Surgical adverse outcome reporting as part of routine clinical care

Analysis and support of clinical decision makin

Challenges and Solutions to the Measurement of Neurocognitive Mechanisms in Developmental Settings

Identifying early neurocognitive mechanisms that confer risk for mental health problems is one important avenue as we seek to develop successful early interventions. Currently, however, we have limited understanding of the neurocognitive mechanisms involved in shaping mental health trajectories from childhood through young adulthood, and this constrains our ability to develop effective clinical interventions. In particular, there is an urgent need to develop more sensitive, reliable, and scalable measures of individual differences for use in developmental settings. In this review, we outline methodological shortcomings that explain why widely used task-based measures of neurocognition currently tell us little about mental health risk. We discuss specific challenges that arise when studying neurocognitive mechanisms in developmental settings, and we share suggestions for overcoming them. We also propose a novel experimental approach—which we refer to as “cognitive microscopy”—that involves adaptive design optimization, temporally sensitive task administration, and multilevel modeling. This approach addresses some of the methodological shortcomings outlined above and provides measures of stability, variability, and developmental change in neurocognitive mechanisms within a multivariate framework

Corrigendum: Mutualistic Coupling Between Vocabulary and Reasoning Supports Cognitive Development During Late Adolescence and Early Adulthood

Correction to: Kievit, R. A., Lindenberger, U., Goodyer, I. M., Jones, P. B., Fonagy, P., Bullmore, E. T., the Neuroscience in Psychiatry Network, & Dolan, R. J. (2017). Mutualistic coupling between vocabulary and reasoning supports cognitive development during late adolescence and early adulthood. Psychological Science, 28, 1419–1431. doi:10.1177/095679761771078

An amino acid polymorphism in histidine-rich glycoprotein (HRG) explains 59% of the variance in plasma HRG levels

A pedigree-based maximum likelihood method developed by Lange et al. (12) was used to study the contribution of a newly defined di-allelic polymorphism in histidine-rich glycoprotein (HRG) to the plasma levels of HRG. In four families (n = 99) and 20 volunteers we found a heritability of 70%, an age effect of 3% and an effect of individual environmental factors of 27%. These results are remarkably similar to the results found in a previous parent-twin study in which a heritability of 69% and an effect of random environment of 31% was found. The overall genetic influence in the present study can be subdivided into an effect of 59% by the HRG phenotype and 11% by residual genetic factors. The influence of the HRG phenotype of 59% can entirely be explained by adding up the effect of the two alleles that make up the phenotype. These results indicate a codominant inheritance pattern of HRG levels in which the genetic influence can almost completely be ascribed to the additive effect of the di-allelic HRG locus whereas only a small part is due to other loci

Episodic abdominal pain characteristics are not associated with clinically relevant improvement of health status after cholecystectomy

BACKGROUND: Cholecystectomy is the therapy of first choice in patients with uncomplicated symptomatic cholecystolithiasis, but it remains unclear which patients truly benefit in terms of health status improvement. Patients generally present with episodic abdominal pain of varying frequency, duration, and intensity. We assessed whether characteristics of abdominal pain episodes are determinants of clinically relevant improvement of health status after cholecystectomy. METHODS: In a post hoc analysis of a prospective multicenter cohort study, patients of ≥18 years of age with uncomplicated symptomatic cholecystolithiasis subjected to cholecystectomy were included. Preoperatively, patients received a structured interview and a questionnaire consisting of the visual analogue scale (VAS; range 0–100) and gastrointestinal quality of life index (GIQLI). At 12 weeks after cholecystectomy, the GIQLI was again administered. Logistic regression analyses were performed to determine significant associations. RESULTS: Questionnaires were sent to 261 and returned by 166 (63.6 %) patients (128 females, mean age at surgery 49.5 ± 13.8). A total of 131 (78.9 %) patients reported a clinically relevant improvement of health status. The median (interquartile range) frequency, duration, and intensity of abdominal pain episodes were 0.38 (0.18–0.75) a week, 4.00 (2.00–8.00) hours, and 92 (77–99), respectively. None of the characteristics was associated with a clinically relevant improvement of health status at 12 weeks after cholecystectomy. CONCLUSIONS: Characteristics of abdominal pain episodes cannot be used to inform patients with symptomatic cholecystolithiasis who are skeptic about the timing of cholecystectomy for optimal benefit. Timing of cholecystectomy should therefore be based on other characteristics and preferences

