A retrospective study of pharmacological treatment in anorexia nervosa: 6-month and 12-month follow-up.

BACKGROUND: Anorexia nervosa (AN) is a serious and potentially life-threatening eating disorder characterized by starvation and malnutrition, a high prevalence of coexisting psychiatric conditions, marked treatment resistance, frequent medical complications, and a substantial risk of death. Body mass index (BMI) is a key measure of treatment outcome of AN and it is necessary to evaluate the long-term prognosis of AN. This study aimed to better assess the BMI course trend between different medications and timepoints in order to improve AN treatment in clinical practice. METHODS: During the period 2010-2021, we retrospectively reviewed historical data of all patients diagnosed with AN. There were two groups in this study, which were based on the duration of follow-up. Group A was a 6-month follow-up group, comprising 93 patients (mean age 19.6 ± 6.8 years), with BMI assessed at three consecutive time points: first outpatient visit (T0), three months follow-up (T3), and six months follow-up (T6). Group B was a 12-month follow-up group comprising 36 patients (mean age 17.0 ± 5.2 years) with BMI assessed at five consecutive time points: first outpatient visit (T0), three months follow-up (T3), six months follow-up (T6), nine months follow-up (T9), and twelve months follow-up (T12). In our study, we retrospectively compared BMI courses based on patients' usage of medication using the following variables: single medication, switching medications, combined medications, and without medications. The primary outcome measurement was BMI recorded at the 6-month follow-up and the 12-month follow-up respectively. In our study, which was conducted at Taichung Veterans General Hospital, we reviewed outpatient medical records of all patients with AN who were seen at the hospital during the period 2010-2021. RESULTS: In Group A (6-month follow-up), patients treated with antidepressants showed a mean BMI increase of 1.3 (p < 0.001); patients treated with antipsychotics showed a mean BMI increase of 1.1 (p = 0.01); patients treated with switching medications showed a mean BMI increase of 0.1 (p = 0.397); patients treated with combined medications showed a mean BMI increase of 0.5 (p = 0.208); and patients treated without medications showed a mean BMI increase of 0.1 (p = 0.821). The results indicated that patients with AN had a significant BMI increase after treatment with antidepressants and antipsychotics in the 6-month follow-up group. In Group B (12-month follow-up), patients treated with antidepressants showed a mean BMI increase of 2.7 (p < 0.001); patients treated with antipsychotics showed a mean BMI increase of 2.8 (p = 0.168); patients treated with switching medications showed a mean BMI decrease of 0.8 (p = 0.595); patients treated with combined medications showed a mean BMI increase of 1.6 (p = 0.368); and patients treated without medications showed a mean BMI increase of 1.0 (p = 0.262). The results indicated that patients with AN had a significant BMI increase after treatment with antidepressants at the 12-month follow-up. CONCLUSIONS: AN is a complex disease caused by multiple factors. Evaluating its long-term prognosis is crucial. Our study provides insights and highlights three key findings: 1) medication adherence is crucial in treating AN, 2) frequent switching of medications may not promote weight gain and may also require a re-establishment of rapport with patients with AN, and 3) pharmacotherapy, especially antidepressants, is more effective than no treatment. Further research is needed to confirm these findings.

Analysis of Heart Rate Variability in Response to Serious Games in Elderly People.

As the proportion of elderly people continues to grow, so does the concern about age-related cognitive decline. Serious games have been developed for cognitive training or treatment, but measuring the activity of the autonomic nervous system (ANS) has not been taken to account. However, cognitive functioning has been known to be heavily influenced by the autonomic nervous system (ANS), and ANS activity can be quantified using heart rate variability (HRV). This paper aims to analyze the physiological response in normal elderly people as they play two types of serious games using HRV features from electrocardiography (ECG). A wearable device designed in-house was used to measure ECG, and the data from this device was pre-processed using digital signal processing techniques. Ten HRV features were extracted, including time-domain, nonlinear, and frequency-domain features. The experiment proceeds as follows: rest for three minutes, play a cognitive aptitude game, rest for another three minutes, followed by two reaction time games. Data from thirty older adults (age: 65.9 ± 7.34; male: 15, female: 15) were analyzed. The statistical results show that there was a significant difference in the HRV between the two types of games. From this, it can be concluded that the type of game has a significant effect on the ANS response. This can be further used in designing games for the elderly, either for training or mood management.

