JMIR Aging最新文献

Background: Intraoperative hypotension (IOH) is an important risk factor for major adverse cardiac events (MACE) in patients undergoing noncardiac surgery. However, the IOH threshold in older adult patients remains controversial.

Objective: This study aimed to explore an appropriate IOH threshold in older adult patients to decrease the risk of MACE.

Methods: This study involved older adult patients undergoing noncardiac surgery (age ≥65 y) from January 2012 to August 2019 in the Chinese People's Liberation Army General Hospital (PLAGH; 35,262 patients) and Shanghai Changhai Hospital from January 2024 to December 2024 (13,418 patients). Univariate moving-average plots and multivariate restricted cubic splines were used to determine the IOH thresholds associated with an increased risk of MACE. The relationship between the IOH threshold and MACE was assessed using univariate and multivariate logistic regression analyses by 3 different hypotension exposure forms (duration, area, and time-weighted average mean arterial pressure [MAP]).

Results: Out of 35,262 patients, 874 developed MACE in PLAGH, and 296 of 13,418 patients developed MACE in Changhai Hospital. In PLAGH, MAP below an absolute threshold of 70 mm Hg was associated with MACE. When the IOH absolute threshold was 70 mm Hg, the risk of MACE demonstrated a "dose-increasing" effect with changes in IOH exposure, and the risk of MACE was significantly increased when the duration lasted >15 minutes (odds ratio 1.51, 95% CI 1.22-1.88; P<.001). The stratified analysis showed that in patients younger than 80 years, when intraoperative MAP dropped below 70 mm Hg for more than 15 minutes, the odds ratio was 1.38 (95% CI 0.86-2.28), P<.01. In Changhai hospital, intraoperative MAP <70 mm Hg was also significantly associated with MACE. Furthermore, IOH lasting longer than 15 minutes substantially increased the risk of MACE.

Conclusions: For older adult patients undergoing noncardiac surgery, intraoperative MAP should be kept above 70 mm Hg to reduce the risk of postoperative MACE.

Background: With a global aging population, technology has been proposed as a solution to address the growing demand for services in the in-home aged care sector. Despite the potential of technology, there are difficulties when implementing technology into routine care delivery. There is a lack of evidence regarding the specific factors affecting technology use in the in-home aged care setting from the perspective of the direct care workforce.

Objective: This study aimed to understand in-home aged care staff members' views of (1) the digital enablement potential of direct in-home care tasks, (2) benefits and drawbacks of technology use, and (3) enablers and barriers for technology use in Australian in-home aged care.

Methods: An explanatory sequential mixed methods research design was used, with a cross-sectional survey and semistructured staff interviews. Participants were recruited from in-home aged care staff members working at a national Australian in-home health and aged care organization.

Results: In total, 226 participants completed the survey, and 18 participants completed the interviews. Overall, participants felt that many care tasks within in-home aged care could be digitally enabled, with more than half (56%) of the common direct care tasks identified as being likely to be digitally enabled. Participants also discussed a range of quality of care-, staff-, and organization-related benefits and drawbacks in the use of technology. Finally, participants agreed that most of the researcher-proposed enablers and barriers were important, while suggesting additional enablers and barriers such as client preferences regarding technology use and poor data connectivity.

Conclusions: This study provides insight into staff members' views regarding the use of technology to deliver in-home aged care services. The results could help inform technology developers and in-home aged care providers, providing key information to guide technology implementation into care delivery. Further research is required to ensure that appropriate strategies are available to ensure successful implementation of technology into in-home aged care.

Background: Neuroimaging is crucial in the diagnosis of Alzheimer disease (AD). In recent years, artificial intelligence (AI)-based neuroimaging technology has rapidly developed, providing new methods for accurate diagnosis of AD, but its performance differences still need to be systematically evaluated.

Objective: This study aims to conduct a systematic review and meta-analysis comparing the diagnostic performance of AI-assisted fluorine-18 fluorodeoxyglucose positron emission tomography (18F-FDG PET) and structural magnetic resonance imaging (sMRI) for AD.

Methods: Databases including Web of Science, PubMed, and Embase were searched from inception to January 2025 to identify original studies that developed or validated AI models for AD diagnosis using 18F-FDG PET or sMRI. Methodological quality was assessed using the TRIPOD-AI (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis-Artificial Intelligence) checklist. A bivariate mixed-effects model was employed to calculate pooled sensitivity, specificity, and summary receiver operating characteristic curve area (SROC-AUC).

