Effect of Home-Based Transcranial Direct Current Stimulation on Cognitive Function in Patients with Mild Cognitive Impairment: A Two-Week Intervention.

PURPOSE: Repeated transcranial direct current stimulation (tDCS) is expected to have the potential to improve cognitive function in patients with mild cognitive impairment (MCI). We aimed to evaluate the efficacy and safety of at-home tDCS for elderly patients with MCI. MATERIALS AND METHODS: Patients aged 60-80 years, who maintained normal daily living but reported objective memory impairments, were enrolled. Active or sham stimulations were applied to the dorsal frontal cortex (left: anode; right: cathode) at home for 2 weeks. Changes in cognitive function were assessed using visual recognition tasks and the Mini-Mental State Exam (MMSE), and safety and efficacy were assessed using self-reports and a remote monitoring application. RESULTS: Of the 19 participants enrolled, 12 participants were included in the efficacy analysis. Response times and MMSE scores significantly improved after active stimulation compared to the sham stimulation; however, there were no significant differences in the proportion of correct responses. The mean compliance of the efficacy group was 97.5%±4.1%. Three participants experienced burns, but no permanent sequelae remained. CONCLUSION: This preliminary result suggests that home-based tDCS may be a promising treatment option for MCI patients; however, it requires more attention and technological development to address safety concerns. CLINICAL TRIAL REGISTRATION: Clinical Research Information Service (CRIS), KCT0002721.

Metabolic phenotyping with computed tomography deep learning for metabolic syndrome, osteoporosis and sarcopenia predicts mortality in adults.

BACKGROUND: Computed tomography (CT) body compositions reflect age-related metabolic derangements. We aimed to develop a multi-outcome deep learning model using CT multi-level body composition parameters to detect metabolic syndrome (MS), osteoporosis and sarcopenia by identifying metabolic clusters simultaneously. We also investigated the prognostic value of metabolic phenotyping by CT model for long-term mortality. METHODS: The derivation set (n = 516; 75% train set, 25% internal test set) was constructed using age- and sex-stratified random sampling from two community-based cohorts. Data from participants in the individual health assessment programme (n = 380) were used as the external test set 1. Semi-automatic quantification of body compositions at multiple levels of abdominal CT scans was performed to train a multi-layer perceptron (MLP)-based multi-label classification model. External test set 2 to test the prognostic value of the model output for mortality was built using data from individuals who underwent abdominal CT in a tertiary-level institution (n = 10 141). RESULTS: The mean ages of the derivation and external sets were 62.8 and 59.7 years, respectively, without difference in sex distribution (women 50%) or body mass index (BMI; 23.9 kg/m2). Skeletal muscle density (SMD) and bone density (BD) showed a more linear decrement across age than skeletal muscle area. Alternatively, an increase in visceral fat area (VFA) was observed in both men and women. Hierarchical clustering based on multi-level CT body composition parameters revealed three distinctive phenotype clusters: normal, MS and osteosarcopenia clusters. The L3 CT-parameter-based model, with or without clinical variables (age, sex and BMI), outperformed clinical model predictions of all outcomes (area under the receiver operating characteristic curve: MS, 0.76 vs. 0.55; osteoporosis, 0.90 vs. 0.79; sarcopenia, 0.85 vs. 0.81 in external test set 1; P < 0.05 for all). VFA contributed the most to the MS predictions, whereas SMD, BD and subcutaneous fat area were features of high importance for detecting osteoporosis and sarcopenia. In external test set 2 (mean age 63.5 years, women 79%; median follow-up 4.9 years), a total of 907 individuals (8.9%) died during follow-up. Among model-predicted metabolic phenotypes, sarcopenia alone (adjusted hazard ratio [aHR] 1.55), MS + sarcopenia (aHR 1.65), osteoporosis + sarcopenia (aHR 1.83) and all three combined (aHR 1.87) remained robust predictors of mortality after adjustment for age, sex and comorbidities. CONCLUSIONS: A CT body composition-based MLP model detected MS, osteoporosis and sarcopenia simultaneously in community-dwelling and hospitalized adults. Metabolic phenotypes predicted by the CT MLP model were associated with long-term mortality, independent of covariates.