Newly Diagnosed Bipolar Disorder and the Subsequent Risk of Erectile Dysfunction: A Nationwide Cohort Study.

BACKGROUND: Although erectile dysfunction (ED) is a common problem in men with mental disorders, there are few reports in the literature on the relation between bipolar disorder (BD) and ED. AIMS: To establish the incidence rate of ED in men with BD and assess the risk of ED in patients with BD according to type of treatment offered or no active treatment with medication during the 1st year of onset. METHODS: We identified 5,150 men with newly diagnosed BD using Taiwan's National Health Insurance Research Database. 2 matched controls per case were selected using the propensity score and a greedy matching method to obtain a balanced control group. Multivariate Cox regression analysis was used to examine the independent risk factors for ED, including obesity and comorbidities. Hazard ratios (HRs) for ED risk were calculated for the different psychotropic therapy groups, including antidepressants, antipsychotics, and mood stabilizers. OUTCOME: HRs for ED risk were calculated for the different psychotropic therapy groups, including antidepressants, antipsychotics, and mood stabilizers. Patients with BD had a significantly higher HR for an ED diagnosis than controls. RESULTS: Patients with BD had a higher HR for an ED diagnosis than controls. Although some psychotropic medications can increase the risk of ED, patients with BD not actively treated with medication still showed a higher risk of ED than controls. CLINICAL IMPLICATIONS: Because ED might be more prevalent in patients with BD than in the general population, clinicians should assess erectile function when selecting appropriate treatment for patients with BD to minimize the risk of ED as an annoying side effect and improve treatment compliance. STRENGTHS AND LIMITATIONS: This is the first large-scale population-based study to explore the association between BD and ED. A particular strength of this study is its nationwide, population-based study design, which afforded substantial statistical power for detecting subtle differences between the 2 cohorts, thereby minimizing selection bias. There are some limitations to the present study. (i) Data on other potential risk factors is lacking. (ii) Patient compliance and dose effect between psychotropic medication and ED could not be established. (iii) We could not assess the relation between ED and the severity and phases of BD. CONCLUSION: This cohort study found a temporal association between BD and subsequent ED in a large national sample of men. Clinicians should consider the risk of ED when choosing treatment for patients with BD. Hou P-H, Mao FC, Chang G-R, et al. Newly Diagnosed Bipolar Disorder and the Subsequent Risk of Erectile Dysfunction: A Nationwide Cohort Study. J Sex Med 2018;15:183-191.

The facial expression of schizophrenic patients applied with infrared thermal facial image sequence.

BACKGROUND: Schizophrenia is a neurological disease characterized by alterations to patients' cognitive functions and emotional expressions. Relevant studies often use magnetic resonance imaging (MRI) of the brain to explore structural differences and responsiveness within brain regions. However, as this technique is expensive and commonly induces claustrophobia, it is frequently refused by patients. Thus, this study used non-contact infrared thermal facial images (ITFIs) to analyze facial temperature changes evoked by different emotions in moderately and markedly ill schizophrenia patients. METHODS: Schizophrenia is an emotion-related disorder, and images eliciting different types of emotions were selected from the international affective picture system (IAPS) and presented to subjects during ITFI collection. ITFIs were aligned using affine registration, and the changes induced by small irregular head movements were corrected. The average temperatures from the forehead, nose, mouth, left cheek, and right cheek were calculated, and continuous temperature changes were used as features. After performing dimensionality reduction and noise removal using the component analysis method, multivariate analysis of variance and the Support Vector Machine (SVM) classification algorithm were used to identify moderately and markedly ill schizophrenia patients. RESULTS: Analysis of five facial areas indicated significant temperature changes in the forehead and nose upon exposure to various emotional stimuli and in the right cheek upon evocation of high valence low arousal (HVLA) stimuli. The most significant P-value (lower than 0.001) was obtained in the forehead area upon evocation of disgust. Finally, when the features of forehead temperature changes in response to low valence high arousal (LVHA) were reduced to 9 using dimensionality reduction and noise removal, the identification rate was as high as 94.3%. CONCLUSIONS: Our results show that features obtained in the forehead, nose, and right cheek significantly differed between moderately and markedly ill schizophrenia patients. We then chose the features that most effectively distinguish between moderately and markedly ill schizophrenia patients using the SVM. These results demonstrate that the ITFI analysis protocol proposed in this study can effectively provide reference information regarding the phase of the disease in patients with schizophrenia.