Meta-analysis of generalized additive models in neuroimaging studies

Contains fulltext : 231772.pdf (publisher's version ) (Open Access)Analyzing data from multiple neuroimaging studies has great potential in terms of increasing statistical power, enabling detection of effects of smaller magnitude than would be possible when analyzing each study separately and also allowing to systematically investigate between-study differences. Restrictions due to privacy or proprietary data as well as more practical concerns can make it hard to share neuroimaging datasets, such that analyzing all data in a common location might be impractical or impossible. Meta-analytic methods provide a way to overcome this issue, by combining aggregated quantities like model parameters or risk ratios. Most meta-analytic tools focus on parametric statistical models, and methods for meta-analyzing semi-parametric models like generalized additive models have not been well developed. Parametric models are often not appropriate in neuroimaging, where for instance age-brain relationships may take forms that are difficult to accurately describe using such models. In this paper we introduce meta-GAM, a method for meta-analysis of generalized additive models which does not require individual participant data, and hence is suitable for increasing statistical power while upholding privacy and other regulatory concerns. We extend previous works by enabling the analysis of multiple model terms as well as multivariate smooth functions. In addition, we show how meta-analytic p-values can be computed for smooth terms. The proposed methods are shown to perform well in simulation experiments, and are demonstrated in a real data analysis on hippocampal volume and self-reported sleep quality data from the Lifebrain consortium. We argue that application of meta-GAM is especially beneficial in lifespan neuroscience and imaging genetics. The methods are implemented in an accompanying R package metagam, which is also demonstrated

The development of PubMed search strategies for patient preferences for treatment outcomes.

BACKGROUND: The importance of respecting patients' preferences when making treatment decisions is increasingly recognized. Efficiently retrieving papers from the scientific literature reporting on the presence and nature of such preferences can help to achieve this goal. The objective of this study was to create a search filter for PubMed to help retrieve evidence on patient preferences for treatment outcomes. METHODS: A total of 27 journals were hand-searched for articles on patient preferences for treatment outcomes published in 2011. Selected articles served as a reference set. To develop optimal search strategies to retrieve this set, all articles in the reference set were randomly split into a development and a validation set. MeSH-terms and keywords retrieved using PubReMiner were tested individually and as combinations in PubMed and evaluated for retrieval performance (e.g. sensitivity (Se) and specificity (Sp)). RESULTS: Of 8238 articles, 22 were considered to report empirical evidence on patient preferences for specific treatment outcomes. The best search filters reached Se of 100 % [95 % CI 100-100] with Sp of 95 % [94-95 %] and Sp of 97 % [97-98 %] with 75 % Se [74-76 %]. In the validation set these queries reached values of Se of 90 % [89-91 %] with Sp 94 % [93-95 %] and Se of 80 % [79-81 %] with Sp of 97 % [96-96 %], respectively. CONCLUSIONS: Narrow and broad search queries were developed which can help in retrieving literature on patient preferences for treatment outcomes. Identifying such evidence may in turn enhance the incorporation of patient preferences in clinical decision making and health technology assessment

OXYGEN REACTIVE POLYMERS FOR TREATMENT OF TRAUMATIC BRAIN INJURY

Methods and compositions for treating traumatic brain injury . The methods and compositions utilize a multi - functional oxygen reactive polymer ( ORP ) that includes repeating units that include a reactive oxygen species ( ROS ) scavenging group and a polyalkylene oxide group . For theranostic applications , the oxygen reactive polymer fur ther includes a diagnostic group