Influenza epidemiology and treatment in people with a visual disability: A retrospective cohort study.

BACKGROUND: Visual disabilities (VD) are expected to rise with an aging population. Persons with VD experience a higher prevalence of chronic and acute diseases. Despite the significance of influenza to this population, there is limited data comparing influenza care disparities between those with VD and those without. OBJECTIVE: The study aimed to determine the influenza burden and associated healthcare utilization in individuals with VD compared to those without disabilities. METHODS: A retrospective cohort study was conducted using the Korean National Health Information Database, encompassing three influenza seasons (2011-2012 to 2013-2014). The influenza incidence and incidence rate ratio (IRR) was calculated. Adjusted IRRs were calculated using a zero-inflated Poisson model. We assessed the risk of admissions and 30-day post-influenza mortality, employing logistic regression or survival analysis. RESULTS: A total of 504,374 patients (252,964 patients with VD and 251,410 controls) were followed for 1,471,480 person-years. The influenza incidence was higher in the VD cohort than in the control (8.8 vs. 7.8 cases per 1000 person-years). VD cohort had a higher influenza IRR (adjusted IRR 1·13, 95% confidence interval [CI] 1·02-1·25). Severe VD exhibited higher hospitalization risk (adjusted odds ratio [OR] 1·29, 95% CI 1·10-1·20) and increased medical costs. Severe VD was a significant risk factor for mortality (adjusted Hazard Ratio 1·89, 95% CI 1·04-3·45). CONCLUSIONS: People with VD have a higher influenza incidence, while their outcomes are comparable to those without. Nevertheless, severe VD significantly contributes more to hospitalization, mortality, and medical costs than controls.

Digital Health Technology Use Among Older Adults: Exploring the Impact of Frailty on Utilization, Purpose, and Satisfaction in Korea.

BACKGROUND: The importance of digital technology is increasing among older adults. In this study, the digital health technology utilization status, purpose, and satisfaction of older adults were investigated according to frailty. METHODS: A face-to-face survey was conducted among adults aged 65 years or older. Frailty was defined using the Korean version of the fatigue, resistance, ambulation, illnesses, and loss of weight scale. RESULTS: A total of 505 participants completed the survey, with 153 (30.3%) identified as pre-frail or frail and 352 (69.7%) as healthy. All respondents used smartphones; 440 (87.1%) were application users, and 290 (57.4%) were healthcare application users. Wearable devices were used by only 36 patients (7.1%). Pre-frail or frail respondents used social media more frequently than healthy respondents (19.4% vs. 7.4%, P < 0.001). Among the respondents, 319 (63.2%) were not able to install or delete the application themselves, and 277 (54.9%) stated that the application was recommended by their children (or partner). Pre-frail and frail respondents used more healthcare applications to obtain health information (P = 0.002) and were less satisfied with wearable devices (P = 0.02). CONCLUSION: The usage rate of digital devices, including mobile phones among older adults in Korea is high, whereas that of wearable devices is low. There was a notable difference in the services used by pre-frail and frail respondents compared to healthy respondents. Therefore, when developing digital devices for pre-frail and frail older adults, it is crucial to incorporate customized services that meet their unique needs, particularly those services that they frequently use.

Jump Power Predicts Fracture Risk in Older Adults Independent of Sarcopenia and FRAX.