Analysis of EEG entropy during visual evocation of emotion in schizophrenia.

BACKGROUND: In this study, the international affective picture system was used to evoke emotion, and then the corresponding signals were collected. The features from different points of brainwaves, frequency, and entropy were used to identify normal, moderately, and markedly ill schizophrenic patients. METHODS: The signals were collected and preprocessed. Then, the signals were separated according to three types of emotions and five frequency bands. Finally, the features were calculated using three different methods of entropy. For classification, the features were divided into different sections and classification using support vector machine (principal components analysis on 95%). Finally, simple regression and correlation analysis between the total scores of positive and negative syndrome scale and features were used. RESULTS: At first, we observed that to classify normal and markedly ill schizophrenic patients, the identification result was as high as 81.5%, and therefore, we further explored moderately and markedly ill schizophrenic patients. Second, the identification rate in both moderately and markedly ill schizophrenic patient was as high as 79.5%, which at the Fz point signal in high valence low arousal fragments was calculated using the ApEn methods. Finally, the total scores of positive and negative syndrome scale were used to analyze the correlation with the features that were the five frequency bands at the Fz point signal. The results show that the p value was less than .001 at the beta wave in the 15-18 Hz frequency range.

Relationship among methadone dose, polymorphisms of dopamine D2 receptor and tri-dimensional personality questionnaire in heroin-addicted patients.

BACKGROUND: We investigated whether variation in the dopamine D2 receptor gene (DRD2) and tri-dimensional personality questionnaire (TPQ) scores could be used to aid adjustment of daily methadone requirements of heroin addicts. DRD2 TaqI B polymorphisms and TPQ scores were determined in 138 male Taiwanese heroin addicts who were receiving methadone treatment. Borderline index (harm avoidance + novelty seeking-reward dependence) was calculated for each subject, and three groups were defined: high (mean from all subjects plus 1 standard deviation, or greater), low (half of the calculated high score, or lower) and medium (all values between the high and low scores). RESULTS: No significant differences in age (p = 0.60), mean methadone dose (p = 0.75) or borderline index group (p = 0.25) were observed between subjects bearing the B1/B1, B1/B2 and B2/B2 DRD2 TaqI genotypes. Among the individuals with low (≤10), medium (11-20) and high (≥21) borderline index scores, there was a significant difference in mean methadone dose (p = 0.04), but not age (p = 0.90). Further analysis showed that mean methadone dose was significantly higher in subjects with low borderline index scores than in those with high scores (62.5 vs. 47.0 mg/day, p = 0.03). The odds ratio for a daily methadone requirement ≥60 mg (median dose across the 138 subjects) was 2.64-fold greater in the low borderline index group than in the high group (p = 0.04). CONCLUSIONS: Although the DRD2 TaqI B genotype was not associated with methadone use requirements, borderline index was revealed as a potential predictive marker for the adjustment of methadone dosage requirements in heroin addicts.

Integrating Evidence-Based Community-Care Services to Improve Schizophrenia Outcomes: A Preliminary Trial.

This aim of this preliminary experimental study was to integrate effective evidence-based community-care services that are subjected to heavy caseloads, and to then examine the effects on individuals with schizophrenia. Using a cluster sampling method, four homecare nurses were randomly assigned to either the experimental group or the comparison group. The nurses in the experimental group applied the following six identified effective elements: (1) established an alliance with their patients; (2) assessed patient-care needs; (3) considered both medical and social-care practices; (4) addressed patients' self-management of medication and their daily tasks; (5) provided crisis intervention; and (6) coordinated resources. The patients comprised 85 individuals with schizophrenia. In the experimental group, psychiatric homecare nurses were randomly assigned to implement integrated, evidence-based community-care services during a six-month follow-up period. Patients in the comparison group continued to receive their customary community care. In the experimental group, patient satisfaction scores, medication attitudes, and general functioning levels were significantly higher than in the comparison group. These preliminary findings indicate a potentially effective model for community care in areas where intensive case management cannot be provided.

