Susceptibility to Treatment-Resistant Depression Within Families.

Importance: Antidepressant responses and the phenotype of treatment-resistant depression (TRD) are believed to have a genetic basis. Genetic susceptibility between the TRD phenotype and other psychiatric disorders has also been established in previous genetic studies, but population-based cohort studies have not yet provided evidence to support these outcomes. Objective: To estimate the TRD susceptibility and the susceptibility between TRD and other psychiatric disorders within families in a nationwide insurance cohort with extremely high coverage and comprehensive health care data. Design, Setting, and Participants: This cohort study assessed data from the Taiwan national health insurance database across entire population (N = 26 554 001) between January 2003 and December 2017. Data analysis was performed from August 2021 to April 2023. TRD was defined as having experienced at least 3 distinct antidepressant treatments in the current episode, each with adequate dose and duration, based on the prescribing records. Then, we identified the first-degree relatives of individuals with TRD (n = 34 467). A 1:4 comparison group (n = 137 868) of first-degree relatives of individuals without TRD was arranged for the comparison group, matched by birth year, sex, and kinship. Main Outcomes and Measures: Modified Poisson regression analyses were performed and adjusted relative risks (aRRs) and 95% CIs were calculated for the risk of TRD, the risk of other major psychiatric disorders, and different causes of mortality. Results: This study included 172 335 participants (88 330 male and 84 005 female; mean [SD] age at beginning of follow-up, 22.9 [18.1] years). First-degree relatives of individuals with TRD had lower incomes, more physical comorbidities, higher suicide mortality, and increased risk of developing TRD (aRR, 9.16; 95% CI, 7.21-11.63) and higher risk of other psychiatric disorders than matched control individuals, including schizophrenia (aRR, 2.36; 95% CI, 2.10-2.65), bipolar disorder (aRR, 3.74; 95% CI, 3.39-4.13), major depressive disorder (aRR, 3.65; 95% CI, 3.44-3.87), attention-deficit/hyperactivity disorders (aRR, 2.38; 95% CI, 2.20-2.58), autism spectrum disorder (aRR, 2.26; 95% CI, 1.86-2.74), anxiety disorder (aRR, 2.71; 95% CI, 2.59-2.84), and obsessive-compulsive disorder (aRR, 3.14; 95% CI, 2.70-3.66). Sensitivity and subgroup analyses validated the robustness of the findings. Conclusions and Relevance: To our knowledge, this study is the largest and perhaps first nationwide cohort study to demonstrate TRD phenotype transmission across families and coaggregation with other major psychiatric disorders. Patients with a family history of TRD had an increased risk of suicide mortality and tendency toward antidepressant resistance; therefore, more intensive treatments for depressive symptoms might be considered earlier, rather than antidepressant monotherapy.

Application and effectiveness of artificial intelligence for the border management of imported frozen fish in Taiwan.

In Taiwan, the number of applications for inspecting imported food has grown annually and noncompliant products must be accurately detected in these border sampling inspections. Previously, border management has used an automated border inspection system (import food inspection (IFI) system) to select batches via a random sampling method to manage the risk levels of various food products complying with regulatory inspection procedures. Several countries have implemented artificial intelligence (AI) technology to improve domestic governmental processes, social service, and public feedback. AI technologies are applied in border inspection by the Taiwan Food and Drug Administration (TFDA). Risk management of border inspections is conducted using the Border Prediction Intelligent (BPI) system. The risk levels are analyzed on based on the noncompliance records of imported food, the country of origin, and international food safety alerts. The subjects of this study were frozen fish products, which have been under surveillance by the BPI system. The purpose of this study was to investigate the relevance between the noncompliant trend of frozen fish products using the adoption of the BPI system and the results of postmarket sampling inspections. The border inspection and postmarket sampling data were divided into two groups: IFI and BPI groups (corresponding to before and after the adoption of the BPI system, respectively). The Chi-square test was employed to analyze the noncompliant differences in products between before and after the BPI system adoption. Despite the number of noncompliance batches being statistically insignificant after the adoption of the BPI system, the noncompliance rate of frozen fish products at the border increased from 3.0% to 4.7%. Meanwhile, the noncompliance rate in the postmarket decreased from 2.1% to 1.9%. The results indicate that the BPI system improves the effectiveness of interception of noncompliant products at the border, thereby preventing the entrance of noncompliant products to the postmarket. The variables were further classified and organized according to the scope of this study and product characteristics. Furthermore, ordinal logistic regression (OLR) was employed to determine the correlations among border, postmarket, and major influencing factors. Based on the analysis of major influencing factors, small fish and fish internal organ products exhibited significantly high risk for fish body type and product type, respectively. The BPI system effectively utilizes the large amount of data accumulated from border inspections over the years. Additionally, real-time information on bilateral data obtained from the border and postmarket should be bidirectionally shared for effectively intercepting noncompliance products and used for improving the border management efficiency.