Low countermovement jump power is associated with prevalent fracture, osteoporosis, and sarcopenia in older adults. However, whether jump power predicts incident fracture risk remains uninvestigated. Data of 1366 older adults in a prospective community cohort were analyzed. Jump power was measured using a computerized ground force plate system. Fracture events were ascertained by follow-up interview and linkage to the national claim database (median follow-up 6.4 years). Participants were divided into normal and low jump power groups using a predetermined threshold (women <19.0 W/kg; men <23.8 W/kg; or unable to jump). Among the study participants (mean age 71.6 years, women 66.3%), low jump power was associated with a higher risk of fracture (hazard ratio [HR] = 2.16 versus normal jump power, p < 0.001), which remained robust (adjusted HR = 1.45, p = 0.035) after adjustment for fracture risk assessment tool (FRAX) major osteoporotic fracture (MOF) probability with bone mineral density (BMD) and Asian Working Group for Sarcopenia (AWGS) 2019 sarcopenia definition. In the AWGS no sarcopenia group, participants with low jump power had a significantly higher risk of fracture than those with normal jump power (12.5% versus 6.7%; HR = 1.93, p = 0.013), comparable to that of possible sarcopenia without low jump power (12.0%). Possible sarcopenia group with low jump power had a similar risk of fracture (19.3%) to sarcopenia group (20.8%). When the definition of sarcopenia was modified with jump power measurement (step-up approach: no sarcopenia to possible sarcopenia; possible sarcopenia to sarcopenia when low jump power present), jump power-modified sarcopenia improved sensitivity (18%-39.3%) to classify individuals who sustained MOF during follow-up to high risk compared with AWGS 2019 sarcopenia, while maintaining positive predictive value (22.3%-20.6%). In summary, jump power predicted fracture risk in community-dwelling older adults independently of sarcopenia and FRAX MOF probabilities, suggesting potential contribution of complex motor function measurement in fracture risk assessment. © 2023 American Society for Bone and Mineral Research (ASBMR).

The Effect of Cognitive Impairment on the Association Between Social Network Properties and Mortality Among Older Korean Adults.

OBJECTIVES: This study investigated the effect of cognitive impairment on the association between social network properties and mortality among older Korean adults. METHODS: This study used data from the Korean Social Life, Health, and Aging Project. It obtained 814 older adults' complete network maps across an entire village in 2011-2012. Participants' deaths until December 31, 2020 were confirmed by cause-of-death statistics. A Cox proportional hazards model was used to assess the risks of poor social network properties (low degree centrality, perceived loneliness, social non-participation, group-level segregation, and lack of support) on mortality according to cognitive impairment. RESULTS: In total, 675 participants (5510.4 person-years) were analyzed, excluding those with missing data and those whose deaths could not be verified. Along with cognitive impairment, all social network properties except loneliness were independently associated with mortality. When stratified by cognitive function, some variables indicating poor social relations had higher risks among older adults with cognitive impairment, with adjusted hazard ratios (HRs) of 2.12 (95% confidence interval [CI], 1.34 to 3.35) for social nonparticipation, 1.58 (95% CI, 0.94 to 2.65) for group-level segregation, and 3.44 (95% CI, 1.55 to 7.60) for lack of support. On the contrary, these effects were not observed among those with normal cognition, with adjusted HRs of 0.73 (95% CI, 0.31 to 1.71), 0.96 (95% CI, 0.42 to 2.21), and 0.95 (95% CI, 0.23 to 3.96), respectively. CONCLUSIONS: The effect of social network properties was more critical among the elderly with cognitive impairment. Older adults with poor cognitive function are particularly encouraged to participate in social activities to reduce the risk of mortality.

The prognostic value of comprehensive geriatric assessment on the management of older patients with small cell lung cancer.

BACKGROUND/AIMS: The prognostic value of a comprehensive geriatric assessment (CGA) for the management of older small cell lung cancer (SCLC) patients remains to be established. METHODS: A retrospective cohort enrolled 21 SCLC patients over 65 years from March 2018 to 2019 at the Yonsei Cancer Center. The CGA included the following instruments: frailty, body mass index, sarcopenia (circumference of arm and calf, Timed Up and Go test, grip strength), comorbidity, polypharmacy, activities of daily living (ADL), Instrumental ADL, nutrition, depression, and cognitive function. The correlations of oncological and geriatric variables with overall survival (OS) were determined. The log-rank test with Cox model and Kaplan-Meier method were used for the analysis. RESULTS: The median age was 75 years (range, 67 to 85). All patients had the Eastern Cooperative Oncology Group performance status 0-2. The median survival was 9.93 months (range, 1.53 to 36.30). Among CGA parameters, ADL and nutritional status had significant differences in OS in univariate analysis. In multivariate analysis, only nutritional status was independently associated with survival (hazard ratio, 0.17; 95% confidence interval, 0.05 to 0.57). Median OS for low nutritional status was 5.63 months and the normal nutrition group was 15.5 months (p = 0.004). CONCLUSION: Pre-treatment nutritional status measured by CGA appears to be a predictor of OS in older SCLC patients. However, for further generalization of the implication of CGA in SCLC, a larger scale study with prospective design is strongly needed.

