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  • Open Access English
    Authors: 
    Madiha Salman; Jason I. Gerhard; David W. Major; Paolo Pironi; Rory Hadden;
    Countries: United Kingdom, Canada

    Self-sustaining treatment for active remediation (STAR) is an innovative soil remediation approach based on smoldering combustion that has been demonstrated to effectively destroy complex hydrocarbon nonaqueous phase liquids (NAPLs) with minimal energy input. This is the first study to explore the smoldering remediation of sand contaminated by a volatile NAPL (trichloroethylene, TCE) and the first to consider utilizing vegetable oil as supplemental fuel for STAR. Thirty laboratory-scale experiments were conducted to evaluate the relationship between key outcomes (TCE destruction, rate of remediation) to initial conditions (vegetable oil type, oil: TCE mass ratio, neat versus emulsified oils). Several vegetable oils and emulsified vegetable oil formulations were shown to support remediation of TCE via self-sustaining smoldering. A minimum concentration of 14,000 mg/kg canola oil was found to treat sand exhibiting up to 80,000 mg/kg TCE. On average, 75% of the ICE mass was removed due to volatilization. This proof-of-concept study suggests that injection and smoldering of vegetable oil may provide a new alternative for driving volatile contaminants to traditional vapour extraction systems without supplying substantial external energy. (C) 2014 Elsevier B.V. All rights reserved.

  • Open Access English
    Authors: 
    Andrew S Moriarty; Nicholas Meader; Kym I E Snell; Richard D Riley; Lewis William Paton; Carolyn Chew-Graham; Simon Gilbody; Rachel Churchill; Robert S. Phillips; Shehzad Ali; +1 more
    Countries: United Kingdom, United Kingdom, Canada

    BACKGROUND: Relapse (the re-emergence of depressive symptoms after some level of improvement but preceding recovery) and recurrence (onset of a new depressive episode after recovery) are common in depression, lead to worse outcomes and quality of life for patients and exert a high economic cost on society. Outcomes can be predicted by using multivariable prognostic models, which use information about several predictors to produce an individualised risk estimate. The ability to accurately predict relapse or recurrence while patients are well (in remission) would allow the identification of high-risk individuals and may improve overall treatment outcomes for patients by enabling more efficient allocation of interventions to prevent relapse and recurrence. \ud \ud OBJECTIVES: To summarise the predictive performance of prognostic models developed to predict the risk of relapse, recurrence, sustained remission or recovery in adults with major depressive disorder who meet criteria for remission or recovery. \ud \ud SEARCH METHODS: We searched the Cochrane Library (current issue); Ovid MEDLINE (1946 onwards); Ovid Embase (1980 onwards); Ovid PsycINFO (1806 onwards); and Web of Science (1900 onwards) up to May 2020. We also searched sources of grey literature, screened the reference lists of included studies and performed a forward citation search. There were no restrictions applied to the searches by date, language or publication status . \ud \ud SELECTION CRITERIA: We included development and external validation (testing model performance in data separate from the development data) studies of any multivariable prognostic models (including two or more predictors) to predict relapse, recurrence, sustained remission, or recovery in adults (aged 18 years and over) with remitted depression, in any clinical setting. We included all study designs and accepted all definitions of relapse, recurrence and other related outcomes. We did not specify a comparator prognostic model. \ud \ud DATA COLLECTION AND ANALYSIS: Two review authors independently screened references; extracted data (using a template based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS)); and assessed risks of bias of included studies (using the Prediction model Risk Of Bias ASsessment Tool (PROBAST)). We referred any disagreements to a third independent review author. Where we found sufficient (10 or more) external validation studies of an individual model, we planned to perform a meta-analysis of its predictive performance, specifically with respect to its calibration (how well the predicted probabilities match the observed proportions of individuals that experience the outcome) and discrimination (the ability of the model to differentiate between those with and without the outcome). Recommendations could not be qualified using the GRADE system, as guidance is not yet available for prognostic model reviews. \ud \ud MAIN RESULTS: We identified 11 eligible prognostic model studies (10 unique prognostic models). Seven were model development studies; three were model development and external validation studies; and one was an external validation-only study. Multiple estimates of performance measures were not available for any of the models and, meta-analysis was therefore not possible. Ten out of the 11 included studies were assessed as being at high overall risk of bias. Common weaknesses included insufficient sample size, inappropriate handling of missing data and lack of information about discrimination and calibration. One paper (Klein 2018) was at low overall risk of bias and presented a prognostic model including the following predictors: number of previous depressive episodes, residual depressive symptoms and severity of the last depressive episode. The external predictive performance of this model was poor (C-statistic 0.59; calibration slope 0.56; confidence intervals not reported). None of the identified studies examined the clinical utility (net benefit) of the developed model.\ud \ud AUTHORS' CONCLUSIONS: Of the 10 prognostic models identified (across 11 studies), only four underwent external validation. Most of the studies (n = 10) were assessed as being at high overall risk of bias, and the one study that was at low risk of bias presented a model with poor predictive performance. There is a need for improved prognostic research in this clinical area, with future studies conforming to current best practice recommendations for prognostic model development/validation and reporting findings in line with the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement.

