Relationship Between Life Satisfaction and Psychological Characteristics Among Community-Dwelling Oldest-old: Focusing on Erikson's Developmental Stages and the Big Five Personality Traits.

OBJECTIVE: To clarify the relationship between life satisfaction and the psychological characteristics of the oldest-old, and explore the factors for achieving mental health and longevity. DESIGN: This cross-sectional study conducted questionnaire surveys and face-to-face interviews as part of a larger prospective cohort study. SETTING: Arakawa Ward, a district in Tokyo, Japan. PARTICIPANTS: A total of 247 oldest-old individuals from two age groups, 85+ (aged 85-87 years) and 95+ (aged 95 years or older). MEASUREMENTS: Life satisfaction was assessed using the Satisfaction with Life Scale (SWLS), developmental stages of the elderly (Erikson's 8th and 9th stages, i.e., ego integrity, and gerotranscendence), and the Big Five personality traits (extraversion, agreeableness, openness, conscientiousness, and neuroticism) using the NEO-Five Factor Inventory. Multiple regression analyses were performed to examine the relationship between the SWLS scores and each assessment, controlling for age, sex, education, activities of daily living, depressive symptoms, and cognitive function. RESULTS: The SWLS scores of 85+ were positively correlated with scores of ego integrity, extraversion, and conscientiousness. Contrastingly, the SWLS scores of 95+ were positively correlated with gerotranscendence scores. CONCLUSIONS: Psychological characteristics associated with the level of life satisfaction among community-dwelling oldest-old individuals were identified, but a causal relationship between these factors and life satisfaction was not established. Ego integrity, extraversion, conscientiousness, and gerotranscendence may be associated with enhanced life satisfaction and mental health in the oldest-old. Further, the factors associated with life satisfaction in the 85+ and 95+ age groups varied, suggesting that life satisfaction among the oldest-old has different foundations in different age groups.

Live two-way video versus face-to-face treatment for depression, anxiety, and obsessive-compulsive disorder: A 24-week randomized controlled trial.

AIM: Live two-way video, easily accessible from home via smartphones and other devices, is becoming a new way of providing psychiatric treatment. However, lack of evidence for real-world clinical setting effectiveness hampers its approval by medical insurance in some countries. Here, we conducted the first large-scale pragmatic, randomized controlled trial to determine the effectiveness of long-term treatment for multiple psychiatric disorders via two-way video using smartphones and other devices, which are currently the primary means of telecommunication. METHODS: This randomized controlled trial compared two-way video versus face-to-face treatment for depressive disorder, anxiety disorder, and obsessive-compulsive disorder in the subacute/maintenance phase during a 24-week period. Adult patients with the above-mentioned disorders were allocated to either a two-way video group (≥50% video sessions) or a face-to-face group (100% in-person sessions) and received standard treatment covered by public medical insurance. The primary outcome was the 36-Item Short-Form Health Survey Mental Component Summary (SF-36 MCS) score. Secondary outcomes included all-cause discontinuation, working alliance, adverse events, and the severity rating scales for each disorder. RESULTS: A total of 199 patients participated in this study. After 24 weeks of treatment, two-way video treatment was found to be noninferior to face-to-face treatment regarding SF-36 MCS score (48.50 vs 46.68, respectively; p < 0.001). There were no significant differences between the groups regarding most secondary end points, including all-cause discontinuation, treatment efficacy, and satisfaction. CONCLUSION: Two-way video treatment using smartphones and other devices, was noninferior to face-to-face treatment in real-world clinical settings. Modern telemedicine, easily accessible from home, can be used as a form of health care.

Gender and age influence the association between gait speed and mild cognitive impairment in community-dwelling Japanese older adults: from the Japan Prospective Studies Collaboration for Ageing and Dementia (JPSC-AD).

