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Background: Early identification of different stages of cognitive impairment is important to provide available intervention and timely care for the elderly. Objective: This study aimed to examine the ability of the artificial intelligence (AI) technology to distinguish participants with mild cognitive impairment (MCI) from those with mild to moderate dementia based on automated video analysis. Methods: A total of 95 participants were recruited (MCI, 41; mild to moderate dementia, 54). The videos were captured during the Short Portable Mental Status Questionnaire process; the visual and aural features were extracted using these videos. Deep learning models were subsequently constructed for the binary differentiation of MCI and mild to moderate dementia. Correlation analysis of the predicted Mini-Mental State Examination, Cognitive Abilities Screening Instrument scores, and ground truth was also performed. Results: Deep learning models combining both the visual and aural features discriminated MCI from mild to moderate dementia with an area under the curve (AUC) of 77.0% and accuracy of 76.0%. The AUC and accuracy increased to 93.0% and 88.0%, respectively, when depression and anxiety were excluded. Significant moderate correlations were observed between the predicted cognitive function and ground truth, and the correlation was strong excluding depression and anxiety. Interestingly, female, but not male, exhibited a correlation. Conclusion: The study showed that video-based deep learning models can differentiate participants with MCI from those with mild to moderate dementia and can predict cognitive function. This approach may offer a cost-effective and easily applicable method for early detection of cognitive impairment. [ABSTRACT FROM AUTHOR]

Aims: While certain drug‐use indicators are known to be associated with clinical outcomes, the relationship is unclear for some highly prevalent conditions in in patients aged ≥65 years. We examine correlations between 3 drug‐use indicators and postdischarge healthcare services use by older patients according to the presence of dementia, advanced age and frailty. Methods: This retrospective cohort study analysed data collected from hospital electronic health records between April and December 2017. Potentially inappropriate medications (PIMs) and anticholinergic burden were assessed using the 2015 Beers Criteria and anticholinergic cognitive burden scale (ACBS) score. Minor and major polypharmacy were defined as the use of 5–9 and ≥10 drugs, respectively. Outcomes were set as emergency room revisits and readmissions at 1, 3 and 6 months postdischarge. The correlation between drug‐use indicators and outcomes was analysed by multivariable logistic regression. Results: The final cohort included 3061 patients for the analysis, and 2930, 2671 and 2560 patients were followed up to 1, 3 and 6 months after discharge. After controlling for confounders, all 3 drug‐use indicators were significantly associated with readmission and emergency room revisits except for the relationship between PIMs and readmission within 6 months. These associations were significantly observed among patients without dementia, aged >80 years and with frailty. Conclusion: PIMs, polypharmacy and anticholinergic burden are common at discharge and correlate with future use of healthcare services. In older patients, the absence of dementia, advanced age and frailty should be given extra consideration with regard to medication safety. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the roles of preoperative anemia and intraoperative blood transfusion in the development of postoperative delirium among older patients undergoing elective orthopedic surgery.Methods: This prospective cohort study recruited subjects aged 60 years old and above who were admitted for elective orthopedic surgery in a tertiary medical center during April 2011 to December 2013. Demographic data (age, gender, body mass index [BMI], and educational level), surgery-related factors (American Society of Anesthesiology [ASA] class, type of anesthesia and surgery, and intraoperative blood transfusion), results of geriatric assessment (hearing/visual impairment, cognition, depressive mood, comorbidity, malnutrition, polypharmacy, activities of daily living [ADL], and instrumental activities of daily living [IADL]), laboratory data, length of hospital stay, and the development of postoperative delirium were collected for analysis.Results: Overall, 461 patients (mean age: 73.5 ± 7.5 years, 42.1% males) were enrolled for study, and 37 (8.0%) of them developed postoperative delirium. We categorized all subjects into four groups based on anemia on admission and blood transfusion during operation or not. Multivariate logistic regression showed that subjects with anemia on admission and received intraoperative blood transfusion were at higher risk of developing postoperative delirium (adjusted odds ratio 3.090; 95% confidence interval [CI], 1.070-8.926) and those without anemia on admission but received intraoperative blood transfusion were at marginal risk (adjusted odds ratio 2.906; 95% CI, 0.912-9.259) after adjustment for covariates.Conclusions: Anemic older patients receiving intraoperative blood transfusion during operation were at the greatest risk for postoperative delirium when they underwent elective orthopedic surgery. Further intervention study is needed to reduce the risk of postoperative delirium for these patients. [ABSTRACT FROM AUTHOR]