Predictors of live-in migrant caregiver employment for people with dementia in Taiwan.

BACKGROUND: With the increasing number of individuals with dementia, families have hired an increasing number of live-in migrant caregivers (LIMCs). Currently, limited evidence is available regarding the influence of long-term care resource utilization on the hiring of LIMCs for caring for individuals with dementia in Taiwan. METHODS: We recruited individuals with dementia who did not hire LIMCs and their primary family caregivers from nine hospitals in Taiwan as baseline. Multivariable logistic regression was used to evaluate the utilization of long-term care resources for individuals with dementia and other factors that may affect the decision to hire LIMCs. RESULTS: The users of non-long-term care resources had the highest likelihood of hiring LIMCs (odds ratio [OR] = 4.24, 95% CI, 2.30-7.84). Compared with spouses, nonimmediate family caregivers (OR = 3.40, 95% CI, 1.16-9.90) were significantly more likely to hire LIMCs. A higher likelihood of hiring LIMCs was observed for those with Lewy body dementia compared with other individuals (OR = 2.31, 95% CI, 1.03-5.14). Compared with individuals who did not hire LIMCs, those who hired LIMCs exhibited higher scores on the Neuropsychiatric Inventory (NPI) and higher severity of individual NPI items. CONCLUSION: Hiring LIMCs is strongly correlated with the utilization of non-long-term care resources and is influenced by the dynamics between individuals with dementia and their primary family caregivers. A higher likelihood of hiring LIMCs was observed for individuals with Lewy body dementia and individuals with elevated NPI scores compared with their counterparts. Given these observations, various support strategies and interventions should be tailored to the specific requirements of individuals with dementia and their families.

A national survey on health-related quality of life for people with dementia in residential long-term care institutions.

BACKGROUND: Health-related quality of life (HRQoL) is an essential outcome parameter in geriatric research; however, the available evidence is mixed regarding the factors associated with HRQoL among people with dementia. We aimed to identify factors that contribute to HRQoL among people with dementia in residential long-term care (LTC) institutions. METHODS: We randomly selected 299 of 1607 registered residential LTC institutions in Taiwan. A cross-sectional survey was conducted between 2019 and 2020, including items on demographic characteristics, comorbidities, the EuroQol-5 dimensions-5 levels (EQ-5D-5L; utility and visual analog scale [VAS] scores), the Mini-Mental State Examination (MMSE), the Clinical Dementia Rating (CDR), behavioral and psychological symptoms of dementia, activities of daily living (ADL), and instrumental ADL (IADL). RESULTS: In total, 1313 people with dementia from 267 institutions were enrolled (mean age, 76.4 ± 12.7 years). The mean EQ-5D-5L utility and VAS scores were 0.10 (standard deviation [SD] = 0.48) and 66.57 (SD = 20.67), respectively. In multivariate linear regression analysis, higher scores for ADL, IADL, and CDR sum of boxes were associated with higher utility scores. Higher VAS scores were associated with higher ADL and MMSE scores. Lower utility scores and VAS scores were associated with more frequent depressive symptoms. CONCLUSION: ADL, dementia severity, cognitive function, and depressive symptoms influenced the HRQoL of people with dementia in residential LTC institutions. Longitudinal studies should be conducted to better understand how HRQoL changes over time among people with disabilities.