BACKGROUND: Studies have shown that decreased gait speed is associated with impaired cognitive function. However, whether this association is equivalent across ages or genders in the older population remains unclear. Thus, we examined the association between mild cognitive impairment (MCI) and gait speed emphasising the influence of age and gender. METHODS: Overall, 8233 Japanese participants aged ≥65 years were enrolled in this cross-sectional study between 2016 and 2018. After stratification by gender and age group, the participants' gait speeds were divided into quintiles, and the difference in MCI prevalence at each gait speed quintile was calculated. Logistic regression analyses were performed to assess the odds of MCI for each quintile and to assess the influence of age and gender. RESULTS: Males had a consistently higher prevalence of MCI than females. The odds of MCI were increased as gait speed decreased. Logistic regression analyses revealed that in the multivariable-adjusted model 2, the odds ratios (95% confidence interval; CI) for MCI were 2.02 (1.47-2.76) for females and 1.75 (1.29-2.38) for males in the slowest gait speed quintiles compared to the fastest quintile. In the stratified analyses, only males showed an age-dependent increase in the associations between gait speed and MCI, while females exhibited comparable associations across age groups. CONCLUSIONS: Reduced gait speed was associated with increased odds of MCI, and this association may vary according to gender and age. Therefore, gait speed could serve as a valuable screening tool for MCI, with gender- and age-dependent clinical implications.

A comparative analysis of dementia inpatient characteristics: results from a nationwide survey of different care facilities in Japan.

BACKGROUND: In Japan, the number of dementia patients admitted to hospitals and other care facilities has been increasing and their hospital stays prolonged. Until now, there has been no study examining the differences between patients in psychiatric hospitals and other care facilities. Here we attempt a comparative analysis of characteristics of dementia patients in psychiatric hospitals and other types of facilities based on a nationwide survey. METHOD: A nationwide, cross-sectional survey was conducted in 2009-2011. Questionnaires were sent to randomly selected facilities and asked about each facility's status as of September 2009 and about individuals with dementia residing in each facility during the 2008 fiscal year. The portion about individuals consisted of items to assess eligibility for the Long-Term Care Insurance programme. Based on data from 6121 patients residing in seven different types of facilities, features of dementia patients in psychiatric hospitals and differences among facilities were analyzed. RESULTS: There was a significant difference in average age, activities of daily living level, and dementia severity level among the seven types of facilities. The average age in all types of facilities, except for psychiatric hospitals, was higher than the national average life expectancy of 82.59 years. The results of the study revealed that in psychiatric hospitals the proportion of men, those aged <75 years, demented patients with severe behavioural and psychological symptoms of dementia, and those with frontotemporal dementia was significantly greater than in other types of facilities. In other Long-Term Care Insurance care facilities, dementia patients >80 years and women accounted for 80% of all patients. CONCLUSION: Result showed that dementia patients in psychiatric hospitals had a higher proportion of men, younger age groups, and severe dementia than other types of facilities. These features contrast markedly with status of dementia patients in other Long-Term Care Insurance care facilities. In order to facilitate dementia patients' early discharge from psychiatric hospitals to other care facilities or to home, further fulfillment care services corresponding to severe dementia and early-onset dementia may be needed.

Amyloid-ß prediction machine learning model using source-based morphometry across neurocognitive disorders.

Previous studies have developed and explored magnetic resonance imaging (MRI)-based machine learning models for predicting Alzheimer's disease (AD). However, limited research has focused on models incorporating diverse patient populations. This study aimed to build a clinically useful prediction model for amyloid-beta (Aß) deposition using source-based morphometry, using a data-driven algorithm based on independent component analyses. Additionally, we assessed how the predictive accuracies varied with the feature combinations. Data from 118 participants clinically diagnosed with various conditions such as AD, mild cognitive impairment, frontotemporal lobar degeneration, corticobasal syndrome, progressive supranuclear palsy, and psychiatric disorders, as well as healthy controls were used for the development of the model. We used structural MR images, cognitive test results, and apolipoprotein E status for feature selection. Three-dimensional T1-weighted images were preprocessed into voxel-based gray matter images and then subjected to source-based morphometry. We used a support vector machine as a classifier. We applied SHapley Additive exPlanations, a game-theoretical approach, to ensure model accountability. The final model that was based on MR-images, cognitive test results, and apolipoprotein E status yielded 89.8% accuracy and a receiver operating characteristic curve of 0.888. The model based on MR-images alone showed 84.7% accuracy. Aß-positivity was correctly detected in non-AD patients. One of the seven independent components derived from source-based morphometry was considered to represent an AD-related gray matter volume pattern and showed the strongest impact on the model output. Aß-positivity across neurological and psychiatric disorders was predicted with moderate-to-high accuracy and was associated with a probable AD-related gray matter volume pattern. An MRI-based data-driven machine learning approach can be beneficial as a diagnostic aid.

