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Robin M. Murray

Bio: Robin M. Murray is an academic researcher from King's College London. The author has contributed to research in topics: Psychosis & Schizophrenia. The author has an hindex of 171, co-authored 1539 publications receiving 116362 citations. Previous affiliations of Robin M. Murray include University of Cambridge & National Institutes of Health.


Papers
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Journal ArticleDOI
TL;DR: Sustained periods of symptom remission are usual following first presentation to mental health services for psychosis, including for those with a non-affective disorder; almost half recover.
Abstract: Background Studies of the long-term course and outcome of psychoses tend to focus on cohorts of prevalent cases. Such studies bias samples towards those with poor outcomes, which may distort our understanding of prognosis. Long-term follow-up studies of epidemiologically robust first-episode samples are rare. Method AESOP-10 is a 10-year follow-up study of 557 individuals with a first episode of psychosis initially identified in two areas in the UK (South East London and Nottingham). Detailed information was collated on course and outcome in three domains (clinical, social and service use) from case records, informants and follow-up interviews. Results At follow-up, of 532 incident cases identified, at baseline 37 (7%) had died, 29 (6%) had emigrated and eight (2%) were excluded. Of the remaining 458, 412 (90%) were traced and some information on follow-up was collated for 387 (85%). Most cases (265, 77%) experienced at least one period of sustained remission; at follow-up, 141 (46%) had been symptom free for at least 2 years. A majority (208, 72%) of cases had been employed for less than 25% of the follow-up period. The median number of hospital admissions, including at first presentation, was 2 [interquartile range (IQR) 1–4]; a majority (299, 88%) were admitted a least once and a minority (21, 6%) had 10 or more admissions. Overall, outcomes were worse for those with a non-affective diagnosis, for men and for those from South East London. Conclusions Sustained periods of symptom remission are usual following first presentation to mental health services for psychosis, including for those with a non-affective disorder; almost half recover.

180 citations

Journal ArticleDOI
TL;DR: The wise psychiatrist should regularly review the benefit to each patient of continuing prophylactic antipsychotics against the risk of side-effects and loss of effectiveness through the development of supersensitivity of the dopamine D2 receptor.
Abstract: Patients who recover from an acute episode of psychosis are frequently prescribed prophylactic antipsychotics for many years, especially if they are diagnosed as having schizophrenia. However, there is a dearth of evidence concerning the long-term effectiveness of this practice, and growing concern over the cumulative effects of antipsychotics on physical health and brain structure. Although controversy remains concerning some of the data, the wise psychiatrist should regularly review the benefit to each patient of continuing prophylactic antipsychotics against the risk of side-effects and loss of effectiveness through the development of supersensitivity of the dopamine D2 receptor. Psychiatrists should work with their patients to slowly reduce the antipsychotic to the lowest dose that prevents the return of distressing symptoms. Up to 40% of those whose psychosis remits after a first episode should be able to achieve a good outcome in the long term either with no antipsychotic medication or with a very low dose.

180 citations

Journal ArticleDOI
TL;DR: The first episode of a psychosis is associated with a larger pituitary volume, which the authors suggest is due to activation of the HPA axis, and the smaller pituitsary volume in the group with established schizophrenia could be the consequence of repeated episodes of HPAaxis hyperactivity.
Abstract: Background Patients with psychosis have activation of the hypothalamic–pituitary–adrenal (HPA) axis during the acute phase of the psychosis. Whether this has any morphological consequences for the pituitary gland is currently unknown. Aims To examine pituitary volume variation in people at different stages of psychotic disorder. Method Pituitary volume was measured using 1.5 mm, coronal magnetic resonance images in 24 people with first-episode psychosis, 51 with established schizophrenia and 59 healthy controls. Results Compared with the control group, the people with first-episode psychosis had pituitary volumes that were 10% larger, whereas those with established schizophrenia had pituitary volumes that were 17% smaller. In both of the groups with psychosis, there was no difference in pituitary volume between those receiving typical antipsychotic drugs and those receiving atypical antipsychotics. Conclusions The first episode of a psychosis is associated with a larger pituitary volume, which we suggest is due to activation of the HPA axis. The smaller pituitary volume in the group with established schizophrenia could be the consequence of repeated episodes of HPA axis hyperactivity.