Developing a Multimodal Monitoring System for Geriatric Depression: A Feasibility Study.

The Internet of Medical Things is promising for monitoring depression symptoms. Therefore, it is necessary to develop multimodal monitoring systems tailored for elderly individuals with high feasibility and usability for further research and practice. This study comprised two phases: (1) methodological development of the system; and (2) system validation to evaluate its feasibility. We developed a system that includes a smartphone for facial and verbal expressions, a smartwatch for activity and heart rate monitoring, and an ecological momentary assessment application. A sample of 21 older Koreans aged 65 years and more was recruited from a community center. The 4-week data were collected for each participant (n = 19) using self-report questionnaires, wearable devices, and interviews and were analyzed using mixed methods. The depressive group (n = 6) indicated lower user acceptance relative to the nondepressive group (n = 13). Both groups experienced positive emotions, had regular life patterns, increased their self-interest, and stated that a system could disturb their daily activities. However, they were interested in learning new technologies and actively monitored their mental health status. Our multimodal monitoring system shows potential as a feasible and useful measure for acquiring mental health information about geriatric depression.

Chest X-ray-based opportunistic screening of sarcopenia using deep learning.

BACKGROUND: Early detection and management of sarcopenia is of clinical importance. We aimed to develop a chest X-ray-based deep learning model to predict presence of sarcopenia. METHODS: Data of participants who visited osteoporosis clinic at Severance Hospital, Seoul, South Korea, between January 2020 and June 2021 were used as derivation cohort as split to train, validation and test set (65:15:20). A community-based older adults cohort (KURE) was used as external test set. Sarcopenia was defined based on Asian Working Group 2019 guideline. A deep learning model was trained to predict appendicular lean mass (ALM), handgrip strength (HGS) and chair rise test performance from chest X-ray images; then the machine learning model (SARC-CXR score) was built using the age, sex, body mass index and chest X-ray predicted muscle parameters along with estimation uncertainty values. RESULTS: Mean age of the derivation cohort (n = 926; women n = 700, 76%; sarcopenia n = 141, 15%) and the external test (n = 149; women n = 95, 64%; sarcopenia n = 18, 12%) cohort was 61.4 and 71.6 years, respectively. In the internal test set (a hold-out set, n = 189, from the derivation cohort) and the external test set (n = 149), the concordance correlation coefficient for ALM prediction was 0.80 and 0.76, with an average difference of 0.18 ± 2.71 and 0.21 ± 2.28, respectively. Gradient-weight class activation mapping for deep neural network models to predict ALM and HGS commonly showed highly weight pixel values at bilateral lung fields and part of the cardiac contour. SARC-CXR score showed good discriminatory performance for sarcopenia in both internal test set [area under the receiver-operating characteristics curve (AUROC) 0.813, area under the precision-recall curve (AUPRC) 0.380, sensitivity 0.844, specificity 0.739, F1-score 0.540] and external test set (AUROC 0.780, AUPRC 0.440, sensitivity 0.611, specificity 0.855, F1-score 0.458). Among SARC-CXR model features, predicted low ALM from chest X-ray was the most important predictor of sarcopenia based on SHapley Additive exPlanations values. Higher estimation uncertainty of HGS contributed to elevate the predicted risk of sarcopenia. In internal test set, SARC-CXR score showed better discriminatory performance than SARC-F score (AUROC 0.813 vs. 0.691, P = 0.029). CONCLUSIONS: Chest X-ray-based deep leaning model improved detection of sarcopenia, which merits further investigation.

Factors Related to Hospital Readmission of Frail Older Adults in Korea.