Decreased short-latency afferent inhibition in individuals with mild cognitive impairment: A TMS-EEG study.

TMS combined with EEG (TMS-EEG) is a tool to characterize the neurophysiological dynamics of the cortex. Among the TMS paradigms, short-latency afferent inhibition (SAI) allows the investigation of inhibitory effects mediated by the cholinergic system. The aim of this study was to compare cholinergic function in the DLPFC between individuals with mild cognitive impairment (MCI) and healthy controls (HC) using TMS-EEG with the SAI paradigm. In this study, 30 MCI and 30 HC subjects were included. The SAI paradigm consisted of 80 single pulse TMS and 80 SAI stimulations applied to the left DLPFC. N100 components, global mean field power (GMFP) and total power were calculated. As a result, individuals with MCI showed reduced inhibitory effects on N100 components and GMFP at approximately 100 ms post-stimulation and on ß-band activity at 200 ms post-stimulation compared to HC. Individuals with MCI showed reduced SAI, suggesting impaired cholinergic function in the DLPFC compared to the HC group. We conclude that these findings underscore the clinical applicability of the TMS-EEG method as a powerful tool for assessing cholinergic function in individuals with MCI.

Social impact of brain fog and analysis of risk factors: Long COVID in Japanese population.

OBJECTIVE: To reveal the clinical features and assess risk factors linked to brain fog and its societal implications, including labor productivity, providing valuable insights for the future care of individuals who have experienced coronavirus disease 2019 (COVID-19). METHODS: We analyzed a comprehensive cohort dataset comprising 1,009 patients with COVID-19 admitted to Japanese hospitals. To assess brain fog, we analyzed patients who responded to a questionnaire indicating symptoms such as memory impairment and poor concentration. RESULTS: The prevalence of brain fog symptoms decreased 3 months posthospitalization but remained stable up to 12 months. Neurological symptoms such as taste and smell disorders and numbness at hospitalization correlated with a higher frequency of identifying brain fog as a long COVID manifestation. Our findings indicated that advanced age, female sex, a high body mass index, oxygen required during hospitalization, chronic obstructive pulmonary disease, asthma, and elevated C-reactive protein and elevated D-dimer levels were risk factors in patients exhibiting brain fog. Additionally, we demonstrated the negative impact of brain fog on labor productivity by presenteeism scores. INTERPRETATIONS: This study clarified the clinical characteristics of patients experiencing brain fog as a long COVID manifestation, specifically emphasizing neurological symptoms during hospitalization and their correlation with brain fog. Additionally, the study identified associated risk factors for its onset and revealed that the emergence of brain fog was linked to a decline in labor productivity.

Performance of plasma Aß42/40, measured using a fully automated immunoassay, across a broad patient population in identifying amyloid status.

