Haneyaguirre9450

nce. It may provide a more distinctive assessment of the functional capacity construct.

A growing body of neuroimaging research has revealed a relationship between blunted activation of the ventral striatum (VS) and apathy in schizophrenia. In contrast, the association between reduced striatal volume and apathy is less well established, while the relationship between VS function and structure in patients with schizophrenia remains an open question. Here, we aimed to replicate previous structural findings in a larger independent sample and to investigate the relationship between VS hypoactivation and VS volume.

We included brain structural magnetic resonance imaging (MRI) data from 60 patients with schizophrenia (SZ) that had shown an association of VS hypoactivation with apathy during reward anticipation and 58 healthy controls (HC). To improve replicability, we applied analytical methods employed in two previously published studies Voxel-based morphometry and the Multiple Automatically Generated Templates (MAGeT) algorithm. VS and dorsal striatum (DS) volume were correlated with apathy corr Finally, associations between reward-related VS function and structure should be further explored.Clozapine is an anti-psychotic drug that is known to be effective in the treatment of patients with chronic treatment-resistant schizophrenia (TRS-SCZ), commonly estimated to be around one third of all cases. However, clinicians sometimes delay the initiation of this drug because of its adverse side-effects. Therefore, identification of predictive biomarkers of clozapine response is extremely valuable to aid on-time initiation of clozapine treatment. In this study, we develop a machine learning (ML) algorithm based on the pre-treatment electroencephalogram (EEG) data sets to predict response to clozapine treatment in TRS-SCZs, where the treatment outcome, after at least one-year follow-up is determined using the Positive and Negative Syndrome Scale (PANSS). The ML algorithm has two steps 1) an effective connectivity named symbolic transfer entropy (STE) is applied to resting state EEG waveforms, 2) the ML algorithm is applied to STE matrix to determine whether a set of features can be found to discriminate most responder (MR) SCZ patients from least responder (LR) ones. The findings of this study revealed that the STE features could achieve an accuracy of 89.90%. This finding implies that analysis of pre-treatment EEG could contribute to our ability to distinguish MR from LR SCZs, and that the STE matrix may prove to be a promising tool for the prediction of the clinical response to clozapine.

The aim of this paper is to determine clinical factors related to hostility and disturbing and aggressive behaviour and to examine the effect of medication on these behaviours in FEP.

Data from phase I and II of the OPTiMiSE trial are used. Outcome measures are the hostility item of the Positive and Negative Syndrome Scale (PANSS P7) and the disturbing and aggressive behaviour domain of the Personal and Social Performance scale (PSP-D).

Moderate, severe or extreme hostility (PANSS P7>3) was present in 42 patients (9.4%). The PANSS P7 and PSP-D were low to moderate but significantly associated with the selected PANSS items delusions, hallucinatory behaviour, excitement, tension, uncooperativeness, unusual thought content, impulsivity, and lack of judgement and insight. In a subsample of 185 patients (41.5%) with baseline PANSS P7>1, the PANSS P7 and PSP-D scores improved in the first 4weeks of amisulpride treatment. This effect remained significant after controlling for baseline positive symptoms (PANSS P1-P6). No significant differences were found between olanzapine and amisulpride in the second phase of the trial.

Clinical risk factors such as poor impulse control, uncooperativeness and excitement could help clinicians in detecting and treating hostile and aggressive behaviour in FEP. Amisulpride could be an effective antipsychotic choice in the treatment of FEP patients who express hostile or aggressive behaviour. Future research is needed to compare the effects of amisulpride and olanzapine on hostility in FEP during the first weeks of treatment.

Clinical risk factors such as poor impulse control, uncooperativeness and excitement could help clinicians in detecting and treating hostile and aggressive behaviour in FEP. Amisulpride could be an effective antipsychotic choice in the treatment of FEP patients who express hostile or aggressive behaviour. Future research is needed to compare the effects of amisulpride and olanzapine on hostility in FEP during the first weeks of treatment.

Acute exacerbation of chronic obstructive pulmonary disease (COPD) results in deterioration of lung function and mortality. Previous prediction models have been designed for severe exacerbation of COPD, leading to readmission. However, these models lacked newly established predictors such as the eosinophil count. The present study developed a novel CO PD-re admission (CORE) score.

We retrospectively reviewed medical records of patients visiting Taipei Tzu Chi Hospital between January 1, 2014, and May 31, 2017. We analyzed all covariates by univariate and then multivariate logistic regressions. Numeric or ordinal variables showing statistical significance were transformed into dichotomous variables by cut-off values determined by the Youden Index. The CORE score was designed to predict one-year readmission rates.

A total of 625 patients were recruited. After analysis, the CORE score included five predictors (eosinophil count, lung function, triple inhaler therapy, previous hospitalization, and neuromuscular disease). We observed a highly linear relationship between the CORE score and COPD readmission (R=0.981; R

=0.963; P<0.001). see more The CORE score had a higher predictive accuracy than that for hospitalization in the previous year (area under the curve=0.703 vs. 0.619; P<0.001). Patients with higher CORE scores had a shorter time to first COPD readmission (P<0.001). Using the zero point as a reference, the hazard ratios for each score from 1 to 4 were 1.209, 2.211, 3.359, and 4.510, respectively.

The CORE score includes two novel predictors (eosinophil count and triple inhaler therapy). The model has a high predictive power for one-year COPD readmission.

The CORE score includes two novel predictors (eosinophil count and triple inhaler therapy). The model has a high predictive power for one-year COPD readmission.