PURPOSE: Frail older adults have a higher risk of hospital readmission due to decline in physical, functional, and psychological health status. The impact of readmission on individuals, families, or the healthcare system is tremendously devastating. This study aimed to investigate factors associated with hospital readmission of frail older adults. MATERIALS AND METHODS: This was a retrospective descriptive study based on multi-professional health assessments found in electronic medical records of patients from a university-affiliated hospital in Seoul, Korea. The participants were 141 older adults who were admitted to the geriatric department with medical problems. Frailty, components of the comprehensive geriatric assessment including nutrition, physical functions, psychological and cognitive status, clinical data including length of hospital stay, and readmission within 30, 90, and 180 days were collected. Survival analysis was performed, and Cox proportional hazard regression model was used to investigate the risk factors for readmission. RESULTS: The statistically significant variables at each time point were slightly different. However, at most time points, disease-related problems (i.e., comorbidities and medications) and body functions (i.e., grip strength and physical activity) were included. The median duration until readmission was 27 days, and grip strength was found to be significantly related to readmission (p=0.020). CONCLUSION: After discharge, both medical services to manage the medical condition and intervention to maintain physical function are needed to prevent frail older adults from being readmitted to the hospital.

Low muscle mass, low muscle function, and sarcopenia in the urban and rural elderly.

Health outcomes of the elderly vary between rural and urban areas. Sarcopenia is diagnosed as loss of muscle strength or impaired physical performance, namely "low muscle function" and low muscle mass. Outcomes of low muscle mass and low muscle function are not equal. This study aimed to investigate the prevalence of low muscle mass, low muscle function, and sarcopenia in rural and urban populations and to determine whether regional differences were associated with each of these components. Participants aged ≥ 69 years (n = 2354) were recruited from three urban districts and one rural district in Korea. Low muscle mass was defined by appendicular lean mass using bioelectrical impedance analysis. Low muscle function was defined by handgrip strength and 5-chair stand test. Sarcopenia was defined as low muscle mass plus low muscle function. The prevalence of low muscle function (53.7% vs. 72.8%), and sarcopenia (16.3% vs. 24.4%) were higher in the rural elderly population. Rural residence was associated with low muscle function (OR 1.63; 95% CI 1.13-2.37, P = 0.009), but not with low muscle mass (OR 0.58; 95% CI 0.22-1.54, P = 0.271) or with sarcopenia (OR 1.13; 95% CI 0.63-2.00, P = 0.683). Interventions to detect and improve low muscle function in rural elderly population are needed.

COMPrehensive geriatric AsseSSment and multidisciplinary team intervention for hospitalised older adults (COMPASS): a protocol of pragmatic trials within a cohort.

INTRODUCTION: There is an increased demand for services for hospitalised older patients with acute medical conditions due to rapidly ageing population. The COMPrehensive geriatric AsseSSment and multidisciplinary team intervention for hospitalised older adults (COMPASS) study will test the effectiveness of comprehensive geriatric assessment (CGA) and multidisciplinary intervention by comparing it with conventional care among acute hospitalised older adults in Korea. METHODS AND ANALYSIS: A multicentre trial within a cohort comprising three substudies (randomised controlled trials) will be conducted. The intervention includes CGA and CGA-based multidisciplinary interventions by physicians (geriatricians, oncologists), nurses, nutritionists and pharmacists. The multidisciplinary intervention includes nutritional support, medication review and adjustment, rehabilitation, early discharge planning and prevention of geriatric syndromes (falls, delirium, pressure sore and urinary retention). The analysis will be based on an intention-to-treat principle. The primary outcome is living at home 3 months after discharge. In addition to assessing the economic effects of the intervention, a cost-utility analysis will be conducted. ETHICS AND DISSEMINATION: The study protocol was reviewed and approved by the ethics committees of Seoul National University Bundang Hospital and each study site. The study findings will be published in peer-reviewed journals. Subgroup and further in-depth analyses will subsequently be published. TRIAL REGISTRATION NUMBER: KCT0006270.

Reference values of skeletal muscle area for diagnosis of sarcopenia using chest computed tomography in Asian general population.

