Effect of age and disease on bone mass in Japanese patients with schizophrenia

BACKGROUND: There have been a limited number of studies comparing bone mass between patients with schizophrenia and the general population. The aim of this study was to compare the bone mass of schizophrenia patients with that of healthy subjects in Japan. METHODS: We recruited patients (n = 362), aged 48.8 ± 15.4 (mean ± SD) years who were diagnosed with schizophrenia or schizoaffective disorder based on the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV). Bone mass was measured using quantitative ultrasound densitometry of the calcaneus. The osteosono-assessment index (OSI) was calculated as a function of the speed of sound and the transmission index. For comparative analysis, OSI data from 832 adults who participated in the Iwaki Health Promotion Project 2009 was used as representative of the general community. RESULTS: Mean OSI values among male schizophrenic patients were lower than those in the general population in the case of individuals aged 40 and older. In females, mean OSI values among schizophrenic patients were lower than those in the general community in those aged 60 and older. In an analysis using the general linear model, a significant interaction was observed between subject groups and age in males. CONCLUSIONS: Older schizophrenic patients exhibit lower bone mass than that observed in the general population. Our data also demonstrate gender and group differences among schizophrenic patients and controls with regard to changes in bone mass associated with aging. These results indicate that intervention programs designed to delay or prevent decreased bone mass in schizophrenic patients might be tailored according to gender

Comparison of ankle-brachial pressure index and pulse wave velocity as markers of cognitive function in a community-dwelling population

<p>Abstract</p> <p>Background</p> <p>Vascular factors have been implicated in the development of cognitive decline and dementia. The purpose of this study is to determine the association of the Ankle Brachial pressure Index (ABI) and brachial-ankle Pulse Wave Velocity (ba-PWV) to cognitive impairment in a community-dwelling population.</p> <p>Methods</p> <p>The ABI and ba-PWV were measured using the volume-plethymographic apparatus in 388 subjects aged 60 years old and over. The Mini-Mental State Examination was also employed to measure global cognitive status. The effectiveness of the ABI and ba-PWV as putative markers of cognitive impairment were determined by using a multiple logistic regression analysis after adjusting for confounding factors.</p> <p>Results</p> <p>Subjects with poor cognition were significantly older and less well educated than those with normal cognition. According to the multiple logistic regression analysis, the lowest ABI tertile was found to be a significant independent risk factor (OR = 3.19, 95% CI = 1.30 to 7.82) of the cognitive impairment, whereas the highest brachial-ankle PWV tertile was not.</p> <p>Conclusions</p> <p>A low ABI was an independent risk factor for cognitive impairment in community-dwelling older populations, whereas a high ba-PWV may not be. Further research will be required to analyze ABI and PWV with greater accuracy.</p

A trial deep learning-based model for four-class histologic classification of colonic tumor from narrow band imaging

Abstract Narrow band imaging (NBI) has been extensively utilized as a diagnostic tool for colorectal neoplastic lesions. This study aimed to develop a trial deep learning (DL) based four-class classification model for low-grade dysplasia (LGD); high-grade dysplasia or mucosal carcinoma (HGD); superficially invasive submucosal carcinoma (SMs) and deeply invasive submucosal carcinomas (SMd) and evaluate its potential as a diagnostic tool. We collected a total of 1,390 NBI images as the dataset, including 53 LGD, 120 HGD, 20 SMs and 17 SMd. A total of 598,801 patches were trimmed from the lesion and background. A patch-based classification model was built by employing a residual convolutional neural network (CNN) and validated by three-fold cross-validation. The patch-based validation accuracy was 0.876, 0.957, 0.907 and 0.929 in LGD, HGD, SMs and SMd, respectively. The image-level classification algorithm was derived from the patch-based mapping across the entire image domain, attaining accuracies of 0.983, 0.990, 0.964, and 0.992 in LGD, HGD, SMs, and SMd, respectively. Our CNN-based model demonstrated high performance for categorizing the histological grade of dysplasia as well as the depth of invasion in routine colonoscopy, suggesting a potential diagnostic tool with minimal human inputs

Body composition in patients with schizophrenia: Comparison with healthy controls

<p>Abstract</p> <p>Background</p> <p>Recently, a relationship between obesity and schizophrenia has been reported. Although fat- mass and fat free mass have been shown to be more predictive of health risk than body mass index, there are limited findings about body composition among patients suffering from schizophrenia. The aim of this study is to compare the body composition of schizophrenia patients with that of healthy subjects in Japan.</p> <p>Methods</p> <p>We recruited patients (n = 204), aged 41.3 ± 13.8 (mean ± SD) years old with the DSM-IV diagnosis of schizophrenia who were admitted to psychiatric hospital using a cross-sectional design. Subjects' anthropometric measurements including weight, height, body mass index (BMI), and medications were also collected. Body fat, percent (%) body fat, fat- free mass, muscle mass, and body water were measured using the bioelectrical impedance analysis (BIA) method. Comparative analysis was performed with schizophrenic subjects and 204 healthy control individuals.</p> <p>Results</p> <p>In a multiple regression model with age, body mass index, and dose in chlorpromazine equivalents, schizophrenia was a significantly linked with more body fat, higher % body fat, lower fat- free mass, lower muscle mass, and lower body water among males. In females, schizophrenia had a significant association with lower % body fat, higher fat- free mass, higher muscle mass, and higher body water.</p> <p>Conclusions</p> <p>Our data demonstrate gender differences with regard to changes in body composition in association with schizophrenia. These results indicate that intervention programs designed to fight obesity among schizophrenic patients should be individualized according to gender.</p