BACKGROUND: Plasma biomarkers have emerged as promising screening tools for Alzheimer's disease (AD) because of their potential to detect amyloid ß (Aß) accumulation in the brain. One such candidate is the plasma Aß42/40 ratio (Aß42/40). Unlike previous research that used traditional immunoassay, recent studies that measured plasma Aß42/40 using fully automated platforms reported promising results. However, its utility should be confirmed using a broader patient population, focusing on the potential for early detection. METHODS: We recruited 174 participants, including healthy controls (HC) and patients with clinical diagnoses of AD, frontotemporal lobar degeneration, dementia with Lewy bodies/Parkinson's disease, mild cognitive impairment (MCI), and others, from a university memory clinic. We examined the performance of plasma Aß42/40, measured using the fully automated high-sensitivity chemiluminescence enzyme (HISCL) immunoassay, in detecting amyloid-positron emission tomography (PET)-derived Aß pathology. We also compared its performance with that of Simoa-based plasma phosphorylated tau at residue 181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL). RESULTS: Using the best cut-off derived from the Youden Index, plasma Aß42/40 yielded an area under the receiver operating characteristic curve (AUC) of 0.949 in distinguishing visually assessed 18F-Florbetaben amyloid PET positivity. The plasma Aß42/40 had a significantly superior AUC than p-tau181, GFAP, and NfL in the 167 participants with measurements for all four biomarkers. Next, we analyzed 99 participants, including only the HC and those with MCI, and discovered that plasma Aß42/40 outperformed the other plasma biomarkers, suggesting its ability to detect early amyloid accumulation. Using the Centiloid scale (CL), Spearman's rank correlation coefficient between plasma Aß42/40 and CL was -0.767. Among the 15 participants falling within the CL values indicative of potential future amyloid accumulation (CL between 13.5 and 35.7), plasma Aß42/40 categorized 61.5% (8/13) as Aß-positive, whereas visual assessment of amyloid PET identified 20% (3/15) as positive. CONCLUSION: Plasma Aß42/40 measured using the fully automated HISCL platform showed excellent performance in identifying Aß accumulation in the brain in a well-characterized cohort. This equipment may be useful for screening amyloid pathology because it has the potential to detect early amyloid pathology and is readily applied in clinical settings.

Impact of Amyloid and Tau PET on Changes in Diagnosis and Patient Management.

BACKGROUND AND OBJECTIVES: Previous studies have evaluated the diagnostic effect of amyloid PET in selected research cohorts. However, these studies did not assess the clinical impact of the combination of amyloid and tau PETs. Our objective was to evaluate the association of the combination of 2 PETs with changes in diagnosis, treatment, and management in a memory clinic cohort. METHODS: All participants underwent amyloid [18F]florbetaben PET and tau PET using [18F]PI-2620 or [18F]Florzolotau, which are potentially useful for the diagnosis of non-Alzheimer disease (AD) tauopathies. Dementia specialists determined a pre- and post-PET diagnosis that existed in both a clinical syndrome (cognitive normal [CN], mild cognitive impairment [MCI], and dementia) and suspected etiology, with a confidence level. In addition, the dementia specialists determined patient treatment in terms of ancillary investigations and management. RESULTS: Among 126 registered participants, 84.9% completed the study procedures and were included in the analysis (CN [n = 40], MCI [n = 25], AD [n = 20], and non-AD dementia [n = 22]). The etiologic diagnosis changed in 25.0% in the CN, 68.0% in the MCI, and 23.8% with dementia. Overall changes in management between pre- and post-PET occurred in 5.0% of CN, 52.0% of MCI, and 38.1% of dementia. Logistic regression analysis revealed that tau PET has stronger associations with change management than amyloid PET in all participants and dementia groups. DISCUSSION: The combination of amyloid and tau PETs was associated with changes in management and diagnosis of MCI and dementia, and the second-generation tau PET has a strong impact on the changes in diagnosis and management in memory clinics. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that the combination of amyloid and tau PETs was associated with changes in management and diagnosis of MCI and dementia.

Case report: Non-Alzheimer's disease tauopathy with logopenic variant primary progressive aphasia diagnosed using amyloid and tau PET.