Right and left amygdalae activation in patients with major depression receiving antidepressant treatment, as revealed by fMRI.

BACKGROUND: A differential contribution of the right and left amygdalae to affective information processing has been proposed. However, the direction of this lateralization has not been confirmed. In this study, we used a pre- and post-treatment (escitalopram) design to analyze the relative differences between neural activity in the right and left amygdalae during exposure to emotional stimuli in currently depressed patients. To the best of our knowledge, this study is to compare neural activity between the left and right amygdalae in people with depression. Our findings could lead to the development of parameters or biomarkers for depressive symptoms and treatment response. METHODS: We used a pre-post-test design without a control group. Twenty currently depressed participants underwent an emotion processing task during fMRI. These participants were then treated with an antidepressant for 6 weeks. We used amygdala region-of-interest analysis to evaluate the hemodynamic response during exposure to colored emotional pictures. RESULTS: In total, thirteen of the 20 participants were placed into a separate group based on degree of response to antidepressants. The partial response group had an averaged HDRS score of 10.75 ± 2.25 and an averaged DBOLDLR signal of 189.18 ± 140.23 (m1 = 8), and the remitted group had an averaged HDRS score of 4.80 ± 1.64 and an averaged DBOLDLR signal of 421.26 ± 109.19 (m2 = 5). Each individual had lateralized amygdala activity, and the direction of asymmetry persisted following treatment. Amygdala responses to four types of emotional stimuli did not significantly change (p > 0.05) with treatment in either the right or the left amygdala. However, the difference in neural activity between the right and left amygdalae was greater after treatment, and the variation in neural activity was larger in the left amygdala. CONCLUSIONS: We found that the response between the right and left amygdala did not differ in terms of time series, although activity increased after pharmaceutical treatment for each emotion tested. In the future, changes in BOLD signals as revealed by fMRI might be useful in evaluating the clinical manifestation of major depression.

Late-life depression and quality of life in a geriatric evaluation and management unit: an exploratory study.

BACKGROUND: Late-life depression is common among elderly patients. Ignorance of the health problem, either because of under-diagnosis or under-treatment, causes additional medical cost and comorbidity. For a better health and quality of life (QoL), evaluation, prevention and treatment of late-life depression in elderly patients is essential. METHODS: This study examined (1) the differences of clinical characteristics, degree of improvement on QoL and functionality on discharge between non-depressed and depressed elderly inpatients and (2) factors associated with QoL on discharge. Four hundred and seventy-one elderly inpatients admitted to a geriatric evaluation and management unit (GEMU) from 2009 to 2010 were enrolled in this study. Comprehensive geriatric assessment including the activities of daily living (ADL), geriatric depression scale, and mini-mental state examination were conducted. QoL was assessed using the European Quality of Life-5 Dimensions and the European Quality of Life-5 Dimensions Visual Analog Scale on discharge. Information on hospital stay and Charlson comorbidity index were obtained by chart review. Chi-square tests, independent t-tests, Mann-Whitney U tests and multiple linear regressions were used in statistical analysis. RESULTS: Worse QoL and ADL on discharge were found among the depressed. Depressive symptoms, female gender, duration of hospital stay, and rehabilitation were significant factors affecting QoL on discharge in linear regression models. CONCLUSIONS: The importance of the diagnosis and treatment of depression among elderly inpatients should not be overlooked during hospital stay and after discharge. Greater efforts should be made to improve intervention with depressed elderly inpatients.

Deep learning based decision tree ensembles for incomplete medical datasets.