  • Open Access English
    Authors: 
    Amresh Shrivastava; Megan Johnston; Nilesh Shah; Marco Innamorati; Larry Stitt; Meghana Thakar; David Lester; Maurizio Pompili;
    Publisher: Dove Press
    Country: Canada

    Amresh Shrivastava1, Megan E Johnston2, Nilesh Shah3, Marco Innamorati4, Larry Stitt5, Meghana Thakar3, David Lester6, Maurizio Pompili4,71Silver Mind Hospital and Mental Health Foundation of India, Mumbai, India; 2Department of Psychology, University of Toronto, Toronto, ON, Canada; 3Lokmanya Tilak Municipal General Hospital, University of Mumbai, India; 4Department of Neurosciences, Mental Health and Sensory Functions, Suicide Prevention Center, Sant’Andrea Hospital, Sapienza University of Rome, Rome, Italy; 5Department of Biostatistics, The University of Western Ontario, London, ON, Canada; 6The Richard Stockton College of New Jersey, Pomona, NJ, USA; 7McLean Hospital, Harvard Medical School, Boston, MA, USABackground: Suicide is a major problem in schizophrenia, estimated to affect 9%–13% of patients. About 25% of schizophrenic patients make at least one suicide attempt in their lifetime. Current outcome measures do not address this problem, even though it affects quality of life and patient safety. The aim of this study was to assess suicidality in long-term clinically improved schizophrenia patients who were treated in a nongovernmental psychiatric treatment centre in Mumbai, India.Method: Participants were 61 patients out of 200 consecutive hospitalized first-episode patients with schizophrenia diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders who were much improved on the Clinical Global Impression Scale-Improvement (CGI-I) scale at the endpoint of a 10-year follow-up. Clinical assessment tools included the Positive and Negative Syndrome Scale for Schizophrenia, CGI-I, Global Assessment of Functioning, and suicidality.Results: Many of the patients, although clinically improved, experienced emerging suicidality during the 10-year follow-up period. All of the patients reported significant suicidality (ie, suicide attempts, suicidal crises, or suicidal ideation) at the end of the study, whereas only 83% had reported previous significant suicidality at baseline. No sociodemographic and clinical variables at baseline were predictive of suicidal status at the end of the 10-year follow-up.Conclusion: Schizophrenia is a complex neurobehavioral disorder that appears to be closely associated with suicidal behavior. Adequate assessment and management of suicidality needs to be a continual process, even in patients who respond well to treatment.Keywords: schizophrenia, suicide risk, prevention 

  • Open Access English
    Authors: 
    Craig Campbell; Richard J. Barohn; Enrico Bertini; Brigitte Chabrol; Giacomo P. Comi; Basil T. Darras; Richard S. Finkel; Kevin M. Flanigan; Nathalie Goemans; Susan T. Iannaccone; +25 more
    Publisher: FUTURE MEDICINE LTD
    Countries: Canada, Belgium, Germany