Abnormalities of Hippocampal Subfield and Amygdalar Nuclei Volumes and Clinical Correlates in Behavioral Variant Frontotemporal Dementia with Obsessive-Compulsive Behavior-A Pilot Study.

(1) Background: The hippocampus (HP) and amygdala are essential structures in obsessive-compulsive behavior (OCB); however, the specific role of the HP in patients with behavioral variant frontotemporal dementia (bvFTD) and OCB remains unclear. (2) Objective: We investigated the alterations of hippocampal and amygdalar volumes in patients with bvFTD and OCB and assessed the correlations of clinical severity with hippocampal subfield and amygdalar nuclei volumes in bvFTD patients with OCB. (3) Materials and methods: Eight bvFTD patients with OCB were recruited and compared with eight age- and sex-matched healthy controls (HCs). Hippocampal subfield and amygdalar nuclei volumes were analyzed automatically using a 3T magnetic resonance image and FreeSurfer v7.1.1. All participants completed the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Neuropsychiatric Inventory (NPI), and Frontal Behavioral Inventory (FBI). (4) Results: We observed remarkable reductions in bilateral total hippocampal volumes. Compared with the HCs, reductions in the left hippocampal subfield volume over the cornu ammonis (CA)1 body, CA2/3 body, CA4 body, granule cell layer, and molecular layer of the dentate gyrus (GC-ML-DG) body, molecular layer of the HP body, and hippocampal tail were more obvious in patients with bvFTD and OCB. Right subfield volumes over the CA1 body and molecular layer of the HP body were more significantly reduced in bvFTD patients with OCB than in those in HCs. We observed no significant difference in amygdalar nuclei volume between the groups. Among patients with bvFTD and OCB, Y-BOCS score was negatively correlated with left CA2/3 body volume (τb = -0.729, p < 0.001); total NPI score was negatively correlated with left GC-ML-DG body (τb = -0.648, p = 0.001) and total bilateral hippocampal volumes (left, τb = -0.629, p = 0.002; right, τb = -0.455, p = 0.023); and FBI score was negatively correlated with the left molecular layer of the HP body (τb = -0.668, p = 0.001), CA4 body (τb = -0.610, p = 0.002), and hippocampal tail volumes (τb = -0.552, p < 0.006). Mediation analysis confirmed these subfield volumes as direct biomarkers for clinical severity, independent of medial and lateral orbitofrontal volumes. (5) Conclusions: Alterations in hippocampal subfield volumes appear to be crucial in the pathophysiology of OCB development in patients with bvFTD.

Treatment resistant depression in elderly.

Treatment refractory depression (TRD) in the elderly is a common psychiatric disorder with high comorbidity and mortality. Older adults with TRD often have complicated comorbidities and several predisposing risk factors, which may lead to neuropsychiatric dysfunction and poor response to treatment. Several hypotheses suggest the underlying mechanisms, including vascular, immunological, senescence, or abnormal protein deposition. Treatment strategies for TRD include optimization of current medication dose, augmentation, switching to an alternative agent or class, and combination of different antidepressant classes, as well as nonpharmacological adjuvant interventions such as biophysical stimulation and psychotherapy. In summary, treatment recommendations for TRD in the elderly favor a multimodal approach, combining pharmacological and nonpharmacological treatments.

Health-related quality of life and mild behavioral impairment in older adults without dementia.