BACKGROUND: In practice, the collected datasets for data analysis are usually incomplete as some data contain missing attribute values. Many related works focus on constructing specific models to produce estimations to replace the missing values, to make the original incomplete datasets become complete. Another type of solution is to directly handle the incomplete datasets without missing value imputation, with decision trees being the major technique for this purpose. OBJECTIVE: To introduce a novel approach, namely Deep Learning-based Decision Tree Ensembles (DLDTE), which borrows the bounding box and sliding window strategies used in deep learning techniques to divide an incomplete dataset into a number of subsets and learning from each subset by a decision tree, resulting in decision tree ensembles. METHOD: Two medical domain problem datasets contain several hundred feature dimensions with the missing rates of 10% to 50% are used for performance comparison. RESULTS: The proposed DLDTE provides the highest rate of classification accuracy when compared with the baseline decision tree method, as well as two missing value imputation methods (mean and k-nearest neighbor), and the case deletion method. CONCLUSION: The results demonstrate the effectiveness of DLDTE for handling incomplete medical datasets with different missing rates.

Risk of Cardiovascular Events in Schizophrenic Patients Treated with Paliperidone Palmitate Once-Monthly Injection (PP1M): A Population-Based Retrospective Cohort Study in Taiwan.

BACKGROUND: Schizophrenia is one of the leading causes of disability. Paliperidone palmitate once-monthly injection (PP1M) was developed to provide consistent drug delivery and improve medication adherence for maintenance treatment. It is well known that patients with schizophrenia have higher cardiovascular risks, however little is known about the cardiovascular risks of patients with schizophrenia treated with PP1M in Asia. OBJECTIVE: This study aimed to estimate the incidence of cardiovascular events after initiating PP1M treatment and evaluate the cardiovascular risk associations compared with oral second-generation antipsychotics (SGAs). METHODS: Data from Taiwan's National Health Insurance Research Database were used to identify a cohort of adult patients with schizophrenia who received any SGAs from 1 March 2012 to 31 December 2018. Patients who initiated PP1M treatment were enrolled for descriptive analysis of incidence rates. PP1M patients were propensity matched 1:1 to patients initiating a new oral SGA, for comparative analysis based on demographics, clinical characteristics and treatment history at baseline, in three-step matching procedures, following the prevalent new-user design to enhance comparability. Follow-up ended at the end of the treatment episode of index drug, death, last record available, or end of the study (31 December 2019). Study endpoints included serious cardiovascular events (including severe ventricular arrhythmia and sudden death), expanded serious cardiovascular events (which further included acute myocardial infarction and ischemic stroke), and cardiovascular hospitalizations. Risks of study endpoints between matched cohorts were compared using Cox regression. RESULTS: Overall, 11,023 patients initiating PP1M treatment were identified (49.5% were females; mean age of 43.2 [12.2] years). Overall incidences for serious cardiovascular events, expanded serious cardiovascular events, and cardiovascular hospitalizations were 3.92, 7.88 and 51.96 per 1000 person-years, respectively. In matched cohort analysis (N = 10,115), the hazard ratios (HRs) between initiating PP1M and a new oral SGA for serious cardiovascular events, expanded serious cardiovascular events, and cardiovascular hospitalizations were 0.86 (95% confidence interval [CI] 0.55-1.36), 0.88 (95% CI 0.63-1.21), and 0.78 (95% CI 0.69-0.89), respectively. CONCLUSION: This study reported the population-based incidence of cardiovascular events in schizophrenic patients initiating PP1M treatment. PP1M was not associated with increased risks of serious cardiovascular events but was potentially associated with lower risks of cardiovascular hospitalizations compared with oral SGAs.

Combining data discretization and missing value imputation for incomplete medical datasets.

Data discretization aims to transform a set of continuous features into discrete features, thus simplifying the representation of information and making it easier to understand, use, and explain. In practice, users can take advantage of the discretization process to improve knowledge discovery and data analysis on medical domain problem datasets containing continuous features. However, certain feature values were frequently missing. Many data-mining algorithms cannot handle incomplete datasets. In this study, we considered the use of both discretization and missing-value imputation to process incomplete medical datasets, examining how the order of discretization and missing-value imputation combined influenced performance. The experimental results were obtained using seven different medical domain problem datasets: two discretizers, including the minimum description length principle (MDLP) and ChiMerge; three imputation methods, including the mean/mode, classification and regression tree (CART), and k-nearest neighbor (KNN) methods; and two classifiers, including support vector machines (SVM) and the C4.5 decision tree. The results show that a better performance can be obtained by first performing discretization followed by imputation, rather than vice versa. Furthermore, the highest classification accuracy rate was achieved by combining ChiMerge and KNN with SVM.