We report a patient with logopenic variant primary progressive aphasia (lv-PPA) who was diagnosed as having non-Alzheimer's disease (AD) tauopathy after multiple biophysical/biological examinations, including amyloid and 18F-florzolotau tau positron emission tomography (PET), had been performed. A woman in her late 60s who had previously been diagnosed as having AD was referred to us for a further, detailed examination. She had been unaware of any symptoms at the time of AD diagnosis, but she subsequently became gradually aware of a speech impairment. She talked nearly completely and fluently, although she occasionally exhibited word-finding difficulty and made phonological errors during naming, word fluency testing, and sentence repetition; these findings met the criteria for the diagnosis of lv-PPA, which is known to be observed more commonly in AD than in other proteinopathies. Magnetic resonance imaging, single photon emission computed tomography, and plasma phosphorylated tau and plasma neurofilament light chain measurements showed an AD-like pattern. However, both 11C-Pittsburgh compound-B and 18F-florbetaben amyloid PET showed negative results, whereas 18F-florzolotau tau PET yielded positive results, with radio signals predominantly in the left superior temporal gyrus, middle temporal gyrus, supramarginal gyrus, and frontal operculum. Whole-genome sequencing revealed no known dominantly inherited mutations in AD or frontotemporal lobar degeneration genes, including the genes encoding amyloid precursor protein, microtubule-associated protein tau, presenilin 1 and 2. To the best of our knowledge, this patient was a rare case of lv-PPA who was diagnosed as having non-AD tauopathy based on the results of multiple examinations, including whole-genome sequencing, plasma measurement, and amyloid and 18F-florzolotau tau PET. This case underscores the clinicopathologically heterogeneous nature of this syndrome.

Neuroimaging-derived brain age is associated with life satisfaction in cognitively unimpaired elderly: A community-based study.

With the widespread increase in elderly populations, the quality of life and mental health in old age are issues of great interest. The human brain changes with age, and the brain aging process is biologically complex and varies widely among individuals. In this cross-sectional study, to clarify the effects of mental health, as well as common metabolic factors (e.g., diabetes) on healthy brain aging in late life, we analyzed structural brain MRI findings to examine the relationship between predicted brain age and life satisfaction, depressive symptoms, resilience, and lifestyle-related factors in elderly community-living individuals with unimpaired cognitive function. We extracted data from a community-based cohort study in Arakawa Ward, Tokyo. T1-weighted images of 773 elderly participants aged ≥65 years were analyzed, and the predicted brain age of each subject was calculated by machine learning from anatomically standardized gray-matter images. Specifically, we examined the relationships between the brain-predicted age difference (Brain-PAD: real age subtracted from predicted age) and life satisfaction, depressive symptoms, resilience, alcohol consumption, smoking, diabetes, hypertension, and dyslipidemia. Brain-PAD showed significant negative correlations with life satisfaction (Spearman's rs= -0.102, p = 0.005) and resilience (rs= -0.105, p = 0.004). In a multiple regression analysis, life satisfaction (p = 0.038), alcohol use (p = 0.040), and diabetes (p = 0.002) were independently correlated with Brain-PAD. Thus, in the cognitively unimpaired elderly, higher life satisfaction was associated with a 'younger' brain, whereas diabetes and alcohol use had negative impacts on life satisfaction. Subjective life satisfaction, as well as the prevention of diabetes and alcohol use, may protect the brain from accelerated aging.

Findings of 18 F-PI-2620 tau PET imaging in patients with Alzheimer's disease and healthy controls in relation to the plasma P-tau181 levels in a Japanese sample.

BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia worldwide. In AD, abnormal tau accumulates within neurons of the brain, facilitated by extracellular ß-amyloid deposition, leading to neurodegeneration, and eventually, cognitive impairment. As this process is thought to be irreversible, early identification of abnormal tau in the brain is crucial for the development of new therapeutic interventions. AIMS: 18 F-PI-2620 is one of the second-generation tau PET tracers with presumably less off-target binding than its predecessors. Although a few clinical studies have recently reported the use of 18 F-PI-2620 tau PET in patients with AD, its applicability to AD is yet to be thoroughly examined. METHODS: In the present pilot study, we performed 18 F-PI-2620 tau PET in seven cases of probable AD (AD group) and seven healthy controls (HC group). Standardized uptake value ratios (SUVR) in regions of interest (ROIs) in the medial temporal region and neocortex were compared between the AD and HC groups. Furthermore, correlations between regional SUVR and plasma p-tau181 as well as cognitive test scores were also analyzed. RESULTS: The uptake of 18 F-PI-2620 was distinctly increased in the AD group across all the ROIs. SUVR in all the target ROIs were significantly correlated with plasma p-tau181 levels, as well as with MMSE and ADAS-cog scores. DISCUSSION & CONCLUSION: Our results add to accumulating evidence suggesting that 18 F-PI-2620 is a promising tau PET tracer that allows patients with AD to be distinguished from healthy controls, although a study with a larger sample size is warranted.