BACKGROUND: The Mild Behavioral Impairment Checklist (MBI-C) was developed to assess neuropsychiatric symptoms (NPS) and to identify mild behavioral impairment (MBI). This study validated the Taiwanese version of the MBI-C and examined its association of health-related quality of life (HR-QoL). METHODS: We recruited 242 older individuals without dementia (129 amnestic mild cognitive impairment, 113 cognitively normal). Their family completed the MBI-C, the Neuropsychiatric Inventory Questionnaire (NPI-Q), and instrumental activities of daily living scale. Participants completed the Geriatric Depression Scale (GDS-15), the Mini-Mental State Examination, the 12-item word recall test, the category verbal fluency test and the EuroQol 5 dimensions questionnaire (EQ-5D). Cronbach's α was used to evaluate the internal consistency of the MBI-C. Linear regression models were used to examined the association between MBI-C score and HR-QoL assessed using ED-5D. RESULTS: The prevalence of MBI was 12% of all participants. Cronbach's α of the MBI-C was 0.893. The optimal cut-off point of MBI-C was 7.5 for identifying MBI, with a sensitivity of 100% and specificity of 85%. The MBI-C total score (ß = -0.01, 95% confidence interval [CI] = -0.02 to -0.01, p < 0.001), MBI-C subdomain of decreased motivation (ß = -0.04, 95% CI = -0.05 to -0.02, p < 0.001) and emotional dysregulation (ß = -0.02, 95% CI = -0.04 to -0.004, p = 0.01) were factors related to EQ-5D index scores. CONCLUSION: Among older adults without dementia, the Taiwanese version of the MBI-C has good reliability and validity for detecting MBI. The total and subdomains of MBI-C were associated with decreased HR-QoL among individuals without dementia.

Risk of All-Cause and Suicide Death in Patients With Schizophrenia: An Entire-Population Longitudinal Study in Taiwan.

Background: Schizophrenia increases mortality from all causes and specific causes. Comprehensive research on modifiable risk factors for early mortality from multiple sources is needed.Methods: Taiwan's National Health Insurance Research Database, which contains claims data from a lifetime insurance program for the whole population, provided extensive medical inpatient and outpatient data categorized by ICD-9-CM and ICD-10 for this nationwide retrospective longitudinal cohort study. The National Mortality Registry provided data on all-cause, natural, suicide, and accidental deaths. 191,553 patients with schizophrenia and 26,362,448 individuals without schizophrenia were monitored from January 1, 2003, to December 31, 2017. Adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for mortality risk were calculated using Cox regression models. We compared different mortality risks associated with schizophrenia across age, sex, and Charlson Comorbidity Index (CCI) subgroups.Results: We found that schizophrenia results in a relatively higher increase in suicidal mortality in those aged ≤ 20 years (aHR = 15.55; 95% CI, 13.95-17.34), and that effect decreased with age. The effect of schizophrenia in female individuals (suicide death: female, aHR = 11.82, 95% CI, 11.21-12.46; male, aHR = 8.11, 95% CI, 7.77-8.47; difference, P < .001) and individuals without comorbidity (natural cause of death, CCI = 0 aHR = 5.94, 95% CI, 5.68-6.22; CCI = 1-2 aHR = 3.62, 95% CI, 3.52-3.73; CCI > 2 aHR = 1.61, 95% CI, 1.58-1.64) led to comparatively higher mortality risks. The effect of schizophrenia in individuals with AIDS (suicide death, aHR = 2.73, 95% CI, 1.70-4.39) resulted in a relatively smaller increase in suicide mortality compared to individuals with other comorbidities; however, in patients with connective tissue diseases, a diagnosis of schizophrenia still leads to an alarming increase in natural and unnatural mortality.Conclusions: Schizophrenia in combination with younger age, female sex, comorbid connective tissue disease, or major organ problems necessitates more tailored countermeasures to lessen the higher mortality risk in these patients compared with patients who have these characteristics and conditions but do not have schizophrenia.

Differences in gut microbiota correlate with symptoms and regional brain volumes in patients with late-life depression.