Results: A total of 38 studies were included, with 28 moderate-to-high-quality studies analyzed. Pooled SROC-AUC values were 0.94 (95% CI 0.92-0.96) for sMRI and 0.96 (95% CI 0.94-0.98) for 18F-FDG PET, demonstrating statistically significant intermodal differences (P=.02). Subgroup analyses revealed that for machine learning, pooled SROC-AUCs were 0.89 (95% CI 0.86-0.92) for sMRI and 0.95 (95% CI 0.92-0.96) for 18F-FDG PET, while for deep learning, these values were 0.96 (95% CI 0.94-0.97) and 0.97 (95% CI 0.96-0.99), respectively. Meta-regression identified heterogeneity arising from study quality stratification, algorithm types, and validation strategies.

Conclusions: Both AI-assisted 18F-FDG PET and sMRI exhibit high diagnostic accuracy in AD, with 18F-FDG PET demonstrating superior overall diagnostic performance compared to sMRI.

Background: Vascular mild cognitive impairment (VMCI) is a significant global health concern, particularly in Asia. The visual cognitive assessment test (VCAT) has shown promise as a language-neutral screening tool for cognitive impairment.

Objective: This study aims to assess the effectiveness of the VCAT in detecting VMCI and compare its diagnostic performance with the widely used and validated Montreal Cognitive Assessment (MoCA).

Methods: Cross-sectional data from 524 community-dwelling participants were analyzed from the BIOCIS (Biomarkers and Cognition Study, Singapore) and classified into cognitively unimpaired, non-VMCI, and VMCI groups. The participants underwent neuropsychological assessments and 3-T magnetic resonance imaging. The random forest technique and multivariable logistic regression were applied to assess the discriminative properties of the tests.

Results: Participants with VMCI exhibited significantly lower performance across various neuropsychological tests (P<.001) and higher rates of vascular risk factors (P<.001). At a cutoff of 27, the VCAT achieved near-perfect accuracy in discriminating the VMCI group from the cognitively unimpaired group (area under the receiver operating characteristic curve=1; sensitivity=1; specificity=0.991). For differentiating the VMCI group from the non-VMCI group, both the VCAT and the MoCA showed optimal performance at a cutoff of 25 (area under the receiver operating characteristic curve=1.00; sensitivity=1.00; specificity=1.00).

Conclusions: The VCAT could be a valuable tool for detecting VMCI, particularly in diverse, multilingual populations. Its comparable or even superior performance to the MoCA, combined with its language-neutral design, positions the VCAT as a strong addition to cognitive assessment toolkits for VMCI. However, the complex nature of cognitive processing in VMCI suggests that a multifaceted approach that integrates both visual and verbal assessments may ultimately offer the most comprehensive evaluation.

International registered report identifier (irrid): RR2-10.14283/jpad.2024.89.

Background: Disability is a global public health challenge, with its prevalence increasing, particularly among older adults, and it exerts a profound impact on both health outcomes and mortality rates.

Objective: This study investigates the associations between age at disability onset, severity at disability onset, and all-cause mortality in community-dwelling adults.

Methods: We analyzed data from waves 10 to 16 (2010-2023) of the Health and Retirement Study, a nationally representative longitudinal survey of US adults aged ≥51 years. Participants without disabilities in activities of daily living (ADLs) or instrumental activities of daily living (IADLs) from the Health and Retirement Study were followed biennially until December 31, 2023. During the follow-up period, 4500 participants developed ADL disability and 4260 developed IADL disability. For each case participant, a control participant matched for age (+1 to -1 y) and sex was randomly selected. Multivariable Cox proportional hazards models were used to assess hazard ratios (HRs) for all-cause mortality among participants with new-onset disabilities, stratified by age groups and severity at disability onset.

Results: Over a median follow-up duration of 8.58 years, 1709 (37.98%) deaths occurred in the ADL group and 1832 (43%) deaths occurred in the IADL group. Individuals who developed ADL disability before the age of 55 years exhibited the highest all-cause mortality risk compared to matched controls (HR 3.12, 95% CI 1.85-5.26), which further increased with severe disability (HR 4.07, 95% CI 2.03-8.19). The mortality risk was inversely associated with age at onset. A parallel trend was identified in the IADL cohort. Notably, men demonstrated a significantly elevated mortality risk compared to women, emphasizing the need for gender-specific interventions.

