The impact of the Val158Met catechol-O-methyltransferase genotype on neural correlates of sad facial affect processing in patients with bipolar disorder and their relatives

Background - The Met allele of the catechol-O-methyltransferase (COMT) valine-to-methionine (Val158Met) polymorphism is known to affect dopamine-dependent affective regulation within amygdala-prefrontal cortical (PFC) networks. It is also thought to increase the risk of a number of disorders characterized by affective morbidity including bipolar disorder (BD), major depressive disorder (MDD) and anxiety disorders. The disease risk conferred is small, suggesting that this polymorphism represents a modifier locus. Therefore our aim was to investigate how the COMT Val158Met may contribute to phenotypic variation in clinical diagnosis using sad facial affect processing as a probe for its neural action. Method - We employed functional magnetic resonance imaging to measure activation in the amygdala, ventromedial PFC (vmPFC) and ventrolateral PFC (vlPFC) during sad facial affect processing in family members with BD (n=40), MDD and anxiety disorders (n=22) or no psychiatric diagnosis (n=25) and 50 healthy controls. Results - Irrespective of clinical phenotype, the Val158 allele was associated with greater amygdala activation and the Met allele with greater signal change in the vmPFC and vlPFC. Signal changes in the amygdala and vmPFC were not associated with disease expression. However, in the right vlPFC the Met158 allele was associated with greater activation in all family members with affective morbidity compared with relatives without a psychiatric diagnosis and healthy controls. Conclusions - Our results suggest that the COMT Val158Met polymorphism has a pleiotropic effect within the neural networks subserving emotional processing. Furthermore the Met158 allele further reduces cortical efficiency in the vlPFC in individuals with affective morbidity. © 2010 Cambridge University Press.

Psychiatric adverse effects of zonisamide in patients with epilepsy and mental disorder comorbidities

Over the last few years, zonisamide has been proposed as a potentially useful medication for patients with focal seizures, with or without secondary generalization. Since psychiatric adverse effects, including mania, psychosis, and suicidal ideation, have been associated with its use, it was suggested that the presence of antecedent psychiatric disorders is an important factor associated with the discontinuation of zonisamide therapy in patients with epilepsy. We, therefore, set out to assess the tolerability profile of zonisamide in a retrospective chart review of 23 patients with epilepsy and comorbid mental disorders, recruited from two specialist pediatric (n=11) and adult (n=12) neuropsychiatry clinics. All patients had a clinical diagnosis of treatment-refractory epilepsy after extensive neurophysiological and neuroimaging investigations. The vast majority of patients (n=22/23, 95.7%) had tried previous antiepileptic medications, and most adult patients (n=9/11, 81.8%) were on concomitant medication for epilepsy. In the majority of cases, the psychiatric adverse effects of zonisamide were not severe. Four patients (17.4%) discontinued zonisamide because of lack of efficacy, whereas only one patient (4.3%) discontinued it because of the severity of psychiatric adverse effects (major depressive disorder). The low discontinuation rate of zonisamide in a selected population of patients with epilepsy and neuropsychiatric comorbidity suggests that this medication is safe and reasonably well-tolerated for use in patients with treatment-refractory epilepsy. Given the limitations of the present study, including the relatively small sample size, further research is warranted to confirm this finding. © 2013 Elsevier Inc.

Corticobasal degeneration and dementia

Corticobasal degeneration is a rare, progressive neurodegenerative disorder which significantly impairs movement. The most common initial symptom is asymmetric limb clumsiness with or without accompanying rigidity or tremor. Subsequently, the disease progresses to affect gait and there is a slow progression to influence ipsilateral arms and legs. Apraxia and dementia are the most common cortical signs. Clinical diagnosis of the disorder is difficult as the symptoms resemble those of related neurodegenerative disorders. Histopathologically, there is widespread neuronal and glial pathology including tau-immunoreactive neuronal cytoplasmic inclusions, neuropil threads, oligodendroglial inclusions, astrocytic plaques, together with abnormally enlarged ‘ballooned’ neurons. Corticobasal degeneration has affinities both with the parkinsonian syndromes including Parkinson’s disease, progressive supranuclear palsy, and multiple system atrophy and with the fronto-temporal dementias. Treatment of corticobasal degeneration involves managing and reducing the effect of symptoms.

Does the Swedish Interactive Threshold Algorithm (SITA) accurately map visual field loss attributed to vigabatrin?