Depression is associated with gut dysbiosis that disrupts a gut-brain bidirectional axis. Gray matter volume changes in cortical and subcortical structures, including prefrontal regions and the hippocampus, have also been noted in depressive disorders. However, the link between gut microbiota and brain structures in depressed patients remains elusive. Neuropsychiatric measures, stool samples, and structural brain images were collected from 36 patients with late-life depression (LLD) and 17 healthy controls. 16S ribosomal RNA (rRNA) gene sequencing was used to profile stool microbial communities for quantitation of microbial composition, abundance, and diversity. T1-weighted brain images were assessed with voxel-based morphometry to detect alterations in gray matter volume between groups. Correlation analysis was performed to identify the possible association between depressive symptoms, brain structures and gut microbiota. We found a significant difference in the gut microbial composition between patients with late-life depression (LLD) and healthy controls. The genera Enterobacter and Burkholderia were positively correlated with depressive symptoms and negatively correlated with brain structural signatures in regions associated with memory, somatosensory integration, and emotional processing/cognition/regulation. Our study purports the microbiota-gut-brain axis as a potential mechanism mediating the symptomatology of LLD patients, which may facilitate the development of therapeutic strategies targeting gut microbes in the treatment of elderly depressed patients.

Stable carbon isotopic characterization of rice vinegar protein as an intrinsic reference for discriminating the authenticity of brewed rice vinegar.

Rice vinegar plays an important role in daily life. However, some unscrupulous manufacturers may deliberately add synthetic acetic acid in vinegar products to reduce fermentation time and save production costs. To protect the rights and health of consumers, vinegar authenticity must be controlled. The rice vinegar protein was used as an intrinsic reference and its stable carbon isotope ratio (δ13Cprotein) was analyzed by elemental analyzer-isotope ratio mass spectrometry. The stable carbon isotope ratio difference between the acetic acid and the rice vinegar protein (Δδ13Cacetic acid-protein) was calculated to evaluate vinegar authenticity. Sixteen rice vinegar samples were analyzed and a stable carbon isotopic pattern of rice vinegar was established by the 95% confidence interval for Δδ13Cacetic acid-protein (0.27‰-2.10‰). An acetic acid adulteration curve of Δδ13Cacetic acid-protein was also assumed according to the data from rice vinegar samples, and its validity was confirmed by rice vinegar deliberately blended with acetic acid at different ratios (25, 50, and 75%). The Δδ13Cacetic acid-protein values of the adulterated vinegars decreased with increasing amounts blended acetic acid, but the δ13Cprotein values did not, showing that rice vinegar protein could be used as an intrinsic reference for identifying the adulterated rice vinegar. The rice vinegar adulterated with acetic acid at higher than approximately 10% could be detected.

Determinants of long-term care service use by persons with dementia: A national dementia registry study conducted in Taiwan.

BACKGROUND: This study investigated the determinants and use of Taiwan's long-term care (LTC) Plan Version 2.0 (LTC 2.0) services by persons with dementia (PWDs) and their caregivers. METHODS: In total, 1268 PWD-caregiver dyads were enrolled for analysis from a national dementia registry. Andersen's Behavioral Model of Health Services Use was used to investigate the association of LTC service use with several factors, namely the demographic data of PWDs and their caregivers, migrant caregiver employment, monthly household income, caregiver burden as determined by the Zarit Burden Interview (ZBI), Mini-Mental State Examination score, Clinical Dementia Rating scores, neuropsychiatric inventory scores for the behavioral and psychological symptoms of dementia, and PWDs' activities of daily living (ADLs). RESULTS: Among the studied family caregivers, 81.4% did not use LTC resources. A multivariable logistic analysis revealed that aberrant motor behaviors (odd ratio [OR] = 1.31, 95% confidence interval [CI] = 1.10-1.56, p = 0.003), dysfunction in ADLs (OR = 1.06, 95% CI = 1.02-1.10, p = 0.002), higher ZBI scores (OR = 1.02, 95% CI = 1.01-1.03, p = 0.004), not residing with family members (OR = 1.88, 95% CI = 1.32-2.66, p < 0.001), and not employing a migrant caregiver (OR = 4.41, 95% CI = 2.59-7.51, p < 0.001) were the factors most significantly associated with LTC service use. CONCLUSION: Factors such as whether PWDs live alone, specific neuropsychiatric symptoms, and impaired function should be considered in future policy amendments to provide required activities and care resources for PWDs and their caregivers.

