Characteristics of theory of mind impairment and its relationship with clinical symptoms and neurocognition in patients with schizophrenia.

BACKGROUND: Schizophrenia (SCZ) is a mental disorder that can cause severe disability, including impairment of social cognition, which is considered a core feature of SCZ, and the Theory of Mind (ToM) is a core component of social cognition. Although many studies have confirmed the presence of ToM impairment in patients with SCZ, its characteristics in terms of different orders (first-order and second-order) and components remain unclear, and no studies have investigated the independent correlations between such impairment and clinical symptoms. Therefore, this study aimed to identify the characteristics of ToM impairment in patients with SCZ. METHODS: This study included 30 patients with SCZ and 30 healthy controls who were matched for age, sex, and level of education. The clinical symptoms of the patients with SCZ were evaluated using the Positive and Negative Symptom Scale (PANSS), and the neurocognitive ability of the subjects was evaluated using the Trail Making Test, Symbol Coding Test, and Digit Span Test. The degree of ToM impairment of the subjects at different stages (first- and second-order) and for individual components was evaluated using the Yoni task. Latent profile analysis and network analysis were conducted to identify and analyze the potential ToM performance types, and independent correlations were assessed between ToM impairment and clinical symptoms. RESULTS: The patients with SCZ exhibited significant first-order and second-order impairment (P < 0.05), and the second-order affective ToM component was mainly reflected by complex affective states (P = 0.003). The latent profile analysis revealed that ToM impairments in patients with SCZ could be classified into groups with complete, second-order, and comprehensive defects, whereas it was impossible to classify patients according to differences in the cognitive and affective ToM components. The Network analysis demonstrated that the cognitive component of ToM was associated with positive symptoms, whereas the affective ToM component was associated with negative symptoms. CONCLUSION: Patients with SCZ exhibited differences in order levels and ToM impairments, as well as different defect types. In addition, cognitive and affective ToM components may be related to different psychotic symptoms; therefore, understanding these differences could promote the rehabilitation of patients with SCZ.

Adaptively leveraging external data with robust meta-analytical-predictive prior using empirical Bayes.

The robust meta-analytical-predictive (rMAP) prior is a popular method to robustly leverage external data. However, a mixture coefficient would need to be pre-specified based on the anticipated level of prior-data conflict. This can be very challenging at the study design stage. We propose a novel empirical Bayes robust MAP (EB-rMAP) prior to address this practical need and adaptively leverage external/historical data. Built on Box's prior predictive p-value, the EB-rMAP prior framework balances between model parsimony and flexibility through a tuning parameter. The proposed framework can be applied to binomial, normal, and time-to-event endpoints. Implementation of the EB-rMAP prior is also computationally efficient. Simulation results demonstrate that the EB-rMAP prior is robust in the presence of prior-data conflict while preserving statistical power. The proposed EB-rMAP prior is then applied to a clinical dataset that comprises 10 oncology clinical trials, including the prospective study.

Development, Implementation, and Evaluation of an In-Hospital Optimized Early Warning Score for Patient Deterioration.

Background. Identification of patients at risk of deteriorating during their hospitalization is an important concern. However, many off-shelf scores have poor in-center performance. In this article, we report our experience developing, implementing, and evaluating an in-hospital score for deterioration. Methods. We abstracted 3 years of data (2014-2016) and identified patients on medical wards that died or were transferred to the intensive care unit. We developed a time-varying risk model and then implemented the model over a 10-week period to assess prospective predictive performance. We compared performance to our currently used tool, National Early Warning Score. In order to aid clinical decision making, we transformed the quantitative score into a three-level clinical decision support tool. Results. The developed risk score had an average area under the curve of 0.814 (95% confidence interval = 0.79-0.83) versus 0.740 (95% confidence interval = 0.72-0.76) for the National Early Warning Score. We found the proposed score was able to respond to acute clinical changes in patients' clinical status. Upon implementing the score, we were able to achieve the desired positive predictive value but needed to retune the thresholds to get the desired sensitivity. Discussion. This work illustrates the potential for academic medical centers to build, refine, and implement risk models that are targeted to their patient population and work flow.

Coupling of Spinosad Fermentation and Separation Process via Two-Step Macroporous Resin Adsorption Method.

In this paper, a two-step resin adsorption technology was investigated for spinosad production and separation as follows: the first step resin addition into the fermentor at early cultivation period to decrease the timely product concentration in the broth; the second step of resin addition was used after fermentation to adsorb and extract the spinosad. Based on this, a two-step macroporous resin adsorption-membrane separation process for spinosad fermentation, separation, and purification was established. Spinosad concentration in 5-L fermentor increased by 14.45 % after adding 50 g/L macroporous at the beginning of fermentation. The established two-step macroporous resin adsorption-membrane separation process got the 95.43 % purity and 87 % yield for spinosad, which were both higher than that of the conventional crystallization of spinosad from aqueous phase that were 93.23 and 79.15 % separately. The two-step macroporous resin adsorption method has not only carried out the coupling of spinosad fermentation and separation but also increased spinosad productivity. In addition, the two-step macroporous resin adsorption-membrane separation process performs better in spinosad yield and purity.