Background: Vigabatrin (VGB) is an anti-epileptic medication which has been linked to peripheral constriction of the visual field. Documenting the natural history associated with continued VGB exposure is important when making decisions about the risk and benefits associated with the treatment. Due to its speed the Swedish Interactive Threshold Algorithm (SITA) has become the algorithm of choice when carrying out Full Threshold automated static perimetry. SITA uses prior distributions of normal and glaucomatous visual field behaviour to estimate threshold sensitivity. As the abnormal model is based on glaucomatous behaviour this algorithm has not been validated for VGB recipients. We aim to assess the clinical utility of the SITA algorithm for accurately mapping VGB attributed field loss. Methods: The sample comprised one randomly selected eye of 16 patients diagnosed with epilepsy, exposed to VGB therapy. A clinical diagnosis of VGB attributed visual field loss was documented in 44% of the group. The mean age was 39.3 years∈±∈14.5 years and the mean deviation was -4.76 dB ±4.34 dB. Each patient was examined with the Full Threshold, SITA Standard and SITA Fast algorithm. Results: SITA Standard was on average approximately twice as fast (7.6 minutes) and SITA Fast approximately 3 times as fast (4.7 minutes) as examinations completed using the Full Threshold algorithm (15.8 minutes). In the clinical environment, the visual field outcome with both SITA algorithms was equivalent to visual field examination using the Full Threshold algorithm in terms of visual inspection of the grey scale plots, defect area and defect severity. Conclusions: Our research shows that both SITA algorithms are able to accurately map visual field loss attributed to VGB. As patients diagnosed with epilepsy are often vulnerable to fatigue, the time saving offered by SITA Fast means that this algorithm has a significant advantage for use with VGB recipients.

Increased risk of diabetes mellitus among persons with psychotic symptoms:results from the WHO World Health Survey

OBJECTIVE: To analyze with a symptom-based approach the relationship between psychosis and diabetes mellitus in the general population. METHOD: Nationally representative samples from the World Health Organization (WHO) World Health Survey, totaling 224,743 randomly selected adults 18 years and older from 52 countries worldwide, were interviewed to establish the presence of psychotic symptoms and diabetes mellitus. Presence of psychotic symptoms was established using questions pertaining to positive symptoms from the psychosis screening module of the Composite International Diagnostic Interview. Presence of diabetes was established with a response of "yes" to the question, "Have you ever been diagnosed with diabetes (high blood sugar)?" The World Health Survey was conducted between 2002 and 2004. RESULTS: An increasing number of psychotic symptoms was related to increasing likelihood of diabetes mellitus (OR = 1.27; 95% CI, 1.24-1.30). As compared to no symptoms, at least 1 psychotic symptom substantially elevated the risk (OR = 1.71; 95% CI, 1.61-1.81). In people with a lifetime diagnosis of schizophrenia or psychosis, the prevalence of diabetes was higher in those with current psychotic symptoms (7.3% vs 5.2%; OR = 1.65; 95% CI, 1.21-2.26), suggesting that the persistence of symptoms over time could play a central role. After controlling for different potential confounders, there was a clear increase in the probability of having diabetes as the number of psychotic symptoms increased. The relationship between psychotic symptoms and diabetes was tested with multiple mediation models and path analyses for categorical outcomes. Only body mass index appeared as a relevant mediator in a model with a good fit (ie, χ21 = 3.2, P = .0742; comparative fit index = 0.999). CONCLUSIONS: Psychotic symptoms are related to increased rates of diabetes mellitus in nonclinical samples, independent of several potential confounders-including a clinical diagnosis of psychosis or schizophrenia, previous antipsychotic treatment, depression, lifestyle, and individual or country socioeconomic status. The findings highlight the worldwide relevance of the problem and the importance of identifying the specific paths of this association.

Machine learning for large-scale wearable sensor data in Parkinson disease:concepts, promises, pitfalls, and futures

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, “wearable,” sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that “learn” from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society.

Serum procalcitonin, interleukin-6, soluble intercellular adhesin molecule-1 and IgG to short-chain exocellular lipoteichoic acid as predictors of infection in total joint prosthesis revision

The diagnosis of prosthetic joint infection and its differentiation from aseptic loosening remains problematic. The definitive laboratory diagnostic test is the recovery of identical infectious agents from multiple intraoperative tissue samples; however, interpretation of positive cultures is often complex as infection is frequently associated with low numbers of commensal microorganisms, in particular the coagulase-negative staphylococci (CNS). In this investigation, the value of serum procalcitonin (PCT), interleukin-6 (IL-6) and soluble intercellular adhesion molecule-1 (sICAM-1) as predictors of infection in revision hip replacement surgery is assessed. Furthermore, the diagnostic value of serum IgG to short-chain exocellular lipoteichoic acid (sce-LTA) is assessed in patients with infection due to CNS. Presurgical levels of conventional serum markers of infection including C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and white blood cell count (WBC) is also established. Forty-six patients undergoing revision hip surgery were recruited with a presumptive clinical diagnosis of either septic (16 patients) or aseptic loosening (30 patients). The diagnosis was confirmed microbiologically and levels of serum markers were determined. Serum levels of IL-6 and sICAM-1 were significantly raised in patients with septic loosening (P=0.001 and P=0.0002, respectively). Serum IgG to sce-LTA was elevated in three out of four patients with infection due to CNS. In contrast, PCT was not found to be of value in differentiating septic and aseptic loosening. Furthermore, CRP, ESR and WBC were significantly higher (P=0.0001, P=0.0001 and P=0.003, respectively) in patients with septic loosening. Serum levels of IL-6, sICAM-1 and IgG to sce-LTA may provide additional information to facilitate the diagnosis of prosthetic joint infection.