Predictors of emergency department visit among people with dementia in Taiwan.

BACKGROUND: We aimed to identify predictors of emergency department (ED) visit by people with dementia (PWDs) and their caregivers with a one-year follow-up in a country with public health system. METHODS: Data were collected from a national dementia registration survey. Andersen's Behavioral Model of Health Services Use was used. Variables such as demographic data of PWDs and their caregivers, caregivers' monthly income, the relationship between PWD and caregivers, the severity of dementia (clinical dementia rating, CDR), physical comorbidities, cognitive function (mini-mental state examination, MMSE), and activities of daily living of PWDs, the caregiver burden, and neuropsychiatric symptoms (assessed by the Neuropsychiatric Inventory Questionnaire) were included in the analyses. RESULTS: A total of 1,227 PWDs-caregiver dyads completed the survey, and 405 (33%) of PWDs visited ED during the one-year follow-up. Multivariable logistic analyses revealed that older age of PWDs (odds ratio [OR] = 1.03, 95% confidence interval [CI] = 1.01-1.05), more severe dementia (CDR; OR = 1.42, 95% CI = 1.09-1.86), higher cognitive function (MMSE; OR = 1.04, 95% CI = 1.01-1.07), and having a female family caregiver (OR = 1.50, 95% CI = 1.13-2.01) were predictors of ED visit. CONCLUSION: Our study results provided information for healthcare providers and policy makers to target models of care that support PWD and their caregivers and reduce the need for ED visits.

Periodontitis is a potential risk factor for transient ischemic attack and minor ischemic stroke in young adults: A nationwide population-based cohort study.

BACKGROUND: This study aims to determine whether periodontitis is a risk factor for transient ischemic attack (TIA) in young adults. METHODS: The National Health Insurance (NHI) Research Database in Taiwan was the source of the data used in this retrospective cohort study. Individuals aged 20 to 53 years with periodontitis in 2001 and 2002 (n = 792,426) and an age- and sex-matched control group (n = 792,426) were selected. All participants were followed up until TIA diagnosis, 55 years of age, removal from the NHI program, death, or December 31, 2016. The incidence density and hazard ratio (HR) of new-onset TIA were compared between individuals with periodontitis and controls. Periodontitis was defined by dentists according to the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes 523.3-5 with concurrent antibiotic prescription or periodontal treatment excluding scaling performed by certified dentists. TIA was defined according to the ICD-9-CM code 435.x at hospital discharge. RESULTS: After adjustment for confounding factors, the risk of developing TIA/minor ischemic stroke was calculated to be higher in participants with periodontitis (HR, 1.24; 95% confidence interval, 1.15-1.32; P <0.001) than in those without. The HR was slightly higher among people aged 20 to 40 years than among those aged 40 to 53 years. CONCLUSION: Periodontitis is associated with an increased risk of developing TIA/minor ischemic stroke. Periodontitis might be a modifiable risk factor for stroke in young adults. Clinicians must devote greater attention to this potential association to develop new preventive and therapeutic strategies for stroke in young adults.

Factors associated with burden among male caregivers for people with dementia.

BACKGROUND: There is a dearth of information on male dementia caregivers in Asia and, in particular, on the factors relating to caregiver burden. We aimed to identify factors that may be associated with burden among male caregivers of people with dementia (PWD). METHODS: Data were collected from a national dementia registration survey. The caregiver burden was measured with the short version of the Zarit Burden Interview (ZBI). We analyzed the correlation between ZBI scores and variables, such as demographic data of PWD and their male caregivers, caregivers' monthly income, the relationship between PWD and caregivers, the severity of dementia, physical comorbidities and activities of daily living (ADL) of PWD, and neuropsychiatric symptoms assessed by the Neuropsychiatric Inventory (NPI). RESULTS: A total of 509 PWD and their male caregivers were included. The majority of caregivers were sons (72.1%) and husbands (22.0%). Sons had higher ZBI scores than husbands (28.5 ± 15.2 vs 22.0 ± 17.0; p < 0.001). Multivariable linear regression showed that sons as caregivers (ß = 7.44, p = 0.034), ADL (ß = 0.52, p = 0.002), and NPI_severity subscore of apathy (ß = 2.74, p = 0.001) were positively associated with ZBI scores. CONCLUSION: Poor ADL and apathy in PWD and being a patient's son were associated with higher levels of burden among male dementia caregivers. Effective interventions are needed to assist male caregivers in accomplishing their caregiving role and at the same time to alleviate their caregiver burden.