Effects of paliperidone extended release on the symptoms and functioning of schizophrenia.

BACKGROUND: We aimed to explore relations between symptomatic remission and functionality evaluation in schizophrenia patients treated with paliperidone extended-release (ER), as seen in a normal day-to-day practice, using flexible dosing regimens of paliperidone ER. We explored symptomatic remission rate in patients treated with flexibly dosed paliperidone ER by 8 items of Positive and Negative Syndrome Scale (PANSS) and change of Personal and Social Performance (PSP) scale. METHOD: This was a 12-week multicenter, open-label, prospective clinical study conducted in in-patient and out-patient populations. Flexible dosing in the range 3-12 mg/day was used throughout the study. All subjects attended clinic visits on weeks 0, 4, 8, and 12 as usual clinical practice for the 12-week observation period. Data were summarized with respect to demographic and baseline characteristics, efficacy measurement with PANSS scale, PSP, and social functioning score, and safety observations. Descriptive statistics were performed to identify the retention rate at each visit as well as the symptomatic remission rate. Summary statistics of average doses the subjects received were based on all subjects participating in the study. RESULTS: A total of 480 patients were enrolled. Among them, 426 patients (88.8%) had evaluation at week 4 and 350 (72.9%) completed the 12-week evaluation. Patients with at least moderate severity of schizophrenia were evaluated as "mild" or better on PANSS scale by all 8 items after 12 weeks of treatment with paliperidone ER. There was significant improvement in patients' functionality as measured by PSP improvement and score changes. Concerning the other efficacy parameters, PANSS total scale, PSP total scale, and social functioning total scale at the end of study all indicated statistically significant improvement by comparison with baseline. The safety profile also demonstrated that paliperidone ER was well-tolerated without clinically significant changes after treatment administration. CONCLUSIONS: Although the short-term nature of this study may limit the potential for assessing improvements in function, it is noteworthy that in the present short-term study significant improvements in patient personal and social functioning with paliperidone ER treatment were observed, as assessed by PSP scale. TRIAL REGISTRATION: Clinical Trials. PAL-TWN-MA3.

Haloperidol and Other Antipsychotics Exposure before Endometrial Cancer Diagnosis: A Population-based Case-control Study.

Objective: Endometrial cancer is the most common malignancy of the female genital tract worldwide, and the associated relationship between endometrial cancer formation and various antipsychotics need to be confirmed. Methods: We conducted a case-control study by using data from Taiwan National Health Insurance Research Database to compare individual antipsychotic exposure between females with and without endometrial cancer. Among 14,079,089 females in the 12-year population-based national dataset, 9,502 females with endometrial cancer were identified. Their medical records of exposure to antipsychotics, including quetiapine, haloperidol, risperidone, olanzapine, amisulpride, clozapine, and aripiprazole, for up to 3 years before endometrial cancer diagnosis were reviewed. Daily dosage and cumulative exposure days were analyzed in the risky antipsychotic users. Additionally, the subsequent 5-year mortality rate of endometrial cancer among users of the risky antipsychotic were also analyzed. Results: Among endometrial cancer patients, the proportion of those who have used haloperidol before being diagnosed with endometrial cancer is significantly higher than other antipsychotic users. The significant odds ratio (OR) and a 95% confidence interval of 1.75 (1.31-2.34) were noted. Furthermore, haloperidol users were associated with a significantly higher 5-year mortality rate after getting endometrial cancer than non-users. Conclusion: There is a high correlation between the use of haloperidol and endometrial cancer formation. However, the underlying pathological biomechanisms require additional investigations.

A comparative study on long-term evoked auditory and visual potential responses between Schizophrenic patients and normal subjects.