180 citations

Journal ArticleDOI
TL;DR: The results of this study indicate that neuroleptic-induced prolactin secretion is a dose-related side effect and, in females, the level of hyperprolactinaemia is correlated with the degree of suppression of the HPG axis.
Abstract: Hyperprolactinaemia is commonly induced by antipsychotic medications that have dopamine-blockade as their main mechanism of action. The purpose of this study was to assess the effect of antipsychotic-induced hyperprolactinaemia on hypothalamic-pituitary-gonadal axis (HPG) function.HPG axis function was assessed in 67 consecutive outpatients who were diagnosed with schizophrenia and stabilized for a period of not less than 2 years on typical antipsychotic medication, by means of clinical history, relevant questionnaires and measurement of plasma prolactin, estradiol, progesterone, testosterone, LH, FSH, sex hormone binding globulin, and TSH levels. Normative laboratory data were used to assess whether hormone levels fell within the reference range for a normal population. There was a significant correlation between dose of medication and plasma prolactin levels for the total group (P<0.001). Prolactin levels were significantly negatively associated with sex hormone levels in females (P<0.05). Males taking antipsychotic medication had a mean prolactin level of 404.1m/IU and mean gonadotrophin and sex hormone levels that fell within normal limits. The results of this study indicate that neuroleptic-induced prolactin secretion is a dose-related side effect and, in females, the level of hyperprolactinaemia is correlated with the degree of suppression of the HPG axis. Women taking long-term prolactin-raising antipsychotic medications are likely to be hyperprolactinaemic and have an associated hypogonadal state. In males, prolactin levels remain within normal limits, but at the upper end, with no apparent disturbance of reproductive hormones.

177 citations

Journal ArticleDOI
Dieter B. Wildenauer1, Sibylle G. Schwab1, Margot Albus, Joachim Hallmayer2, Bernard Lerer, Wolfgang Maier1, Douglas Blackwood3, Walter J. Muir3, David St Clair3, S. W. Morris3, Hans W. Moises4, Liu Yang4, H. Kristbjarnarson, Tómas Helgason, Claudia Wiese4, David A. Collier5, Peter Holmans6, Jo Daniels6, Mark I. Rees6, Philip Asherson6, Queta Roberts6, Alastair G. Cardno6, Maria Arranz5, Homero Vallada5, David Ball5, Hiroshi Kunugi5, Robin M. Murray5, John Powell5, Sin Nanko7, Pak C. Sham5, Michael Gill8, Peter McGuffin6, Michael J. Owen6, Ann E. Pulver9, Stylianos E. Antonarakis10, Robert Babb9, Jean-Louis Blouin10, Nicola DeMarchi11, Beth A. Dombroski12, David E. Housman13, Maria Karayiorgou14, Jurg Ott14, Laura Kasch9, Haig H. Kazazian12, Virginia K. Lasseter9, Erika Loetscher15, Hermann Luebbert, Gerald Nestadt9, Carl Ton13, Paula S. Wolyniec9, Claudine Laurent16, Michel de Chaldée16, Florence Thibaut, M. Jay, Danièle Samolyk16, Michel Petit, Dominique Campion, Jacques Mallet16, Richard E. Straub17, C J MacLean17, Stephen M. Easter17, F. Anthony O'Neill18, Dermot Walsh, Kenneth S. Kendler17, Pablo V. Gejman19, Qiuhe Cao19, Elliot S. Gershon19, Judith A. Badner19, Ethiopia Beshah19, Jing Zhang19, Brien P. Riley20, Swarnageetha Rajagopalan20, Mpala Mogudi-Carter, Trefor Jenkins21, Robert Williamson20, Lynn E. DeLisi22, Chad Garner, Mary Kelly, Carrie LeDuc, Lon R. Cardon, Jay B. Lichter, Tim Harris, J. Loftus23, Gail Shields22, Margarite Comasi24, Antonio Vita24, Angela B. Smith22, Jay Dann23, Geoff Joslyn, Hugh Gurling25, Gursharan Kalsi25, J Brynjolfsson26, David Curtis27, Thordur Sigmundsson25, R Butler25, T Read25, P Murphy25, Andrew Chih-Hui Chen25, Hannes Petursson26, Bill Byerley28, Mark Hoff28, John Holik28, Hilary Coon28, Douglas F. Levinson29, Derek J. Nancarrow30, Derek J. Nancarrow31, Raymond R. Crowe32, Nancy C. Andreasen32, Jeremy M. Silverman33, Richard C. Mohs33, Larry J. Siever33, Jean Endicott34, Lawrence Sharpe34, Marilyn K. Walters31, David P. Lennon30, Nicholas K. Hayward31, Lodewijk A. Sandkuijl35, Bryan J. Mowry30, Harald N. Aschauer, K. Meszaros, Elisabeth Lenzinger, Karoline Fuchs, Angela M. Heiden, Leonid Kruglyak13, Mark J. Daly13, Tara C. Matise34 
TL;DR: Results are interpreted as inconclusive but suggestive of linkage in the latter two regions, and it is concluded that multicenter follow-up linkage studies of complex disorders can help to direct research efforts toward promising regions.
Abstract: In response to reported schizophrenia linkage findings on chromosomes 3, 6 and 8, fourteen research groups genotyped 14 microsatellite markers in an unbiased, collaborative (New) sample of 403-567 informative pedigrees per marker, and in the Original sample which produced each finding (the Johns Hopkins University sample of 46-52 informative pedigrees for chromosomes 3 and 8, and the Medical College of Virginia sample of 156-191 informative pedigrees for chromosome 6). Primary planned analyses (New sample) were two-point heterogeneity lod score (lod2) tests (dominant and recessive affected-only models), and multipoint affected sibling pair (ASP) analysis, with a narrow diagnostic model (DSM-IIIR schizophrenia and schizoaffective disorders). Regions with positive results were also analyzed in the Original and Combined samples. There was no evidence for linkage on chromosome 3. For chromosome 6, ASP maximum lod scores (MLS) were 2.19 (New sample, nominal p = 0.001) and 2.68 (Combined sample, p = .0004). For chromosome 8, maximum lod2 scores (tests of linkage with heterogeneity) were 2.22 (New sample, p = .0014) and 3.06 (Combined sample, p = .00018). Results are interpreted as inconclusive but suggestive of linkage in the latter two regions. We discuss possible reasons for failing to achieve a conclusive result in this large sample. Design issues and limitations of this type of collaborative study are discussed, and it is concluded that multicenter follow-up linkage studies of complex disorders can help to direct research efforts toward promising regions.

