Predicting early psychiatric readmission with natural language processing of narrative discharge summaries

The ability to predict psychiatric readmission would facilitate the development of interventions to reduce this risk, a major driver of psychiatric health-care costs. The symptoms or characteristics of illness course necessary to develop reliable predictors are not available in coded billing data, but may be present in narrative electronic health record (EHR) discharge summaries. We identified a cohort of individuals admitted to a psychiatric inpatient unit between 1994 and 2012 with a principal diagnosis of major depressive disorder, and extracted inpatient psychiatric discharge narrative notes. Using these data, we trained a 75-topic Latent Dirichlet Allocation (LDA) model, a form of natural language processing, which identifies groups of words associated with topics discussed in a document collection. The cohort was randomly split to derive a training (70%) and testing (30%) data set, and we trained separate support vector machine models for baseline clinical features alone, baseline features plus common individual words and the above plus topics identified from the 75-topic LDA model. Of 4687 patients with inpatient discharge summaries, 470 were readmitted within 30 days. The 75-topic LDA model included topics linked to psychiatric symptoms (suicide, severe depression, anxiety, trauma, eating/weight and panic) and major depressive disorder comorbidities (infection, postpartum, brain tumor, diarrhea and pulmonary disease). By including LDA topics, prediction of readmission, as measured by area under receiver-operating characteristic curves in the testing data set, was improved from baseline (area under the curve 0.618) to baseline+1000 words (0.682) to baseline+75 topics (0.784). Inclusion of topics derived from narrative notes allows more accurate discrimination of individuals at high risk for psychiatric readmission in this cohort. Topic modeling and related approaches offer the potential to improve prediction using EHRs, if generalizability can be established in other clinical cohorts

Label-free, live optical imaging of reprogrammed bipolar disorder patient-derived cells reveals a functional correlate of lithium responsiveness

Development of novel treatments and diagnostic tools for psychiatric illness has been hindered by the absence of cellular models of disease. With the advent of cellular reprogramming, it may be possible to recapitulate the disease biology of psychiatric disorders using patient skin cells transdifferentiated to neurons. However, efficiently identifying and characterizing relevant neuronal phenotypes in the absence of well-defined pathophysiology remains a challenge. In this study, we collected fibroblast samples from patients with bipolar 1 disorder, characterized by their lithium response (n=12), and healthy control subjects (n=6). We identified a cellular phenotype in reprogrammed neurons using a label-free imaging assay based on a nanostructured photonic crystal biosensor and found that an optical measure of cell adhesion was associated with clinical response to lithium treatment. This cellular phenotype may represent a useful biomarker to evaluate drug response and screen for novel therapeutics

Cognitive Behavioral Therapy for Insomnia in Alcohol‐Dependent Veterans: A Randomized, Controlled Pilot Study

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149521/1/acer14030.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149521/2/acer14030-sup-0001-FigS1-S3.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149521/3/acer14030_am.pd

Information Retrieval on the World Wide Web and Active Logic: A Survey and Problem Definition

As more information becomes available on the World Wide Web (there are currently over 4 billion pages covering most areas of human endeavor), it becomes more difficult to provide effective search tools for information access. Today, people access web information through two main kinds of search interfaces: Browsers (clicking and following hyperlinks) and Query Engines (queries in the form of a set of keywords showing the topic of interest). The first process is tentative and time consuming and the second may not satisfy the user because of many inaccurate and irrelevant results. Better support is needed for expressing one's information need and returning high quality search results by web search tools. There appears to be a need for systems that do reasoning under uncertainty and are flexible enough to recover from the contradictions, inconsistencies, and irregularities that such reasoning involves. Active Logic is a formalism that has been developed with real-world applications and their challenges in mind. Motivating its design is the thought that one of the factors that supports the flexibility of human reasoning is that it takes place step-wise, in time. Active Logic is one of a family of inference engines (step-logics) that explicitly reason in time, and incorporate a history of their reasoning as they run. This characteristic makes Active Logic systems more flexible than traditional AI systems and therefore more suitable for commonsense, real-world reasoning. In this report we mainly will survey recent advances in machine learning and crawling problems related to the web. We will review the continuum of supervised to semi-supervised to unsupervised learning problems, highlight the specific challenges which distinguish information retrieval in the hypertext domain and will summarize the key areas of recent and ongoing research. We will concentrate on topic-specific search engines, focused crawling, and finally will propose an Information Integration Environment, based on the Active Logic framework. Keywords: Web Information Retrieval, Web Crawling, Focused Crawling, Machine Learning, Active Logic (Also UMIACS-TR-2001-69

A Behavioural Foundation for Natural Computing and a Programmability Test

What does it mean to claim that a physical or natural system computes? One answer, endorsed here, is that computing is about programming a system to behave in different ways. This paper offers an account of what it means for a physical system to compute based on this notion. It proposes a behavioural characterisation of computing in terms of a measure of programmability, which reflects a system's ability to react to external stimuli. The proposed measure of programmability is useful for classifying computers in terms of the apparent algorithmic complexity of their evolution in time. I make some specific proposals in this connection and discuss this approach in the context of other behavioural approaches, notably Turing's test of machine intelligence. I also anticipate possible objections and consider the applicability of these proposals to the task of relating abstract computation to nature-like computation.Comment: 37 pages, 4 figures. Based on an invited Talk at the Symposium on Natural/Unconventional Computing and its Philosophical Significance, Alan Turing World Congress 2012, Birmingham, UK. http://link.springer.com/article/10.1007/s13347-012-0095-2 Ref. glitch fixed in 2nd. version; Philosophy & Technology (special issue on History and Philosophy of Computing), Springer, 201