Visual signs and symptoms of corticobasal degeneration

Corticobasal degeneration is a rare, progressive neurodegenerative disease and a member of the 'parkinsonian' group of disorders, which also includes Parkinson's disease, progressive supranuclear palsy, dementia with Lewy bodies and multiple system atrophy. The most common initial symptom is limb clumsiness, usually affecting one side of the body, with or without accompanying rigidity or tremor. Subsequently, the disease affects gait and there is a slow progression to influence ipsilateral arms and legs. Apraxia and dementia are the most common cortical signs. Corticobasal degeneration can be difficult to distinguish from other parkinsonian syndromes but if ocular signs and symptoms are present, they may aid clinical diagnosis. Typical ocular features include increased latency of saccadic eye movements ipsilateral to the side exhibiting apraxia, impaired smooth pursuit movements and visuo-spatial dysfunction, especially involving spatial rather than object-based tasks. Less typical features include reduction in saccadic velocity, vertical gaze palsy, visual hallucinations, sleep disturbance and an impaired electroretinogram. Aspects of primary vision such as visual acuity and colour vision are usually unaffected. Management of the condition to deal with problems of walking, movement, daily tasks and speech problems is an important aspect of the disease.

Validation of the English version of the Scale for Psychosocial Factors in Food Allergy and the relationship with mental health, quality of life, and self-efficacy

Background. The Scale for Psychosocial Factors in Food Allergy (SPS-FA) is based on the biopsychosocial model of health and was developed and validated in Chile to measure the interaction between psychological variables and allergy symptoms in the child. We sought to validate this scale in an English speaking population and explore its relationship with parental quality of life, self-efficacy, and mental health. Methods. Parents (n = 434) from the general population in the UK, who had a child with a clinical diagnosis of food allergy, completed the SPS-FA and validated scales on food allergy specific parental quality of life (QoL), parental self-efficacy, and general mental health. Findings. The SPS-FA had good internal consistency (alphas = .61-.86). Higher scores on the SPS-FA significantly correlated with poorer parental QoL, self-efficacy, and mental health. All predictors explained 57% of the variance in SPS-FA scores with QoL as the biggest predictor (β = .52). Discussion. The SPS-FA is a valid scale for use in the UK and provides a holistic view of the impact of food allergy on the family. In conjunction with health-related QoL measures, it can be used by health care practitioners to target care for patients and evaluate psychological interventions for improvement of food allergy management.

Classifying clinical decision making:interpreting nursing intuition, heuristics and medical diagnosis

This is the second of two linked papers exploring decision making in nursing. The first paper, 'Classifying clinical decision making: a unifying approach' investigated difficulties with applying a range of decision-making theories to nursing practice. This is due to the diversity of terminology and theoretical concepts used, which militate against nurses being able to compare the outcomes of decisions analysed within different frameworks. It is therefore problematic for nurses to assess how good their decisions are, and where improvements can be made. However, despite the range of nomenclature, it was argued that there are underlying similarities between all theories of decision processes and that these should be exposed through integration within a single explanatory framework. A proposed solution was to use a general model of psychological classification to clarify and compare terms, concepts and processes identified across the different theories. The unifying framework of classification was described and this paper operationalizes it to demonstrate how different approaches to clinical decision making can be re-interpreted as classification behaviour. Particular attention is focused on classification in nursing, and on re-evaluating heuristic reasoning, which has been particularly prone to theoretical and terminological confusion. Demonstrating similarities in how different disciplines make decisions should promote improved multidisciplinary collaboration and a weakening of clinical elitism, thereby enhancing organizational effectiveness in health care and nurses' professional status. This is particularly important as nurses' roles continue to expand to embrace elements of managerial, medical and therapeutic work. Analysing nurses' decisions as classification behaviour will also enhance clinical effectiveness, and assist in making nurses' expertise more visible. In addition, the classification framework explodes the myth that intuition, traditionally associated with nurses' decision making, is less rational and scientific than other approaches.