (IRR, 1.14; 95% CI, 0.97-1.34), requiring ADL assistance (IRR, 1.04; 95% CI, 0.77-1.41), or medical comorbidities (IRR, 0.99; 95% CI, 0.94-1.04). Sensitivity analyses including only widowers revealed greater post-loss ADL difficulty (IRR, 1.30; 95% CI, 1.04-1.63), ADL assistance (IRR, 1.76; 95% CI, 1.14-2.73), and medical comorbidities (IRR, 1.12; 95% CI, 1.05-1.20).

Conclusions and implications: Compared with married veterans, widowers had greater rates of cognitive decline, greater difficulty completing IADLs, and increased medical comorbidities. These findings may inform access to mental health services addressing bereavement and other clinical outcomes after widowhood.

Objectives: This study examined the incidence of hospitalizations for urinary tract infections (UTIs) and associated factors among residents of long-term care facilities (LTCFs) during the first 12 months of their LTCF stay.

Design: Population-based retrospective cohort study.

Setting and participants: This study included people aged ≥65 years who first entered an LTCF between 2015 and 2018 using data from the Registry of Senior Australians National Historical Cohort.

Methods: The cumulative incidence of hospitalizations of UTI in the 12 months following LTCF entry was evaluated. Individual, facility, medicine, and service utilization-related factors associated with hospitalizations for UTIs were investigated. A Fine-Gray model was used to estimate subdistribution hazard ratios (sHRs) and 95% CIs.

Results: Of the 180,858 people included from 2464 LTCFs, 59.7% (n = 107,914) were female, with a median age of 85 years. The cumulative incidence of hospitalizations for UTIs in the 12 months after LTCF entry was 3.7% (95% CI 3.7-3.8). Factors associated with a higher rate of hospitalizations for UTIs included long-term urinary catheter use (sHR 3.39, 95% CI 3.16-3.65), history of hospitalizations with UTI (sHR 2.33, 95% CI 2.21-2.46), preferred language other than English (sHR 1.38, 95% CI 1.28-1.48), diabetes (sHR 1.29, 95% CI 1.22-1.37), high (sHR 1.30, 95% CI 1.19-1.41) or medium (sHR 1.21, 95% CI 1.11-1.32) need for assistance with activities of daily living, cerebrovascular disease (sHR 1.14, 95% CI 1.08-1.20), and urinary incontinence (sHR 1.08, 95% CI 1.01-1.15).

Conclusions and implications: A considerable burden of UTI-associated hospitalizations was observed in Australian LTCFs, which can be minimized through implementing effective UTI prevention, detection, and management strategies.

Objective: To develop and internally validate a malnutrition screening tool based on routinely collected data in the long-term care setting.

Design: Diagnostic prediction model development and internal validation study.

Setting and participants: Residents (n = 539) from 10 long-term care facilities in Australia.

Methods: Candidate variables identified through expert consultation were collected from routinely collected data in a convenience sample of long-term care facilities. Logistic regression using the Subjective Global Assessment as the reference standard was conducted on 500 samples derived using bootstrapping from the original sample. Candidate variables were selected if included in more than 95% of samples using backwards stepwise elimination. The final model was developed using logistic regression of selected variables. Internal validation was conducted using bootstrapping to calculate the optimism-adjusted performance. Overall discrimination was evaluated via receiver operator characteristic curve and calculation of the area under the curve. Youden's Index was used to identify the optimal threshold value for classifying malnutrition. Sensitivity and specificity were calculated.

Results: Body mass index and weight change % over 6 months were included in the automated malnutrition screening model (AutoMal), identified in 100% of bootstrapped samples. AutoMal demonstrated excellent discrimination of malnutrition, with area under the curve of 0.8378 (95% CI, 0.80-0.87). Youden's Index value was 0.37, resulting in sensitivity of 78% (95% CI, 71%-83%) and specificity of 77% (72%-81%). Optimism-corrected area under the curve was 0.8354.

Conclusions and implications: The AutoMal demonstrates excellent ability to differentiate malnutrition status. It makes automated identification of malnutrition possible by using 2 variables commonly found in electronic health records.

Objective: To examine whether having tele-mental health (tele-MH) visits with new providers is different by race, ethnicity, Medicare-Medicaid dual eligibility, and rurality.

Design: Retrospective study.

Setting and participants: This study linked 2019 and 2021 Medicare claims data. We included community-dwelling Medicare fee-for-service beneficiaries with Alzheimer's disease and related dementias who had at least 1 tele-MH visit in 2021.

Methods: The outcome variable was whether an individual had tele-MH visits with new providers in 2021, compared with providers they had in 2019, measured by comparing the list of providers they had visits with using Medicare outpatient claims data. The main variables of interest were race, ethnicity, Medicare-Medicaid dual eligibility, and rurality, measured using the Medicare Beneficiary Summary File. Logistic regression models, with zip code-level random effects, were estimated while accounting for individual- and community-level characteristics.

Results: The analytical sample included 99,329 individuals, of whom 53.6% had MH care with new providers via tele-MH services in 2021. After accounting for individual- and community-level characteristics, Black individuals (odds ratio [OR], 1.158; 95% CI, 1.096-1.222; P < .01), Medicare-Medicaid dual-eligibles (OR, 1.066; 95% CI, 1.027-1.105; P < .01), and rural residents (1.215; 95% CI, 1.125-1.312; P < .01) were more likely to have tele-MH visits with new providers compared with their White, nondual-eligible, and metropolitan counterparts, respectively.

Conclusions and implications: Telemedicine may improve MH care access for underserved populations by facilitating connections with new MH providers.

Objectives: Throughout the COVID-19 pandemic, public debate arose regarding the proportionality of infection prevention and control (IPC) measures in nursing homes (NHs), as these measures negatively impacted residents' well-being. To be better prepared for future outbreaks and pandemics, we need a deeper understanding of how NHs manage COVID-19 or influenza outbreaks, and which considerations are being made to balance IPC and well-being.

Design: Mixed-methods study.

Setting and participants: Fourteen Dutch NH organizations (176 NH locations) where COVID-19 or influenza outbreaks occurred during winter 2022-2023 were included.

Methods: We monitored the progression and management of 24 outbreaks by administering weekly questionnaires. Heterogeneous sampling was used to select 7 outbreaks for extensive monitoring, including epidemiologic data collection on the resident level and outbreak management evaluation through qualitative interviews (n = 7). Quantitative data were used for descriptive analysis (all outbreaks) and the generation of epidemiologic curves (extensively monitored outbreaks). Qualitative interview data were used to deepen our understanding of the considerations and adjustments made to IPC strategies by NH staff.

Results: We observed differences in IPC measures taken between NH organizations, but also within NH organizations, as IPC protocols were often customized to fit specific units, residents, or situations during outbreaks. Staff consistently considered the impact of IPC measures on residents against their beliefs about the effectiveness of measures, which occasionally led them to deviate from their IPC strategy in favor of residents' well-being.

Conclusion and implications: The current study provides an understanding of how COVID-19 and influenza outbreaks were managed, how NH staff considered the impact and effectiveness of measures, and consequently, how IPC strategies were gradually adjusted during outbreaks. Acknowledging that although the majority of NH staff consistently recognize the need to tailor IPC measures, they inconsistently apply such customization in practice, which may help NH organizations better prepare for future outbreaks.