BACKGROUND: Diagnostic cutoff points for sarcopenia in chest computed tomography (CT) have not been established although CT is widely used for investigating skeletal muscles. This study aimed to determine reference values for sarcopenia of thoracic skeletal muscles acquired from chest CT scans and to analyse variables related to sarcopenia using the cutoff values determined in a general Asian population. METHODS: We retrospectively reviewed chest CT scans of 4470 participants (mean age 54.8 ± 9.9 years, 65.8% male) performed at a check-up centre in South Korea (January 2016-August 2017). To determine cutoffs, 335 participants aged 19-39 years (mean age 35.2 ± 3.6 years, 75.2% male) were selected as the healthy and younger reference group, and 4135 participants aged ≥40 years (mean age 56.4 ± 8.4 years, 65.1% male) were selected as the study group. We measured the following: cross-sectional area (CSA) of the pectoralis, intercostalis, paraspinal, serratus, and latissimus muscles at the 4th vertebral region (T4CSA ); T4CSA divided by height2 (T4MI); pectoralis muscle area (PMCSA ); and PMCSA divided by height2 (PMI) at the 4th vertebral region. Sarcopenia cutoff was defined as sex-specific values of less than -2 SD below the mean from the reference group. RESULTS: In the reference group, T4CSA , T4MI, PMCSA , and PMI cutoffs for sarcopenia were 100.06cm2 , 33.69cm2 /m2 , 29.00cm2 , and 10.17cm2 /m2 in male, and 66.93cm2 , 26.01cm2 /m2 , 18.29cm2 , and 7.31cm2 /m2 in female, respectively. The prevalence of sarcopenia in the study group measured with T4CSA , T4MI, PMCSA and PMI cutoffs were 11.4%, 8.7%, 8.5%, and 10.1%, respectively. Correlations were observed between appendicular skeletal mass divided by height2 measured by bioelectrical impedance analysis (BIA) and T4CSA (r = 0.82; P < 0.001)/T4MI (r = 0.68; P < 0.001), and ASM/height2 measured by BIA and PMCSA (r = 0.72; P < 0.001)/PMI (r = 0.63; P < 0.001). In the multivariate logistic regression models, sarcopenia defined by T4CSA /T4MI were related to age [odds ratio (95% confidence interval), P-values: 1.09 (1.07-1.11), <0.001/1.05 (1.04-1.07), <0.001] and diabetes [1.60 (1.14-2.25), 0.007/1.47 (1.01-2.14), 0.043]. Sarcopenia defined by PMCSA /PMI were related to age [1.09 (1.08-1.10), <0.001/1.05 (1.03-1.06), <0.001], male sex [0.23 (0.18-0.30), <0.001/0.47 (0.32-0.71), <0.001], diabetes [2.30 (1.73-3.05), <0.001/1.63 (1.15-2.32), 0.007], history of cancer [2.51 (1.78-3.55), <0.001/1.61 (1.04-2.48), 0.033], and sufficient physical activity [0.67 (0.50-0.89), 0.007/0.74 (0.56-0.99), 0.042]. CONCLUSIONS: The reference cutoff values of a general population reported here will enable sex-specific standardization of thoracic muscle mass quantification and sarcopenia assessment.

Physical resilience as a moderator of the relationship between frailty and disability in older adults with osteoarthritis.

AIMS: Frailty is a leading cause of deteriorating physical function of older adults with osteoarthritis. This study examined a model of frailty with the goals of (1) exploring the direct effect of osteoarthritic symptoms on disability and the mediating effect of frailty on disability and (2) determining whether both effects are moderated by physical resilience. DESIGN: A cross-sectional descriptive study. METHODS: Data collection was conducted among patients 65-92 years of age (N = 235) who visited primary medical centres for the management of chronic arthritic pain between July and December 2019. Participants completed a questionnaire measuring osteoarthritic symptoms, frailty, physical resilience, and disability. SPSS 25.0 was used to analyse the conditional process model. This study was reported following the STROBE guidelines. RESULTS: Frailty was shown to be a mediator between osteoarthritic symptoms and disability. Furthermore, physical resilience played a role as a moderator in both the direct and indirect pathways of this mediating relationship. CONCLUSION: The findings emphasize the detrimental effects of osteoarthritic symptoms on disability through frailty, and the moderated mediation results suggest that these effects were conditional on physical resilience, which is a modifiable internal resource of individuals. When planning nursing interventions for older adults with osteoarthritis, nurses need to consider physical resilience as a moderator to prevent frailty and disability.

Association of frailty with regional sagittal spinal alignment in the elderly.