Conclusions: Early and severe disability onset significantly increases mortality risk, with men experiencing a disproportionately higher risk. Preventive strategies aimed at addressing early-onset and severe disability, with consideration of gender differences, are essential for improving long-term outcomes in affected populations.

Background: As the global population continues to age, the prevalence of sarcopenia is gradually increasing, and the loss of skeletal muscle mass is one of the manifestations of sarcopenia. Low calf circumference (CC) is often used as a predictor of poor skeletal muscle mass or sarcopenia. Older adults usually have a combination of multiple chronic diseases. There is a lack of evidence to explore the risk factors for low CC with multimorbidity in Chinese, community-dwelling, older adults.

Objective: This study aimed to explore the risk factors and potential categories in older adult patients with low CC and multimorbidity from an individual-centered perspective.

Methods: We selected 15,874 participants from the Chinese Longitudinal Healthy Longevity Survey in 2018 and screened for low CC in older adult patients. The individual-centered latent class analysis was used to classify potential multimorbidity groups. Multiple logistic regression was used to explore the risk factors associated with low CC and multimorbidity by applying the elastic net to screen for reliable risk variables.

Results: A total of 7956 older individuals were eligible for the study, of whom 3960 (49.8%) were aged >90 years and 2166 (27.2%) had multimorbidity with low CC. The prevalence of multimorbidity increases between the ages of 65 and 89 years. However, the majority of older adults remain in reasonably good health beyond the age of 90 years. Five multimorbidity groups were identified by latent class analysis: multisystem morbidity diseases (78/2166, 3.6%), arthritis-rheumatism or rheumatoid diseases (400/2166, 18.47%), diabetes-hypertension diseases (330/2166, 15.23%), respiratory-heart diseases (347/2166, 16.02%), and cardiovascular diseases (1011/2166, 46.68%). Through 12 variables screened by the elastic net, multiple logistic regression showed different impacts on multimorbidity groups, including demographic background, behavioral characteristics, and physical and mental health factors. In particular, older patients who self-report poor health and live in urban areas need more attention.

Conclusions: The results revealed that low CC is a common phenomenon among community-dwelling older adults, and a substantial proportion also present with multimorbidity. In the older adult population with low CC, the proportion of multimorbidity does not simply increase with age. Multimorbidity in low CC has been identified in 5 potential groups. Different groups have distinctive risk factors. Public health authorities should pay attention to low CC in older adult patients with multimorbidity and carry out targeted interventions, thereby enhancing health outcomes.

Background: The digital divide has loomed as a global public issue in recent years. However, evidence is limited regarding whether the digital divide is associated with health-related quality of life (HRQOL) and whether digital back-feeding would buffer this association.

Objective: This study aims to explore the role of digital back-feeding in the relationship between the digital divide and HRQOL among older men and women living in rural China.

Methods: We used data from wave 3 of the Shandong Rural Elderly Health Cohort, conducted in 2022. A total of 3242 (n=1946, 60.02% women) rural older adults were included in the analysis. Moderating effect analysis was performed using Tobit regression models and margins plots.

Results: A total of 71.01% (2302/3242) of the participants reported experiencing digital divide. Participants experiencing digital divide were significantly associated with lower HRQOL as measured by EQ-5D-5L scores (β=-0.020; P<.001). We found that digital back-feeding buffered the relationship between digital divide and HRQOL (β=0.024; P=.02). Furthermore, gender-stratified analyses revealed divergent moderation patterns; a significant buffering role was observed in women (β=0.031; P=.02), whereas no substantially significant moderating role emerged in men.

Conclusions: Our study established a significant inverse association between the digital divide and HRQOL among rural adults. Digital back-feeding emerged as a measurable protective buffer mitigating this adverse relationship. Furthermore, this buffering effect was only observed among older women. Policy implications underscore the necessity of gender-tailored digital inclusion strategies, particularly advocating for technology-proficient adult offsprings to prioritize digital engagement with their mothers in digitally marginalized rural communities.