Understanding psychiatric illness through natural language processing (UNDERPIN): Rationale, design, and methodology.

Introduction: Psychiatric disorders are diagnosed through observations of psychiatrists according to diagnostic criteria such as the DSM-5. Such observations, however, are mainly based on each psychiatrist's level of experience and often lack objectivity, potentially leading to disagreements among psychiatrists. In contrast, specific linguistic features can be observed in some psychiatric disorders, such as a loosening of associations in schizophrenia. Some studies explored biomarkers, but biomarkers have yet to be used in clinical practice. Aim: The purposes of this study are to create a large dataset of Japanese speech data labeled with detailed information on psychiatric disorders and neurocognitive disorders to quantify the linguistic features of those disorders using natural language processing and, finally, to develop objective and easy-to-use biomarkers for diagnosing and assessing the severity of them. Methods: This study will have a multi-center prospective design. The DSM-5 or ICD-11 criteria for major depressive disorder, bipolar disorder, schizophrenia, and anxiety disorder and for major and minor neurocognitive disorders will be regarded as the inclusion criteria for the psychiatric disorder samples. For the healthy subjects, the absence of a history of psychiatric disorders will be confirmed using the Mini-International Neuropsychiatric Interview (M.I.N.I.). The absence of current cognitive decline will be confirmed using the Mini-Mental State Examination (MMSE). A psychiatrist or psychologist will conduct 30-to-60-min interviews with each participant; these interviews will include free conversation, picture-description task, and story-telling task, all of which will be recorded using a microphone headset. In addition, the severity of disorders will be assessed using clinical rating scales. Data will be collected from each participant at least twice during the study period and up to a maximum of five times at an interval of at least one month. Discussion: This study is unique in its large sample size and the novelty of its method, and has potential for applications in many fields. We have some challenges regarding inter-rater reliability and the linguistic peculiarities of Japanese. As of September 2022, we have collected a total of >1000 records from >400 participants. To the best of our knowledge, this data sample is one of the largest in this field. Clinical Trial Registration: Identifier: UMIN000032141.

Development of medical device software for the screening and assessment of depression severity using data collected from a wristband-type wearable device: SWIFT study protocol.

Introduction: Few biomarkers can be used clinically to diagnose and assess the severity of depression. However, a decrease in activity and sleep efficiency can be observed in depressed patients, and recent technological developments have made it possible to measure these changes. In addition, physiological changes, such as heart rate variability, can be used to distinguish depressed patients from normal persons; these parameters can be used to improve diagnostic accuracy. The proposed research will explore and construct machine learning models capable of detecting depressive episodes and assessing their severity using data collected from wristband-type wearable devices. Methods and analysis: Patients with depressive symptoms and healthy subjects will wear a wristband-type wearable device for 7 days; data on triaxial acceleration, pulse rate, skin temperature, and ultraviolet light will be collected. On the seventh day of wearing, the severity of depressive episodes will be assessed using Structured Clinical Interview for DSM-5 (SCID-5), Hamilton Depression Rating Scale (HAMD), and other scales. Data for up to five 7-day periods of device wearing will be collected from each subject. Using wearable device data associated with clinical symptoms as supervisory data, we will explore and build a machine learning model capable of identifying the presence or absence of depressive episodes and predicting the HAMD scores for an unknown data set. Discussion: Our machine learning model could improve the clinical diagnosis and management of depression through the use of a wearable medical device. Clinical trial registration: [https://jrct.niph.go.jp/latest-detail/jRCT1031210478], identifier [jRCT1031210478].

