Diffusion kurtosis imaging (DKI) is an extension of diffusion tensor imaging (DTI), exhibiting improved sensitivity and specificity in detecting developmental and pathological changes in neural ...tissues. However, little attention was paid to the performances of DKI and DTI in detecting white matter abnormality in schizophrenia. In this study, DKI and DTI were performed in 94 schizophrenia patients and 91 sex- and age-matched healthy controls. White matter integrity was assessed by fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), mean kurtosis (MK), axial kurtosis (AK) and radial kurtosis (RK) of DKI and FA, MD, AD and RD of DTI. Group differences in these parameters were compared using tract-based spatial statistics (TBSS) (P < 0.01, corrected). The sensitivities in detecting white matter abnormality in schizophrenia were MK (34%) > AK (20%) > RK (3%) and RD (37%) > FA (24%) > MD (21%) for DKI, and RD (43%) > FA (30%) > MD (21%) for DTI. DKI-derived diffusion parameters (RD, FA and MD) were sensitive to detect abnormality in white matter regions (the corpus callosum and anterior limb of internal capsule) with coherent fiber arrangement; however, the kurtosis parameters (MK and AK) were sensitive to reveal abnormality in white matter regions (the juxtacortical white matter and corona radiata) with complex fiber arrangement. In schizophrenia, the decreased AK suggests axonal damage; however, the increased RD indicates myelin impairment. These findings suggest that diffusion and kurtosis parameters could provide complementary information and they should be jointly used to reveal pathological changes in schizophrenia.
Fractional anisotropy (FA) and mean diffusivity (MD) are the most frequently used metrics to investigate white matter impairments in mental disorders. However, these two metrics are derived from ...intra-voxel analyses and only reflect the diffusion properties solely within the voxel unit. Local diffusion homogeneity (LDH) is a newly developed inter-voxel metric which quantifies the local coherence of water molecule diffusion in a model-free manner. In this study, 94 schizophrenia patients and 91 sex- and age-matched healthy controls underwent diffusion tensor imaging (DTI) examinations. White matter integrity was assessed by FA, MD and LDH. Group differences in these metrics were compared using tract-based spatial statistics (TBSS). Compared with healthy controls, schizophrenia patients exhibited reduced FA and increased MD in the corpus callosum, cingulum, internal capsule, fornix and widespread superficial white matter in the frontal, parietal, occipital and temporal lobes. We also found decreased LDH in the corpus callosum, cingulum, internal capsule and fornix in schizophrenia. Our findings suggest that both intra-voxel and inter-voxel diffusion metrics are able to detect impairments in the anisotropic white matter regions, and intra-voxel diffusion metrics could detect additional impairments in the widespread isotropic white matter regions in schizophrenia.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This study was proposed to compare the relative efficacy and tolerability of the second and third generation AEDs for refractory epilepsy. The 50% responder rate (RR) was selected as the efficacy ...outcome whereas the incidence of dizziness and somnolence were considered to evaluate the tolerability of AEDs. Odds ratio (OR) and their 95% credible interval (CrI) were obtained using a consistency model and surface under the cumulative ranking curve (SUCRA) value was calculated to rank AEDs. Topiramate appeared to be significantly more effective than placebo, eslicarbazepine acetate, perampanel, pregabalin, zonisamide, gabapentin and lamotrigine with respect to the 50% RR (all OR > 1). Patients who were managed by eslicarbazepine acetate, perampanel, oxcarbazepine, topiramate and pregabalin were more likely to suffer from dizziness compared to those who receive placebo (all OR > 1). Perampanel, topiramate and pregabalin were related to elevated risks of somnolence compared to placebo (all OR > 1). Moreover, topiramate ranked highest with respect to 50% RR (SUCRA = 0.968) whereas levetiracetam appeared to have balanced efficacy and tolerability (SUCRA = 0.769, 0.743, 0.604 and 0.659). In conclusion, topiramate was the most efficacious AED, while levetiracetam was able to provide patients with balanced efficacy and tolerability.