176 citations


Cited by
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TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal ArticleDOI
TL;DR: The AUDIT provides a simple method of early detection of hazardous and harmful alcohol use in primary health care settings and is the first instrument of its type to be derived on the basis of a cross-national study.
Abstract: The Alcohol Use Disorders Identification Test (AUDIT) has been developed from a six-country WHO collaborative project as a screening instrument for hazardous and harmful alcohol consumption. It is a 10-item questionnaire which covers the domains of alcohol consumption, drinking behaviour, and alcohol-related problems. Questions were selected from a 150-item assessment schedule (which was administered to 1888 persons attending representative primary health care facilities) on the basis of their representativeness for these conceptual domains and their perceived usefulness for intervention. Responses to each question are scored from 0 to 4, giving a maximum possible score of 40. Among those diagnosed as having hazardous or harmful alcohol use, 92% had an AUDIT score of 8 or more, and 94% of those with non-hazardous consumption had a score of less than 8. AUDIT provides a simple method of early detection of hazardous and harmful alcohol use in primary health care settings and is the first instrument of its type to be derived on the basis of a cross-national study.

11,042 citations

Journal Article
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

9,847 citations

Journal ArticleDOI
TL;DR: This article reviews studies investigating complex brain networks in diverse experimental modalities and provides an accessible introduction to the basic principles of graph theory and highlights the technical challenges and key questions to be addressed by future developments in this rapidly moving field.
Abstract: Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization. The brain's structural and functional systems have features of complex networks--such as small-world topology, highly connected hubs and modularity--both at the whole-brain scale of human neuroimaging and at a cellular scale in non-human animals. In this article, we review studies investigating complex brain networks in diverse experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans) and provide an accessible introduction to the basic principles of graph theory. We also highlight some of the technical challenges and key questions to be addressed by future developments in this rapidly moving field.

9,700 citations

01 Jan 2014
TL;DR: These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care.
Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

9,618 citations