Aim Slow gait speed has been associated with mortality, poor physical function and disability in older people. Our aim was to evaluate the association between slow gait speed and rapid cognitive decline among oldest-old men in Taiwan. Methods We carried out a longitudinal cohort study in a veterans' retirement community, and enrolled 249 male residents aged 80 years and older. Slow gait speed was defined as <1 m/s, and rapid cognitive decline was defined as a Mini-Mental State Examination (MMSE) decline of ≥3 points over 1 year. Body mass index, Charlson's Comorbidity Index, handgrip strength, gait speed and Mini-Mental State Examination datasets were collected, and a logistic regression model was built to evaluate the association between fast cognitive decline and slow gait speed. Results In all, 249 residents (mean age 86.4 ± 4.01 years) were recruited, including 58 (23.3%) with rapid cognitive decline. Univariate analysis showed that slow gait speed could predict rapid cognitive decline (OR 4.10, 95% CI 1.20-14.00, P = 0.024). After adjusting for age, Charlson's Comorbidity Index, polypharmacy, psychiatric drug usage, cigarette smoking experience, baseline cognitive function, depressive mood, handgrip strength, nutritional status and history of fall, slow gait speed was still independently associated with rapid cognitive decline (adjusted OR 4.58, 95% CI 1.22-17.2, P = 0.024). Conclusions Slow gait speed was thus an independent predictor of rapid cognitive decline in oldest-old men in a veterans' retirement community in Taiwan. Geriatr Gerontol Int 2017: 17 (Suppl. 1): 14-19. [ABSTRACT FROM AUTHOR]

As populations age, sarcopenia becomes a major health problem among adults aged 65 years and older. However, little information is available about the relationship between sarcopenia and brain structure abnormalities. The objective of this study was to investigate associations between sarcopenia and brain atrophy in older adults and relationships with regional brain areas. This prospective cohort study recruited 102 retirement community residents aged 65 years and older. All participants underwent gait speed measurement, handgrip strength measurement and muscle mass measurement by dual X-ray absorptiometry. Diagnosis of sarcopenia was made according to criteria of the Asian Working Group for Sarcopenia (AWGSOP). All patients underwent magnetic resonance imaging (MRI), and images were analysed for global cortical atrophy (GCA) (range 0–3), parietal atrophy (PA) (range 0–3) and medial temporal atrophy (MTA) (range 0–4). Among 102 older adult participants (81.4 ± 8.2 years), 47 (46.1%) were diagnosed with sarcopenia according to AWGSOP criteria. The sarcopenia group had more moderate to severe PA (Grade 2: 19.1% vs. 5.5%; grade 3:6.4% vs. 0%, P = 0.016) and GCA (Grade 2: 40.4% vs. 18.2%, P = 0.003) and a trend of more moderate to severe MTA (Grade 2: 46.8% vs. 30.9%; grade 3: 8.5% vs. 1.8%, P = 0.098) than the non-sarcopenia group. In univariate logistic regression, sarcopenia was significantly associated with PA (OR 5.94, 95% CI 1.56–22.60, P = 0.009), GCA (OR 3.05, 95% CI 1.24–7.51, P = 0.015), and MTA (OR 2.55, 95% CI 1.14–5.69, P = 0.023). In multivariable logistic regression analysis, sarcopenia was an independent risk factor for PA (adjusted OR 6.90, 95% CI 1.30–36.47, P = 0.023). After adjusting for all covariates, only age had a significant relationship with GCA (Adjusted OR 1.09, 95% CI 1.00–1.19, P = 0.044) and MTA (Adjusted OR 1.09, 95% CI 1.01–1.17, P = 0.022). This is the first study to explore associations between sarcopenia and global as well as regional brain atrophy in older adults. The sarcopenia group had higher rates of moderate to severe PA, GCA and MTA than the non-sarcopenia group. PA was significantly associated with sarcopenia in older adults. Further longitudinal studies are needed to address the mechanism and pathogenesis of brain atrophy and sarcopenia. • Sarcopenia was common in old adults living in a retirement community (46.1%). • Sarcopenia had moderate-severe global cortical, parietal and medial temporal atrophy. • Sarcopenia is significantly associated with parietal atrophy in older adults. • Age had a significant relationship with global cortical and medial temporal atrophy. [ABSTRACT FROM AUTHOR]

Introduction: Geriatric syndrome (GS) increases risk of disability and mortality in older adults. Sarcopenia is a predominant illness of GS and accelerate its progression. This study aimed to investigate associations between mortality, emergency department (ED) re-visits and GS-related illnesses among older adults who visited the ED., Method: This retrospective observational study enrolled elderly patients who visited the ED in our hospital between January 2018 and October 2020. Patients were evaluated for potential sarcopenia, which was defined by both low handgrip strength and calf circumference. Follow-up was at least 6 months. Data of age, gender, mortality, ED re-visits, and GS-related illnesses were collected and analyzed for associations., Results: A total of 273 older adults aged 74 years or older were included, of whom 194 were diagnosed with possible sarcopenia. Older adults with possible sarcopenia also had significantly lower body mass index (BMI); a higher proportion needed assistance with daily activities; more had malnutrition, frailty, and history of falls (all p < 0.001) and acute decline in activities of daily living ( p = 0.027). Multivariate analysis showed that possible sarcopenia [adjusted hazard ratio, aHR): 9.89, 95% confidence interval (CI): 1.17-83.81, p = 0.036], living in residential institutions (aHR: 2.85, 95% CI: 1.08-7.50, p = 0.034), and frailty (aHR: 7.30, 95% CI: 1.20-44.62, p = 0.031) were associated with mortality. Aged over 85 years (adjusted odds ratio: 2.44, 95% CI: 1.25-4.80, p = 0.02) was associated with ED re-visits., Conclusion: Sarcopenia is associated with mortality among older adults who visit ED. Initial screening for sarcopenia and relevant risk factors among older adults in the ED may help with early intervention for those at high-risk and may improve their prognosis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Liao, Yen, Lin, Huang and Chang.)