Japanese Project for Telepsychiatry Evaluation during COVID-19: Treatment Comparison Trial (J-PROTECT): Rationale, design, and methodology.

INTRODUCTION: The COVID-19 pandemic has had a profound impact on the mental health of people around the world. Anxiety related to infection, stress and stigma caused by the forced changes in daily life have reportedly increased the incidence and symptoms of depression, anxiety disorder and obsessive-compulsive disorder. Under such circumstances, telepsychiatry is gaining importance and attracting a great deal of attention. However, few large pragmatic clinical trials on the use of telepsychiatry targeting multiple psychiatric disorders have been conducted to date. METHODS: The targeted study cohort will consist of adults (>18 years) who meet the DSM-5 diagnostic criteria for either (1) depressive disorders, (2) anxiety disorders, or (3) obsessive-compulsive and related disorders. Patients will be assigned in a 1:1 ratio to either a "telepsychiatry group" (at least 50% of treatments to be conducted using telemedicine, with at least one face-to-face treatment [FTF] within six months) or an "FTF group" (all treatments to be conducted FTF, with no telemedicine). Both groups will receive the usual treatment covered by public medical insurance. The study will utilize a master protocol design in that there will be primary and secondary outcomes for the entire group regardless of diagnosis, as well as the outcomes for each individual disorder group. DISCUSSION: This study will be a non-inferiority trial to test that the treatment effect of telepsychiatry is not inferior to that of FTF alone. This study will provide useful insights into the effect of the COVID-19 pandemic on the practice of psychiatry. TRIAL REGISTRATION: jRCT1030210037, Japan Registry of Clinical Trials (jRCT).

Comprehensive and long-term surveys of COVID-19 sequelae in Japan, an ambidirectional multicentre cohort study: study protocol.

INTRODUCTION: The rapid spread of COVID-19 posed a global burden. Substantial number of people died of the disease in the acute phase of infection. In addition, a significant proportion of patients have been reported to suffer from post-acute phase symptoms, sequelae of COVID-19, which may negatively influence the quality of daily living and/or socioeconomic circumstances of the patients. However, no previous study has comprehensively and objectively assessed the quality of life of patients by using existing international scales. Further, evidence of socioeconomic consequences among patients with COVID-19 is scarce. To address the multidimensional issues from sequelae of COVID-19, evidence from comprehensive surveys beyond clinical perspectives is critical that investigates health, and social determinants of disease progression as well as socioeconomic consequences at a large scale. METHODS AND ANALYSIS: In this study, we plan to conduct a nationwide and comprehensive survey for the sequelae of COVID-19 in a total of 1000 patients diagnosed at 27 hospitals throughout Japan. This study will evaluate not only the health-related status of patients from clinical perspectives but also the Health-related Quality of Life (HRQoL) scores, socioeconomic status and consequences to discuss the sequelae of the disease and the related risk factors. The primary endpoint is the frequency of long-term complications of COVID-19 infection. The secondary endpoints are risk factors for progression to sequelae of COVID-19 infection. The study will provide robust and important evidence as a resource to tackle the issues from the sequelae of COVID-19 from the multi-dimensional perspectives. ETHICS AND DISSEMINATION: This trial was approved by the Keio University School of Medicine Ethics Committee (20200243, UMIN000042299). The results of this study will be reported at a society meeting or published in a peer-reviewed journal.

The project for objective measures using computational psychiatry technology (PROMPT): Rationale, design, and methodology.