The degenerative changes in the spine of the frail elderly gradually exacerbate the alignment of the spine as the degeneration progresses. This study was conducted to assess the relationship between frailty and spine sagittal alignment measured in terms of global, cervical, thoracic, and lumbo-pelvic parameters. In total, 101 patients aged 75 years and older hospitalized for spine surgery were prospectively enrolled. We evaluated spinal sagittal parameters by dividing them into global (C7 sagittal vertical axis [SVA] and T1 pelvic angle [T1PA]), cervical (the C2-7 Cobb angle, Jackson line, and C2-7 plumb line), thoracic (thoracic kyphosis [TK]), and lumbo-pelvic (pelvic tilt [PT] and pelvic incidence minus lumbar lordosis value [PI-LL]). Patient characteristics; the Fatigue, Resistance, Ambulation, Illness, Loss of Weight (FRAIL) scale; and sagittal spinal parameters were included in the analysis. Multiple regression analysis was performed to identify associations between the FRAIL scale and sagittal spinal parameters. The FRAIL scale showed correlations with global sagittal parameters (C7 SVA [ß = 0.225, p = 0.029] and T1PA [ß = 0.273, p = 0.008]) and lumbo-pelvic parameters (PT [ß = 0.294, p = 0.004] and PI-LL [ß = 0.323, p = 0.001). Cervical and thoracic parameters were not directly associated with the FRAIL scale. LL and PI-LL were associated with TK, and TK was associated with cervical parameters (the C2-7 Cobb angle, Jackson line and C2-7 plumb line). In conclusion, frailty status could be an important factor that influences sagittal spinal alignment in the elderly. In this study, it was found that frailty mainly affected the balance of lumbo-pelvic alignment, and consequently affected the balance of the whole spine.

Deep neural network for automatic volumetric segmentation of whole-body CT images for body composition assessment.

BACKGROUND & AIMS: Body composition analysis on CT images is a valuable tool for sarcopenia assessment. We aimed to develop and validate a deep neural network applicable to whole-body CT images of PET-CT scan for the automatic volumetric segmentation of body composition. METHODS: For model development, one hundred whole-body or torso 18F-fluorodeoxyglucose PET-CT scans of 100 patients were retrospectively included. Two radiologists semi-automatically labeled the following seven body components in every CT image slice, providing a total of 46,967 image slices from the 100 scans for training the 3D U-Net (training, 39,268 slices; tuning, 3116 slices; internal validation, 4583 slices): skin, bone, muscle, abdominal visceral fat, subcutaneous fat, internal organs with vessels, and central nervous system. The segmentation accuracy was assessed using reference masks from three external datasets: two Korean centers (4668 and 4796 image slices from 20 CT scans, each) and a French public dataset (3763 image slices from 24 CT scans). The 3D U-Net-driven values were clinically validated using bioelectrical impedance analysis (BIA) and by assessing the model's diagnostic performance for sarcopenia in a community-based elderly cohort (n = 522). RESULTS: The 3D U-Net achieved accurate body composition segmentation with an average dice similarity coefficient of 96.5%-98.9% for all masks and 92.3%-99.3% for muscle, abdominal visceral fat, and subcutaneous fat in the validation datasets. The 3D U-Net-derived torso volume of skeletal muscle and fat tissue and the average area of those tissues in the waist were correlated with BIA-derived appendicular lean mass (correlation coefficients: 0.71 and 0.72, each) and fat mass (correlation coefficients: 0.95 and 0.93, each). The 3D U-Net-derived average areas of skeletal muscle and fat tissue in the waist were independently associated with sarcopenia (P < .001, each) with adjustment for age and sex, providing an area under the curve of 0.858 (95% CI, 0.815 to 0.901). CONCLUSIONS: This deep neural network model enabled the automatic volumetric segmentation of body composition on whole-body CT images, potentially expanding adjunctive sarcopenia assessment on PET-CT scan and volumetric assessment of metabolism in whole-body muscle and fat tissues.

Daytime Glycemic Variability and Frailty in Older Patients with Diabetes: a Pilot Study Using Continuous Glucose Monitoring.