ObjectivesAnxiety has been suggested to be associated with poor outcomes in patients with acute coronary syndrome (ACS). However, results of previous follow-up studies were inconsistent. The aim of ...this meta-analysis was to evaluate the association between anxiety and clinical outcomes in patients with ACS, and to investigate the potential role of depression underlying the above association.DesignA meta-analysis of prospective follow-up studies.SettingHospitals.ParticipantsPatients with ACS.InterventionsWe included related prospective follow-up studies up through 20 July 2019 that were identified by searching PubMed and Embase databases. A random-effect model was used for the meta-analysis. Anxiety was evaluated by validated instruments at baseline.Primary and secondary outcome measuresWe determined the association between anxiety and risks of mortality and adverse cardiovascular events (MACEs) in patients with ACS.ResultsOur analysis included 17 studies involving 39 038 patients wqith ACS. Anxiety was independently associated with increased mortality risk (adjusted risk ratio (RR) 1.21, 95% CI 1.07 to 1.37, p=0.002) and MACEs (adjusted RR 1.47, 95% CI 1.24 to 1.74, p<0.001) in patients with ACS. Subgroup analyses showed that depression may at least partly confound the association between anxiety and poor outcomes in patients with ACS. Adjustment of depression significantly attenuated the association between anxiety and MACEs (adjusted RR 1.25, 95% CI 1.04 to 1.52, p=0.02). Moreover, anxiety was not significantly associated with mortality risk after adjusting for depression (adjusted RR 0.88, 95% CI 0.66 to 1.17, p=0.37).ConclusionsAnxiety is associated with increased risk of mortality and MACEs in patients with ACS. However, at least part of the association may be confounded by concurrent depressive symptoms in these patients.
Work addiction (WA), which can impair personal relationships, engagement in recreational activities, and/or health, is a behavioral addiction. A tool for the early detection of WA in China is needed.
...The aim of this study was to develop and determine the validity and reliability of a Chinese version of the Bergen Work Addiction Scale (C-BWAS).
Two hundred social workers who provided post-discharge services for adolescents with non-suicidal self-injury (NSSI) were enrolled in this study. The construct validity of the C-BWAS was assessed by confirmatory factor analysis (CFA). Criterion validity was assessed by conducting Pearson correlation analyses of C-CWAS scores with Hamilton Depression Scale (HAM-D) and Hamilton Anxiety Scale (HAM-A) scores. Cronbach's α and the intra-class correlation coefficient (ICC) were used to evaluate the reliability of the C-BWAS.
CFA confirmed a one-dimensional structure of the C-BWAS with good construct validity indices comparative fit index (CFI) = 0.964, Tucker-Lewis index (TLI) = 0.951, root-mean-square error of approximation (RMSEA) = 0.079, and minimum discrepancy Ĉ/degrees of freedom (Cmin/DF) = 0.362. The standardized regression weights ranged from 0.523 to 0.753. All C-BWAS items loaded on one major factor (loading weights, 0.646-0.943). Coefficients of correlation between C-BWAS scores and HAM-D and HAM-A scores were 0.889 and 0.933, respectively. The Cronbach's α coefficient and ICC for the instrument was 0.837 and 0.905, respectively.
The presently developed C-BWAS showed very good reliability and acceptably validity. It can be employed as a useful tool for assessing WA severity in social workers who provide post-discharge services for adolescents with NSSI.
Due to recent advances in human genomic technologies, there have been explosive interests and extensive research on the genomics of schizophrenia, a severe psychiatric disorder characterized by ...social cognitive deficits, hallucinations, and delusions. These new technologies, including next-generation sequencing (NGS), genome-wide association studies (GWAS), and the Clustered Regularly Interspaced Short Palindromic Repeats-associated nuclease 9 (CRISPR/Cas9) genome editing platform are capable of interrogating and editing the genome directly. In the past few years, these efforts have led to the identification of important loci and genes susceptible to schizophrenia. The findings have increased our understanding of the underlying genetic causes of schizophrenia and aided in the development of new approaches for more effectively diagnosing and treating schizophrenia. Despite the substantial progress, there are several unanswered questions about the genomics of schizophrenia, and there are a number of potential shortcomings in the current literature considering the complexity of the disease and limits of the current technologies. In the present review, we assessed the existing literature on the genomics of schizophrenia, identifying the strengths and study design shortcomings from the following aspects: elucidation of the pathogenesis, early risk prediction and diagnosis, and the treatment of schizophrenia. Moreover, we have proposed solutions to overcome the shortcomings of past studies. Lastly, we have discussed the importance of developing multidisciplinary teams and global research groups in order to improve the lives of schizophrenic patients globally.
•Although current genomics findings have increased our understanding of the underlying genetic causes of schizophrenia, there are a number of potential shortcomings in the current literature.•In this review, we assessed the existing literature on the genomics of schizophrenia.•Moreover, we have proposed solutions to overcome the shortcomings of past studies.•Lastly, we have discussed the importance of developing multidisciplinary teams and global research groups in order to improve the lives of schizophrenic patients globally.