BACKGROUND: The electrical signals measuring method is recommended to examine the relationship between neuronal activities and measure with the event related potentials (ERPs) during an auditory and a visual oddball paradigm between schizophrenic patients and normal subjects. The aim of this study is to discriminate the activation changes of different stimulations evoked by auditory and visual ERPs between schizophrenic patients and normal subjects. METHODS: Forty-three schizophrenic patients were selected as experimental group patients, and 40 healthy subjects with no medical history of any kind of psychiatric diseases, neurological diseases, or drug abuse, were recruited as a control group. Auditory and visual ERPs were studied with an oddball paradigm. All the data were analyzed by SPSS statistical software version 10.0. RESULTS: In the comparative study of auditory and visual ERPs between the schizophrenic and healthy patients, P300 amplitude at Fz, Cz, and Pz and N100, N200, and P200 latencies at Fz, Cz, and Pz were shown significantly different. The cognitive processing reflected by the auditory and the visual P300 latency to rare target stimuli was probably an indicator of the cognitive function in schizophrenic patients. CONCLUSIONS: This study shows the methodology of application of auditory and visual oddball paradigm identifies task-relevant sources of activity and allows separation of regions that have different response properties. Our study indicates that there may be slowness of automatic cognitive processing and controlled cognitive processing of visual ERPs compared to auditory ERPs in schizophrenic patients. The activation changes of visual evoked potentials are more regionally specific than auditory evoked potentials.

fMRI Investigation of Semantic Lexical Processing in Healthy Control and Alzheimer's Disease Subjects Using Naming Task: A Preliminary Study.

For decades, scientists have been trying to solve the problem of dementia, with no cure currently available. Semantic-lexical impairment is well established as the early critical sign of dementia, although there are still gaps in knowledge that must be investigated. In this study, we used fMRI to observe the neural activity of 31 subjects, including 16 HC (Healthy Control) and 15 AD (Alzheimer's Disease), who participated in the naming task. The neuropsychology profile of HC (Healthy Control) and AD (Alzheimer's Disease) are discussed in this study. The involvement of FG (Fusiform Gyrus) and IFG (Inferior Frontal Gyrus) shows dominant activation in both of the groups. We observed a decrease in neural activity in the AD group, resulting in semantic deficit problems in this preliminary study. Furthermore, ROI analysis was performed and revealed both hyperactivation and hypoactivation in the AD group. The compensatory mechanism demonstrated during the task, due to the effort required to identify an animal's name, represents the character profile of AD.

Risks of all-cause death and completed suicide in patients with schizophrenia/schizoaffective disorder treated with long-acting injectable or oral antipsychotics: A population-based retrospective cohort study in Taiwan.

BACKGROUND: Long-acting injectable (LAI) antipsychotics improve medication adherence in patients with schizophrenia and extend the duration of therapeutic drug levels but with administration of an increased dose. Real-world mortality data in patients prescribed LAIs are lacking. We conducted a population-based cohort study to estimate and compare the incidence rates of all-cause death and completed suicide in patients with schizophrenia/schizoaffective disorder exposed to LAIs and oral antipsychotics. METHODS: Patients with a diagnosis of schizophrenia/schizoaffective disorder between January 1, 2015 and November 30, 2019 were enrolled from the Taiwan National Health Insurance Research Database and linked to Death Registry records. Eligible patients were new antipsychotic users. Relative risks of death for each antipsychotic compared with oral paliperidone were evaluated using a Cox proportional hazard model adjusted for age, sex, Charlson Comorbidity Index, index year, bipolar or major depressive or other mood disorders, mental disorders due to drug use, and baseline hospitalization frequency. RESULTS: There were 228,791.08 person-years of follow-up (mean 2.48 years). The incidence rates of all-cause death in users of LAI paliperidone administered monthly (PP1M) and every 3 months (PP3M) were 7.40/1,000 person-years (95% confidence interval 5.94-9.11) and 9.93 (5.88-15.79), respectively. The incidences of completed suicide were 2.03/1,000 person-years (1.32-2.99) and 3.10 (1.14-6.88), respectively. No significant associations were observed between PP1M and PP3M compared to oral paliperidone in incidences of all-cause death or for completed suicide. DISCUSSION: No increased risk of all-cause death or completed suicide was observed in users of antipsychotic LAIs, including PP1M and PP3M.