The impact of dynapenia on the complexity of care for residents of long-term care facilities (LTCF) remains unclear. The present study evaluated associations between dynapenia, care problems and care complexity in 504 residents of Veterans Care Homes (VCHs) in Taiwan. Subjects with dynapenia, defined as low muscle strength (handgrip strength <26 kg), were older adults with lower body mass index (BMI), slow gait speed, and higher numbers of Resident Assessment Protocol (RAP) triggers. After adjusting for age, education, BMI, and Charlson's comorbidity index (CCI), only age, education, BMI and gait speed were independently associated with higher numbers of RAP triggers, but not dynapenia or handgrip strength (kg). Dividing subjects into groups based on quartiles of gait speed, those with gait speed ≤0.803 m/s were significantly associated with higher complexity of care needs (defined as ≥4 RAP triggers) compared to the reference group (gait speed >1 m/s). Significantly slow gait speed was associated with RAP triggers, including cognitive loss, poor communication ability, rehabilitation needs, urinary incontinence, depressed mood, falls, pressure ulcers, and use of psychotropic drugs. In conclusion, slow gait speed rather than dynapenia is a simple indicator for higher complexity of care needs of older male LTCF residents.

Secreted factors play a central role in normal and pathological processes in every tissue in the body. The brain is composed of a highly complex milieu of different cell types and few methods exist that can identify which individual cells in a complex mixture are secreting specific analytes. By identifying which cells are responsible, we can better understand neural physiology and pathophysiology, more readily identify the underlying pathways responsible for analyte production, and ultimately use this information to guide the development of novel therapeutic strategies that target the cell types of relevance. We present here a method for detecting analytes secreted from single human induced pluripotent stem cell (iPSC)-derived neural cells and have applied the method to measure amyloid β (Aβ) and soluble amyloid precursor protein-alpha (sAPPα), analytes central to Alzheimer's disease pathogenesis. Through these studies, we have uncovered the dynamic range of secretion profiles of these analytes from single iPSC-derived neuronal and glial cells and have molecularly characterized subpopulations of these cells through immunostaining and gene expression analyses. In examining Aβ and sAPPα secretion from single cells, we were able to identify previously unappreciated complexities in the biology of APP cleavage that could not otherwise have been found by studying averaged responses over pools of cells. This technique can be readily adapted to the detection of other analytes secreted by neural cells, which would have the potential to open new perspectives into human CNS development and dysfunction., Significance Statement: We have established a technology that, for the first time, detects secreted analytes from single human neurons and astrocytes. We examine secretion of the Alzheimer's disease-relevant factors amyloid β (Aβ) and soluble amyloid precursor protein-alpha (sAPPα) and present novel findings that could not have been observed without a single-cell analytical platform. First, we identify a previously unappreciated subpopulation that secretes high levels of Aβ in the absence of detectable sAPPα. Further, we show that multiple cell types secrete high levels of Aβ and sAPPα, but cells expressing GABAergic neuronal markers are overrepresented. Finally, we show that astrocytes are competent to secrete high levels of Aβ and therefore may be a significant contributor to Aβ accumulation in the brain., (Copyright © 2016 the authors 0270-6474/16/361730-17$15.00/0.)

The progressive accumulation of beta-amyloid (Abeta) in senile plaques and in the cerebral vasculature is the hallmark of Alzheimer's disease and related disorders. Degradation of Abeta by specific proteolytic enzymes is an important process that regulates its levels in brain. Matrix metalloproteinase 2 (MMP2) was shown to be expressed in reactive astrocytes surrounding amyloid plaques and may contribute to Abeta degradation. Membrane type 1 (MT1) MMP is the physiological activator for the zymogen pro-MMP2. Here, we show that, in addition to MMP2, its activator MT1-MMP is also expressed in reactive astrocytes in regions with amyloid deposits in transgenic mice. Using a Cos-1 cell expression system, we demonstrated that MT1-MMP can degrade exogenous Abeta40 and Abeta42. A purified soluble form of MT1-MMP degraded both soluble and fibrillar Abeta peptides in a time-dependent manner, yielding specific degradation products. Mass spectrometry analysis identified multiple MT1-MMP cleavage sites on soluble Abeta40 and Abeta42. MT1-MMP-mediated Abeta degradation was inhibited with the general MMP inhibitor GM6001 or the specific MT1-MMP inhibitor tissue inhibitor of metalloproteinases 2. Furthermore, in situ experiments showed that purified MT1-MMP degraded parenchymal fibrillar amyloid plaques that form in the brains of Abeta precursor protein transgenic mice. Together, these findings indicate that MT1-MMP possesses Abeta degrading activity in vitro.