INTRODUCTION: Depressive and neurocognitive disorders are debilitating conditions that account for the leading causes of years lived with disability worldwide. However, there are no biomarkers that are objective or easy-to-obtain in daily clinical practice, which leads to difficulties in assessing treatment response and developing new drugs. New technology allows quantification of features that clinicians perceive as reflective of disorder severity, such as facial expressions, phonic/speech information, body motion, daily activity, and sleep. METHODS: Major depressive disorder, bipolar disorder, and major and minor neurocognitive disorders as well as healthy controls are recruited for the study. A psychiatrist/psychologist conducts conversational 10-min interviews with participants ≤10 times within up to five years of follow-up. Interviews are recorded using RGB and infrared cameras, and an array microphone. As an option, participants are asked to wear wrist-band type devices during the observational period. Various software is used to process the raw video, voice, infrared, and wearable device data. A machine learning approach is used to predict the presence of symptoms, severity, and the improvement/deterioration of symptoms. DISCUSSION: The overall goal of this proposed study, the Project for Objective Measures Using Computational Psychiatry Technology (PROMPT), is to develop objective, noninvasive, and easy-to-use biomarkers for assessing the severity of depressive and neurocognitive disorders in the hopes of guiding decision-making in clinical settings as well as reducing the risk of clinical trial failure. Challenges may include the large variability of samples, which makes it difficult to extract the features that commonly reflect disorder severity. TRIAL REGISTRATION: UMIN000021396, University Hospital Medical Information Network (UMIN).

Impact of Depressive Symptoms on Conversion from Mild Cognitive Impairment Subtypes to Alzheimer's Disease: A Community-Based Longitudinal Study.

BACKGROUND: While longitudinal studies have investigated the relationships between mild cognitive impairment (MCI) subtypes and dementia subtypes, the results have been contradictory. In addition, some research shows that depression accompanied by MCI might increase the risk of Alzheimer's disease (AD). OBJECTIVE: The aim of this study is to longitudinally investigate the relationships between MCI subtypes and dementia subtypes, with special attention to the effect of comorbid depressive symptoms in a Japanese rural community. METHODS: Non-demented participants (n = 802) completed a baseline and follow-up study. Outcomes were conversion to dementia especially AD, MCI, or no conversion. A complementary log-log analysis was conducted to investigate the risk of dementia and AD in amnestic MCI (aMCI) compared to nonamnestic MCI (naMCI) groups. The impact of depressive symptoms on the transition from MCI to AD and from cognitively normal to MCI or AD was also analyzed. RESULTS: The risk of developing dementia, in particular AD, for the aMCI group was significantly higher than that for the naMCI group. In the aMCI group, the presence of depressive symptoms increased the risk of developing AD, but depressive symptoms in the naMCI group did not. In the cognitively normal group, the presence of depressive symptoms increased the risk of aMCI but not naMCI or AD. CONCLUSION: MCI subtyping could be useful in finding a prodrome for dementia and in particular for AD. The differing impacts of depressive symptoms on the development of AD suggest that the relationship between depressive symptoms and cognitive impairment could differ in aMCI and naMCI patients.

A combination of supplements may reduce the risk of Alzheimer's disease in elderly Japanese with normal cognition.

A number of studies have examined the effect of a single supplement against Alzheimer's disease (AD) with conflicting results. Taking into account the complex and multifactorial nature of AD pathogenesis, multiple supplements may be more effective. Physical activity is another prospect against AD. An open-label intervention study was conducted to explore a potential protective effect of multiple supplements and physical activity. Their interaction was also examined. Participants were community-dwelling volunteers aged 65 or older as of May 2001 in a rural area of Japan. Among 918 cognitively normal participants included in the analyses, 171 took capsules daily for three years that contained n-3 polyunsaturated fatty acid, Ginkgo biloba leaf dry extracts, and lycopene. Two hundred and forty one participants joined the two-year exercise intervention that included a community center-based and a home-based exercise program. One-hundred and forty eight participated in both interventions. A standardized neuropsychological battery was administered at baseline in 2001, the first follow-up in 2004-2005, and the second in 2008-2009. The primary outcome was AD diagnosis at follow-ups. A complementary log-log model was used for survival analysis. A total of 76 participants were diagnosed with AD during follow-up periods. Higher adherence to supplementation intervention was associated with lower AD incidence in both unadjusted and adjusted models. Exercise intervention was also associated with lower AD incidence in the unadjusted model, but not in the adjusted model. We hypothesized that the combination of supplements acted in a complementary and synergistic fashion to bring significant effects against AD occurrence.