Brain Structural Magnetic Resonance Imaging for Joint Independent Component Analysis in Schizophrenic Patients.

BACKGROUND: In past magnetic resonance imaging studies, normal participants and schizophrenia patients have usually been compared using imaging processing modes with only one parameter. A more extensive evaluation of significant differences between gray and white matter in Schizophrenic patents was necessary. METHODS: Voxel based morphometry was used to separate brain images into gray matter and white matter. Then, the images were mapped to Montreal Neurological Institute space, and DARTEL analytic template was applied for image calibration with statistical parametric mapping. Finally, joint independent component analysis was employed to analyze the gray and white matter of brain images from Schizophrenic patients and normal controls. In this study, joint independent component analysis was used to discriminate clinical differences in magnetic resonance imaging signals between Schizophrenic patients and normal controls. RESULTS: Region of interest analyses has repeatedly shown gray matter reduction in the superior temporal gyrus of Schizophrenic patients. CONCLUSION: These results strongly support previous studies regarding brain volume in schizophrenic patients. The connection networks in frontal and temporal lobes evidently did not differ between normal participants and schizophrenia patients.

Altered mRNA expressions for N-methyl-D-aspartate receptor-related genes in WBC of patients with major depressive disorder.

OBJECTIVE: Major depressive disorder (MDD) is a complex mental disorder. The lack of well-established biomarkers hinders its diagnosis, treatment, and new-drug development. N-methyl-D-aspartate receptor (NMDAR) dysfunction has been implicated in the pathogenesis of MDD. This study examined whether expressions of the NMDAR-related genes are characteristic of MDD. METHODS: Expressions of NMDAR-related genes including SRR, SHMT2, PSAT1, GCAT, GAD1, SLC1A4, NRG1 and COMT in peripheral WBCs of 110 patients with MDD (25 drug-naïve, 21 drug-free, and 64 medicated patients) and 125 healthy individuals were measured using quantitative PCR. RESULTS: The mRNA expression levels of SRR, PSAT1, GCAT, GAD1, NRG1 and COMT were significantly different among the four groups (all p < 0.05). For drug-naïve patients, the ΔΔCT values of SRR, PSAT1, GCAT, GAD1, and NRG1 mRNA expressions were significantly different from those in healthy individuals (all p < 0.05). The ROC analysis of the ΔΔCT values of the target genes for differentiating drug-naïve patients from healthy controls showed an excellent sensitivity (0.960) and modest specificity (0.640) (AUC = 0.889). Drug-free and medicated patients obtained less favorable AUC values while compared to healthy controls. The results for the age- and sex-matched cohort were similar to those of the unmatched cohort. CONCLUSIONS: This is the first study demonstrating that the peripheral mRNA expression levels of NMDAR-related genes may be altered in patients with MDD, especially drug-naïve individuals. The finding supports the NMDAR hypothesis of depression. Whether mRNA expresssion of NMDAR-related genes could serve as a potential biomarker of MDD deserves further investigations.

Outlier Removal in Model-Based Missing Value Imputation for Medical Datasets.

Many real-world medical datasets contain some proportion of missing (attribute) values. In general, missing value imputation can be performed to solve this problem, which is to provide estimations for the missing values by a reasoning process based on the (complete) observed data. However, if the observed data contain some noisy information or outliers, the estimations of the missing values may not be reliable or may even be quite different from the real values. The aim of this paper is to examine whether a combination of instance selection from the observed data and missing value imputation offers better performance than performing missing value imputation alone. In particular, three instance selection algorithms, DROP3, GA, and IB3, and three imputation algorithms, KNNI, MLP, and SVM, are used in order to find out the best combination. The experimental results show that that performing instance selection can have a positive impact on missing value imputation over the numerical data type of medical datasets, and specific combinations of instance selection and imputation methods can improve the imputation results over the mixed data type of medical datasets. However, instance selection does not have a definitely positive impact on the imputation result for categorical medical datasets.