We investigated the relationship between glucose variability and frailty. Forty-eight type 2 diabetic patients aged ≥ 65 years were enrolled. The FRAIL scale was used for frailty assessment, and participants were classified into 'healthy & pre-frail' (n = 24) and 'frail' (n = 24) groups. A continuous glucose monitoring (CGM) system was used for a mean of 6.9 days and standardized CGM metrics were analyzed: mean glucose, glucose management indicator (GMI), coefficient of variation, and time in range, time above range (TAR), and time below range. The demographics did not differ between groups. However, among the CGM metrics, mean glucose, GMI, and TAR in the postprandial periods were higher in the frail group (all P < 0.05). After multivariate adjustments, the post-lunch TAR (OR = 1.12, P = 0.019) affected the prevalence of frailty. Higher glucose variability with marked daytime postprandial hyperglycemia is significantly associated with frailty in older patients with diabetes.

Bone Radiomics Score Derived From DXA Hip Images Enhances Hip Fracture Prediction in Older Women.

Dual-energy X-ray absorptiometry (DXA)-based bone mineral density testing is standard to diagnose osteoporosis to detect individuals at high risk of fracture. A radiomics approach to extract quantifiable texture features from DXA hip images may improve hip fracture prediction without additional costs. Here, we investigated whether bone radiomics scores from DXA hip images could improve hip fracture prediction in a community-based cohort of older women. The derivation set (143 women who sustained hip fracture [mean age 73 years, time to fracture median 2.1 years] versus 290 age-matched women [mean age 73 years] who did not sustain hip fracture during follow-up [median 5.5 years]) were split into the train set (75%) and the test set (25% hold-out set). Among various models using 14 selected features out of 300 texture features mined from DXA hip images in the train set, random forest model was selected as the best model to build a bone radiomics score (range 0 to 100) based on the performance in the test set. In a community-based cohort (2029 women, mean age 71 years) as the clinical validation set, the bone radiomics score was calculated using a model fitted in the train set. A total of 34 participants (1.7%) sustained hip fracture during median follow-up of 5.4 years (mean bone radiomics score 40 ± 16 versus 28 ± 12 in non-fractured, p < 0.001). A one-point bone radiomics score increment was associated with a 4% elevated risk of incident hip fracture (adjusted hazard ratio [aHR] = 1.04, p = 0.001) after adjustment for age, body mass index (BMI), previous history of fracture, and femoral neck T-score, with improved model fit when added to covariates (likelihood ratio chi-square 10.74, p = 0.001). The association between bone radiomics score with incident hip fracture remained robust (aHR = 1.06, p < 0.001) after adjustment for FRAX hip fracture probability. Bone radiomics scores estimated from texture features of DXA hip images have the potential to improve hip fracture prediction. © 2021 American Society for Bone and Mineral Research (ASBMR).

Computed Tomography-Derived Skeletal Muscle Radiodensity Predicts Peak Weight-Corrected Jump Power in Older Adults: The Korean Urban Rural Elderly (KURE) Study.

Computed tomography (CT)-derived skeletal muscle area (SMA) and skeletal muscle radiodensity (SMD) reflect distinctive quantitative and qualitative characteristics of skeletal muscles. However, data on whether CT-based muscle parameters, especially SMD, can predict muscle function is limited. In a prospective cohort, 1523 community-dwelling older adults who underwent abdominal CT scans and the countermovement two-legged jumping test on a ground reaction force platform were analyzed (mean age 74.7 years, 65.1% women). SMA and SMD were measured at third lumbar vertebra level (L3). Individuals with low jump power (peak weight-corrected jump power < 23.8 W/kg in men and < 19.0 W/kg in women using clinically validated threshold) were older; had lower SMA, SMD, and maximal grip strength values; and had lower chair rise test and timed up and go test performance than those without low jump power. SMD was positively associated with peak weight-corrected jump power (adjusted ß = 0.33 and 0.23 per 1 HU increase in men and women, respectively, p < 0.001). One HU decrement in SMD was associated with 10% elevated odds of low jump power (adjusted OR [aOR] 1.10, p < 0.001) after adjusting for age, sex, height, inflammation, and insulin resistance markers, whereas the association of SMA with low jump power was attenuated (aOR 1.00, p = 0.721). SMD showed better discrimination for low jump power than SMA (AUC 0.699 vs. 0.617, p < 0.001), with additional improvement when added to SMA and conventional risk factors (AUC 0.745 to 0.773, p < 0.001). Therefore, CT-measured L3 SMD can be a sensitive surrogate marker for muscle function along with SMA in older adults, which merits further investigation.