Outcome of patients with dual diagnosis in secondary psychiatric care

Background: Dual diagnosis (DD) is a common co-morbidity of mental illness and substance use disorder (SUD) and patients with DD are prone to complications. Better knowledge on the outcome, mortality and management of patients with DD in usual secondary psychiatric care would help to inform improved treatment strategies in the future. Aims: To explore the functional outcome and mortality of patients with DD receiving psychiatric treatment. To assess the recognition of substance use disorders (SUDs) in terms of diagnosis, and the associations of clinically diagnosed SUDs with treatment-related variables. Methods: The sample of 330 patients was collected by screening all currently treated patients with the Alcohol Use Disorders Identification Test (AUDIT) and a question about other substances used. The inclusion criteria were AUDIT?>7 and/or reported use of other substances during the preceding 12 months. The Global Assessment of Functioning scale was used to assess functional outcomes during a 2-year follow-up. Information concerning treatment and patient characteristics was collected retrospectively. Results: Level of functioning remained stable among all study patients during follow-up. The mortality rate was not increased. Effective medication use was associated with improved functional outcomes. SUDs were underdiagnosed. A clinically diagnosed SUD seemed to have an impact on the regularity of appointments and the doses of prescribed medications. Conclusions: Given our results suggesting a stable level of functioning, patients with DD appear to be well managed within secondary psychiatric care. Attention should be paid to more precise diagnostics of SUDs and to effective use of medication.     

Unmet health care and health care utilization

The objective of this study is to examine the causal effect of health care utilization on unmet health care needs. An IV approach deals with the endogeneity between the use of health care services and unmet health care, using the presence of drug insurance and the number of physicians by health region as instruments. We employ three cycles of the Canadian Community Health Survey confidential master files (2003, 2005, and 2014). We find a robustly negative relationship between health care use and unmet health care needs. One more visit to a medical doctor on average decreases the probability of reporting unmet health care needs by 0.014 points. The effect is negative for the women‐only group whereas it is statistically insignificant for men; similarly, the effect is negative for urban dwellers but insignificant for rural ones. Health care use reduces the likelihood of reporting unmet health care. Policies that encourage the use of health care services, like increasing the coverage of public drug insurance and increasing after hours accessibility of physicians, can help reduce the likelihood of unmet health care.     

Stochastic approximation EM for large-scale exploratory IRT factor analysis

A stochastic approximation EM algorithm (SAEM) is described for exploratory factor analysis of dichotomous or ordinal variables. The factor structure is obtained from sufficient statistics that are updated during iterations with the Robbins-Monro procedure. Two large-scale simulations are reported that compare accuracy and CPU time of the proposed SAEM algorithm to the Metropolis-Hasting Robbins-Monro procedure and to a generalized least squares analysis of the polychoric correlation matrix. A smaller-scale application to real data is also reported, including a method for obtaining standard errors of rotated factor loadings. A simulation study based on the real data analysis is conducted to study bias and error estimates. The SAEM factor algorithm requires minimal lines of code, no derivatives, and no large-matrix inversion. It is programmed entirely in R.     

Airway obstruction lability helps distinguish levels of disease activity in asthma

Classifying disease activity in asthma relies on clinical and physiological variables, but these variables do not capture all aspects of asthma that distinguish levels of disease activity. We used data from two pivotal trials of montelukast in asthma to classify disease activity as "high" or "low". We performed a principal component analysis (PCA) of disease activity using 21 efficacy outcome variables, including several novel derived outcome variables reflecting clinical and airway obstruction lability. Then we performed discriminant analysis (DA) based on disease activity classification. PCA revealed 6 factors (daytime asthma control, nighttime-predominant asthma control, airway obstruction, exacerbations, clinical lability, airway obstruction lability) that explained 76% of the variance between outcome variables. Although airway obstruction lability (comprising both diurnal variability in peak expiratory flow and diurnal variability in β-agonist use) accounted for only 6% of the explained variance in PCA, in DA it was more accurate (canonical coefficient 0.75) than traditional measures of asthma severity such as obstruction (-0.54) and daytime control (-0.56) in distinguishing between high and low disease activity. We conclude that airway obstruction lability, a parameter not typically captured in clinical trials, may contribute to more complete assessment of asthma disease activity and may define an emerging clinical target of future therapy.     

瓜蒌皮提取物对PDGF-BB所致血管平滑肌细胞增殖周期的影响

目的 研究瓜蒌皮提取物对血小板源生长因子BB所致血管平滑肌细胞增殖周期的影响并探讨其可能机制.方法 组织块贴块法培养SD大鼠胸主动脉平滑肌细胞,3H-TdR掺入观察瓜蒌皮提取物(10、20和30mg/L)对血小板源生长因子BB(20 μg/L)所致血管平滑肌细胞DNA合成的影响;流式细胞仪分析细胞增殖周期;real time RT-PCR检测血管平滑肌细胞中c-fos、c-myc mRNA表达.结果 血小板源生长因子BB可明显升高细胞每分钟脉冲数(P＜0.01),并增加S期细胞比例而降低G0/G1期细胞比例(P＜0.01),并上调c-fos、c-myc mRNA表达(P＜0.01).瓜蒌皮提取物各浓度组均明显抑制血小板源生长因子BB诱导的每分钟脉冲数升高(P＜0.01),降低S期细胞比例而升高G0/G1期细胞比例,明显下调血小板源生长因子BB所致的c-fos、c-myc mRNA高表达(P＜0.01).结论 瓜蒌皮提取物通过阻止血管平滑肌细胞由G0/G1期进入S期而抑制血小板源生长因子BB所致的增殖,其作用机制可能与降低细胞内c-fos、c-myc mRNA高表达有关.     

Contextual control over derived relational responding in a teenager with autism

The derived relational repertoire of a teenager with autism spectrum disorder was tested in two slightly different contexts using a multiple treatments reversal design. Both contexts involved match-to-sample training and testing with abstract stimuli, but one involved referring to the stimuli as the names and sounds of “animals.” In the latter context, training of baseline relations was more efficient and derivation was shown to be more likely. This demonstrates the importance of contextual control over derived relational responding and suggests that the animal context may be a useful one for assessing and training derived relations for individuals in which the derived relational repertoire is not as robustly established across contexts.