Abstract
Background
Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help ...precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity. This study aimed to investigate if the machine learning (ML)-based neuroanatomical and symptomatic subtypes of schizophrenia are associated.
Methods
A total of 314 schizophrenia patients and 257 healthy controls from four sites were recruited. Gray matter volume (GMV) and Positive and Negative Syndrome Scale (PANSS) scores were employed to recognize schizophrenia neuroanatomical and symptomatic subtypes using
K
-means and hierarchical methods, respectively.
Results
Patients with ML-based neuroanatomical subtype-1 had focally increased GMV, and subtype-2 had widespread reduced GMV than the healthy controls based on either
K
-means or Hierarchical methods. In contrast, patients with symptomatic subtype-1 had severe PANSS scores than subtype-2. No differences in PANSS scores were shown between the two neuroanatomical subtypes; similarly, no GMV differences were found between the two symptomatic subtypes. Cohen’s Kappa test further demonstrated an apparent dissociation between the ML-based neuroanatomical and symptomatic subtypes (
P
> 0.05). The dissociation patterns were validated in four independent sites with diverse disease progressions (chronic vs. first episodes) and ancestors (Chinese vs. Western).
Conclusions
These findings revealed a replicable dissociation between ML-based neuroanatomical and symptomatic subtypes of schizophrenia, which provides a new viewpoint toward understanding the heterogeneity of schizophrenia.
This study aimed to investigate alterations in brain function among different subtypes of auditory hallucinations (AH) in drug-naïve first episode schizophrenia patients. We recruited 20 patients ...with drug-naïve first episode schizophrenia who had constant commanding and commenting auditory verbal hallucinations (CCCAVH), 15 drug-naïve first episode schizophrenia patients who had nonverbal auditory hallucinations (NVAH), and 20 healthy controls to participate in this study. We used global functional connectivity density (gFCD) and one-way analysis of covariance to characterize differences in brain function between the two patient groups. Statistical significance was set at
P
< 0.05. As compared to controls, schizophrenia patients with CCCAVH demonstrated increased gFCD in the right Broca’s area, bilateral superior temporal gyri, hippocampus, bilateral insula, and anterior cingulate gyri, and decreased gFCD in the left temporoparietal junction (family-wise error FEW correct,
P
< 0.05). Schizophrenia patients with NVAH demonstrated increased gFCD in the bilateral superior temporal gyri and most of the components of the default mode network (DMN), and decreased gFCD in components of the executive control network (FWE correct,
P
< 0.05). We found that schizophrenia patients with CCCAVH and NVAH have distinct functional brain patterns. The features observed in patients with CCCAVH are consistent with the “inner speech” hypothesis of AH. Features of patients with NVAH suggest hyperactivity of the superior temporal gyrus and DMN, and hypoactivity of the prefrontal lobe.
Bipolar disorder (BD) is associated with a high risk of suicide. We used proton magnetic resonance spectroscopy (
1
H-MRS) to detect biochemical metabolite ratios in the bilateral prefrontal white ...matter (PWM) and hippocampus in 32 BD patients with suicidal ideation (SI) and 18 BD patients without SI, identified potential brain biochemical differences and used abnormal metabolite ratios to predict the severity of suicide risk based on the support vector machine (SVM) algorithm. Furthermore, we analyzed the correlations between biochemical metabolites and clinical variables in BD patients with SI. There were three main findings: (1) the highest classification accuracy of 88% and an area under the curve of 0.9 were achieved in distinguishing BD patients with and without SI, with N-acetyl aspartate (NAA)/creatine (Cr), myo-inositol (mI)/Cr values in the bilateral PWM, NAA/Cr and choline (Cho)/Cr values in the left hippocampus, and Cho/Cr values in the right hippocampus being the features contributing the most; (2) the above seven features could be used to predict Self-rating Idea of Suicide Scale scores (r = 0.4261,
p
= 0.0302); and (3) the level of neuronal function in the left hippocampus may be related to the duration of illness, the level of membrane phospholipid catabolism in the left hippocampus may be related to the severity of depression, and the level of inositol metabolism in the left PWM may be related to the age of onset in BD patients with SI. Our results showed that the combination of multiple brain biochemical metabolites could better predict the risk and severity of suicide in patients with BD and that there was a significant correlation between biochemical metabolic values and clinical variables in BD patients with SI.
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