Psychiatric co-morbidity is associated with increased risk of surgery in Crohn's disease

Psychiatric co-morbidity, in particular major depression and anxiety, is common in patients with Crohn's disease (CD) and ulcerative colitis (UC). Prior studies examining this may be confounded by the co-existence of functional bowel symptoms. Limited data exist examining an association between depression or anxiety and disease-specific endpoints such as bowel surgery.National Institutes of Health (U.S.) (NIH U54-LM008748)American Gastroenterological AssociationNational Institutes of Health (U.S.) (NIH K08 AR060257)Beth Isreal Deaconess Medical Center (Katherine Swan Ginsburg Fund)National Institutes of Health (U.S.) (NIH R01-AR056768)National Institutes of Health (U.S.) (NIH U01-GM092691)National Institutes of Health (U.S.) (NIH R01-AR059648)Burroughs Wellcome Fund (Career Award for Medical Scientists)National Institutes of Health (U.S.) (NIH K24 AR052403)National Institutes of Health (U.S.) (NIH P60 AR047782)National Institutes of Health (U.S.) (NIH R01 AR049880

Dysregulated protocadherin-pathway activity as an intrinsic defect in induced pluripotent stem cell-derived cortical interneurons from subjects with schizophrenia.

We generated cortical interneurons (cINs) from induced pluripotent stem cells derived from 14 healthy controls and 14 subjects with schizophrenia. Both healthy control cINs and schizophrenia cINs were authentic, fired spontaneously, received functional excitatory inputs from host neurons, and induced GABA-mediated inhibition in host neurons in vivo. However, schizophrenia cINs had dysregulated expression of protocadherin genes, which lie within documented schizophrenia loci. Mice lacking protocadherin-α showed defective arborization and synaptic density of prefrontal cortex cINs and behavioral abnormalities. Schizophrenia cINs similarly showed defects in synaptic density and arborization that were reversed by inhibitors of protein kinase C, a downstream kinase in the protocadherin pathway. These findings reveal an intrinsic abnormality in schizophrenia cINs in the absence of any circuit-driven pathology. They also demonstrate the utility of homogenous and functional populations of a relevant neuronal subtype for probing pathogenesis mechanisms during development

Towards the clinical implementation of pharmacogenetics in bipolar disorder.

BackgroundBipolar disorder (BD) is a psychiatric illness defined by pathological alterations between the mood states of mania and depression, causing disability, imposing healthcare costs and elevating the risk of suicide. Although effective treatments for BD exist, variability in outcomes leads to a large number of treatment failures, typically followed by a trial and error process of medication switches that can take years. Pharmacogenetic testing (PGT), by tailoring drug choice to an individual, may personalize and expedite treatment so as to identify more rapidly medications well suited to individual BD patients.DiscussionA number of associations have been made in BD between medication response phenotypes and specific genetic markers. However, to date clinical adoption of PGT has been limited, often citing questions that must be answered before it can be widely utilized. These include: What are the requirements of supporting evidence? How large is a clinically relevant effect? What degree of specificity and sensitivity are required? Does a given marker influence decision making and have clinical utility? In many cases, the answers to these questions remain unknown, and ultimately, the question of whether PGT is valid and useful must be determined empirically. Towards this aim, we have reviewed the literature and selected drug-genotype associations with the strongest evidence for utility in BD.SummaryBased upon these findings, we propose a preliminary panel for use in PGT, and a method by which the results of a PGT panel can be integrated for clinical interpretation. Finally, we argue that based on the sufficiency of accumulated evidence, PGT implementation studies are now warranted. We propose and discuss the design for a randomized clinical trial to test the use of PGT in the treatment of BD

The Functional DRD3 Ser9Gly Polymorphism (rs6280) Is Pleiotropic, Affecting Reward as Well as Movement

Abnormalities of motivation and behavior in the context of reward are a fundamental component of addiction and mood disorders. Here we test the effect of a functional missense mutation in the dopamine 3 receptor (DRD3) gene (ser9gly, rs6280) on reward-associated dopamine (DA) release in the striatum. Twenty-six healthy controls (HCs) and 10 unmedicated subjects with major depressive disorder (MDD) completed two positron emission tomography (PET) scans with [11C]raclopride using the bolus plus constant infusion method. On one occasion subjects completed a sensorimotor task (control condition) and on another occasion subjects completed a gambling task (reward condition). A linear regression analysis controlling for age, sex, diagnosis, and self-reported anhedonia indicated that during receipt of unpredictable monetary reward the glycine allele was associated with a greater reduction in D2/3 receptor binding (i.e., increased reward-related DA release) in the middle (anterior) caudate (p<0.01) and the ventral striatum (p<0.05). The possible functional effect of the ser9gly polymorphism on DA release is consistent with previous work demonstrating that the glycine allele yields D3 autoreceptors that have a higher affinity for DA and display more robust intracellular signaling. Preclinical evidence indicates that chronic stress and aversive stimulation induce activation of the DA system, raising the possibility that the glycine allele, by virtue of its facilitatory effect on striatal DA release, increases susceptibility to hyperdopaminergic responses that have previously been associated with stress, addiction, and psychosis