RETRACTED - Risk factors for mild behavioral impairment in non-demented geriatrics: a population-based survey in Taiwan.

OBJECTIVES: To investigate potential risk factors for mild behavioral impairment (MBI) among non-demented geriatrics. DESIGN: Population-based, cross-sectional survey. SETTING: Taiwan Alzheimer Disease Association (TADA) Database. PARTICIPANTS: Participants were selected by multistage random sampling of all Taiwan counties. They received in-person interviews between December 2011 and March 2013. MEASUREMENTS: Demographic data, lifestyle and habits, medical comorbidities, cognitive status measured by the Taiwanese Mini-Mental Status Examination (TMSE) and presence of MCI of the participants were collected. Subjects were distributed to the MBI and non-MBI groups. These factors had been evaluated for their effects on MBI in the univariate and multivariable logistic regression models. RESULTS: In total, 6,196 non-demented participants aged 65 years or older, including 409 MBI and 5,787 non-MBI participants, were recruited. After adjustment for age, sex, education, body mass index, lifestyle and habits, medical comorbidities, and MCI, good sleep was associated with lower risk of MBI (OR 0.09, 95% CI 0.07 - 0.12). Low body weight (OR 2.01, 95% CI 1.21-3.33), low-to-medium education (OR 1.40, 95%CI 1.06-1.85; OR 2.32, 95% CI 1.67-3.21), medical comorbidities of hypertension (OR 1.56, 95% CI 1.25-1.95), hyperlipidemia (OR 1.29, 95% CI 1.00-1.67), cancer (OR 2.05, 95% CI 1.37-3.06) were significantly associated with increased MBI risk. MCI neither increased nor decreased risk of MBI (OR 1.00, 95% CI 0.76-1.32). CONCLUSIONS: Good sleep was associated with lower MBI risk. Underweight, lower education, medical comorbidities of cancer, hypertension, hyperlipidemia were predictive of MBI.

Resting-State EEG Signal for Major Depressive Disorder Detection: A Systematic Validation on a Large and Diverse Dataset.

Major depressive disorder (MDD) is a global healthcare issue and one of the leading causes of disability. Machine learning combined with non-invasive electroencephalography (EEG) has recently been shown to have the potential to diagnose MDD. However, most of these studies analyzed small samples of participants recruited from a single source, raising serious concerns about the generalizability of these results in clinical practice. Thus, it has become critical to re-evaluate the efficacy of various common EEG features for MDD detection across large and diverse datasets. To address this issue, we collected resting-state EEG data from 400 participants across four medical centers and tested classification performance of four common EEG features: band power (BP), coherence, Higuchi's fractal dimension, and Katz's fractal dimension. Then, a sequential backward selection (SBS) method was used to determine the optimal subset. To overcome the large data variability due to an increased data size and multi-site EEG recordings, we introduced the conformal kernel (CK) transformation to further improve the MDD as compared with the healthy control (HC) classification performance of support vector machine (SVM). The results show that (1) coherence features account for 98% of the optimal feature subset; (2) the CK-SVM outperforms other classifiers such as K-nearest neighbors (K-NN), linear discriminant analysis (LDA), and SVM; (3) the combination of the optimal feature subset and CK-SVM achieves a high five-fold cross-validation accuracy of 91.07% on the training set (140 MDD and 140 HC) and 84.16% on the independent test set (60 MDD and 60 HC). The current results suggest that the coherence-based connectivity is a more reliable feature for achieving high and generalizable MDD detection performance in real-life clinical practice.

