Unimaginable imagining: Fantasies and works off the margin

Abstract

Since the 1940s art therapists have often worked with marginalised people and marginalised imaginations. The expressions of this can be strikingly original, yet fit uneasily with any genre. Artists becoming therapists were presented with radical opportunities to witness, support and possibly befriend those possessing, or possessed by, ways of seeing, feeling and thinking contradicting conventional consciousness. This was particularly true in the large populations inhabiting psychiatric institutions in Britain until the 1980s. This paper describes the work and ‘performances’ of five people; three of whom it was possible to know well, and the unusual ways of being of the others could only be experienced. The approach is not ‘scientifically’ clinical but more like anthropological reportage and stories about ‘characters’. Change is of course aim of psychotherapy, but so is witnessed. No matter what traumas lay in their past, over time they had become who they most memorably were.     

An Analysis of Calls to a Drug Crisis Intervention Service

Abstract

There is little medical information available about gamma- hydroxybutyrate (GHB) or gamma-butyrolactone (GBL) dependence or withdrawal. In this study the authors treated and reviewed multiple cases of GHB and GBL withdrawal in high-dose users. Five patients during nine hospitalizations were treated for GHB or GBL withdrawal. The authors describe a spectrum of GHB or GBL withdrawal from mild to severe and discuss medications used for treatment. They conclude that patients with GHB or GBL withdrawal may present with agitated psychosis, delirium, and autonomic instability. In this sample, relapse to GHB or GBL use occurred soon after treatment of withdrawal.     

螺旋CT在老年精神病合并肠梗阻患者诊断中的价值分析

目的：分析螺旋CT在老年精神病合并肠梗阻患者诊断中的价值。方法：选取我院收治的老年精神病合并肠梗阻患者50例,首先进行X线腹部平片的检查,后给予螺旋CT检查,对不同检测手段对患者的诊断结果进行分析。结果：螺旋CT准确诊断比例、误诊比例、肠梗阻性质、部位、患者满意度等均明显优越于X线检查,差异具有统计学意义（ P＜0．05）。结论：螺旋CT扫描检查对老年精神病合并肠梗阻患者诊断准确性高,误诊比例低,在老年精神病合并肠梗阻患者的诊断和治疗中具有较高的临床意义。     

Management of psychosis in patients with Alzheimer’s disease: focus on aripiprazole

Psychosis of Alzheimer’s disease (AD) is characterized by delusions or hallucinations and may be associated with agitation, negative symptoms or depression. There are no psychotropic medications that are approved by the US FDA for the treatment of psychosis of AD. However, atypical antipsychotics have been widely used and recommended by geriatric experts in the management of psychosis of AD in view of the modest efficacy and relative safety until FDA warnings were issued in 2005 and meta-analytic studies showed no significant difference to placebo. The FDA warnings on the cardiac, metabolic, cerebrovascular, and mortality risks have caused serious concerns for the use of atypical antipsychotic agents in elderly patients with dementia. Only a few studies have evaluated prospectively the effects of aripiprazole in psychosis associated with AD. These studies show improvement in the symptoms of psychosis associated with AD with aripiprazole. The safety and tolerability profile of aripiprazole suggests a low potential for negative impact on dementia and overall patient health. Further studies comparing the efficacy and tolerability of aripiprazole vs other atypical antipsychotics in dementia are needed.     

Expressed emotion and family burden in relatives of patients in first-episode psychosis

BACKGROUND

Evidence suggests that expressed emotion (EE) and family burden (FB) are phenomena that interact, but there is a lack of studies that analyze this association in patients in first-episode psychosis.

Multimodal MRI assessment for first episode psychosis: A major change in the thalamus and an efficient stratification of a subgroup

Multi‐institutional brain imaging studies have emerged to resolve conflicting results among individual studies. However, adjusting multiple variables at the technical and cohort levels is challenging. Therefore, it is important to explore approaches that provide meaningful results from relatively small samples at institutional levels. We studied 87 first episode psychosis (FEP) patients and 62 healthy subjects by combining supervised integrated factor analysis (SIFA) with a novel pipeline for automated structure‐based analysis, an efficient and comprehensive method for dimensional data reduction that our group recently established. We integrated multiple MRI features (volume, DTI indices, resting state fMRI—rsfMRI) in the whole brain of each participant in an unbiased manner. The automated structure‐based analysis showed widespread DTI abnormalities in FEP and rs‐fMRI differences between FEP and healthy subjects mostly centered in thalamus. The combination of multiple modalities with SIFA was more efficient than the use of single modalities to stratify a subgroup of FEP (individuals with schizophrenia or schizoaffective disorder) that had more robust deficits from the overall FEP group. The information from multiple MRI modalities and analytical methods highlighted the thalamus as significantly abnormal in FEP. This study serves as a proof‐of‐concept for the potential of this methodology to reveal disease underpins and to stratify populations into more homogeneous sub‐groups.     

Using Natural Language Processing on Electronic Health Records to Enhance Detection and Prediction of Psychosis Risk

BackgroundUsing novel data mining methods such as natural language processing (NLP) on electronic health records (EHRs) for screening and detecting individuals at risk for psychosis. MethodThe study included all patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within the South London and Maudsley (SLaM) NHS Foundation Trust between January 1, 2008, and July 28, 2018. Least Absolute Shrinkage and Selection Operator (LASSO)-regularized Cox regression was used to refine and externally validate a refined version of a five-item individualized, transdiagnostic, clinically based risk calculator previously developed (Harrell’s C = 0.79) and piloted for implementation. The refined version included 14 additional NLP-predictors: tearfulness, poor appetite, weight loss, insomnia, cannabis, cocaine, guilt, irritability, delusions, hopelessness, disturbed sleep, poor insight, agitation, and paranoia. ResultsA total of 92 151 patients with a first index diagnosis of nonorganic and nonpsychotic mental disorder within the SLaM Trust were included in the derivation (n = 28 297) or external validation (n = 63 854) data sets. Mean age was 33.6 years, 50.7% were women, and 67.0% were of white race/ethnicity. Mean follow-up was 1590 days. The overall 6-year risk of psychosis in secondary mental health care was 3.4 (95% CI, 3.3–3.6). External validation indicated strong performance on unseen data (Harrell’s C 0.85, 95% CI 0.84–0.86), an increase of 0.06 from the original model. ConclusionsUsing NLP on EHRs can considerably enhance the prognostic accuracy of psychosis risk calculators. This can help identify patients at risk of psychosis who require assessment and specialized care, facilitating earlier detection and potentially improving patient outcomes.