A Machine-Learning-Based Assessment Method for Early-Stage Neurocognitive Impairment by an Immersive Virtual Supermarket.

Alzheimer's disease (AD) is a neurodegenerative disorder. Though it is not yet curable or reversible, research has shown that clinical intervention or intensive cognitive training at an early stage may effectively delay the progress of the disease. As a result, screening populations with mild cognitive impairment (MCI) or early AD via efficient, effective and low-cost cognitive assessments is important. Currently, a cognitive assessment relies mostly on cognitive tests, such as the Mini-Mental State Examination (MMSE) or the Montreal Cognitive Assessment (MoCA), which must be performed by therapists. Also, cognitive functions can be divided into a variety of dimensions, such as memory, attention, executive function, visual spatial and so on. Executive functions (EF), also known as executive control or cognitive control, refer to a set of skills necessary to perform higher-order cognitive processes, including working memory, planning, attention, cognitive flexibility, and inhibitory control. Along with the fast progress of virtual reality (VR) and artificial intelligence (AI), this study proposes an intelligent assessment method aimed at assessing executive functions. Utilizing machine learning to develop an automatic evidence-based assessment model, behavioral information is acquired through performing executive-function tasks in a VR supermarket. Clinical trials were performed individuals with MCI or early AD and six healthy participants. Statistical analysis showed that 45 out of 46 indices derived from behavioral information were found to differ significantly between individuals with neurocognitive disorder and healthy participants. This analysis indicates these indices may be potential bio-markers. Further, machine-learning methods were applied to build classifiers that differentiate between individuals with MCI or early AD and healthy participants. The accuracy of the classifier is up to 100%, demonstrating the derived features from the VR system were highly related to diagnosis of individuals with MCI or early AD.

Risks of Coaggregation of Major Psychiatric Disorders Among First-Degree Relatives of Patients With Bipolar I and Bipolar II Disorder: Evidence From a Nationwide Population-Based Study.

Background: Etiologic differences between bipolar I disorder (BD-I) and bipolar II disorder (BD-II) have been challenged recently, and family epidemiologic studies may elucidate the matter. Nevertheless, it remains unclear whether BD-I and BD-II display different familial aggregation patterns within each bipolar disorder subtype and coaggregation with other psychiatric disorders.Method: Per the Taiwan National Health Insurance Research Database (N = 23,258,175), patients with bipolar disorder were classified as having BD-I or BD-II based on the history of psychiatric hospitalization for a manic episode. During the study period (2001-2011), 184,958 first-degree relatives (FDRs) of patients with BD-I and BD-II were identified. By comparing patients with 1:4 age-, sex-, and kinship-matched samples without BD-I/BD-II probands, the relative risks (RRs) of major psychiatric disorders were estimated.Results: FDRs of BD-I probands had a significantly higher risk of BD-I than those of BD-II probands (BD-I proband: RR = 15.80 vs BD-II proband: RR = 5.68, P < .001). The risk of BD-II was similar between FDRs of BD-I and BD-II probands (BD-I proband: RR = 6.48 vs BD-II proband: RR = 5.89, P = .1161). Familial aggregation was greater within each BD subtype than among cross-subtypes. Furthermore, FDRs of BD-I probands had an increased risk of schizophrenia (BD-I probands: RR = 5.83 vs BD-II probands: RR = 2.72, P < .001); FDRs of BD-II probands had a higher likelihood of attention-deficit/hyperactivity disorder (BD-II probands: 2.36 vs BD-I probands: 1.93, P = .0009).Conclusions: The risk of psychiatric disorders is higher among the FDRs of patients with either BD-I or BD-II. Furthermore, the familial specificity of BD-I and BD-II assessed in this study may further the current understanding of etiologic boundaries between bipolar disorder subtypes.