    Aim: Assess the totality of efficacy evidence for ataluren in patients with nonsense mutation Duchenne muscular dystrophy (nmDMD). Materials & methods: Data from the two completed randomized controlled trials (ClinicalTrials.gov: NCT00592553; NCT01826487) of ataluren in nmDMD were combined to examine the intent-to-treat (ITT) populations and two patient subgroups (baseline 6-min walk distance [6MWD] ≥300-<400 or <400 m). Meta-analyses examined 6MWD change from baseline to week 48. Results: Statistically significant differences in 6MWD change with ataluren versus placebo were observed across all three meta-analyses. Least-squares mean difference (95% CI): ITT (n = 342), +17.2 (0.2-34.1) m, p = 0.0473; ≥300-<400 m (n = 143), +43.9 (18.2-69.6) m, p = 0.0008; <400 m (n = 216), +27.7 (6.4-49.0) m, p = 0.0109. Conclusion: These meta-analyses support previous evidence for ataluren in slowing disease progression versus placebo in patients with nmDMD over 48 weeks. Treatment benefit was most evident in patients with a baseline 6MWD ≥300-<400 m (the ambulatory transition phase), thereby informing future trial design. ispartof: JOURNAL OF COMPARATIVE EFFECTIVENESS RESEARCH vol:9 issue:14 pages:973-984 ispartof: location:England status: published

  • Open Access English
    Authors: 
    Steven G. Greening; Derek G.V. Mitchell; Fraser W. Smith;
    Countries: Canada, United Kingdom
    Project: SSHRC

    A network of cortical and sub-cortical regions is known to be important in the processing of facial expression. However, to date no study has investigated whether representations of facial expressions present in this network permit generalization across independent samples of face information (e.g., eye region vs mouth region). We presented participants with partial face samples of five expression categories in a rapid event-related fMRI experiment. We reveal a network of face-sensitive regions that contain information about facial expression categories regardless of which part of the face is presented. We further reveal that the neural information present in a subset of these regions: dorsal prefrontal cortex (dPFC), superior temporal sulcus (STS), lateral occipital and ventral temporal cortex, and even early visual cortex, enables reliable generalization across independent visual inputs (faces depicting the 'eyes only' vs 'eyes removed'). Furthermore, classification performance was correlated to behavioral performance in STS and dPFC. Our results demonstrate that both higher (e.g., STS, dPFC) and lower level cortical regions contain information useful for facial expression decoding that go beyond the visual information presented, and implicate a key role for contextual mechanisms such as cortical feedback in facial expression perception under challenging conditions of visual occlusion. (C) 2017 Elsevier Ltd. All rights reserved.

  • Publication . Article . Other literature type . 2018
    Open Access English
    Authors: 
    Karen Horsburgh; Joanna M. Wardlaw; Tom van Agtmael; Stuart M. Allan; Mike L.J. Ashford; Philip M. Bath; Rosalind Brown; Jason Berwick; M. Zameel Cader; Roxana O. Carare; +36 more
    Publisher: Portland Press
    Countries: United Kingdom, United Kingdom, United Kingdom, Canada, United Kingdom, United Kingdom, United Kingdom, United Kingdom, United Kingdom, United Kingdom

    Cerebral small vessel disease (SVD) is a major health challenge. Therapeutic approaches remain limited, hampered by the lack of mechanistic understanding and identification of therapeutic targets. Relevant animal models could provide a cornerstone to basic scientific studies of disease mechanisms and pre-clinical studies of potential therapies, but there is a critical need to improve the current translational gap that exists between pre-clinical research and treatments in patients. The Medical Research Council Dementias Platform UK (MRC DPUK) Vascular Experimental Medicine Theme identified that a comprehensive assessment of the latest developments in animal models and of their contribution to understanding of cerebral microvascular disease would reduce the translational gap. In response to this, a two day workshop took place in late January 2017 at the British Heart Foundation Centre of Research Excellence in Glasgow, Scotland in conjunction with MRC DPUK and brought together experts from several disciplines in cerebrovascular disease, dementia and cardiovascular biology, to highlight current advances in these fields, explore synergies and scope for development. There were presentations from UK and international researchers and a specific focus on animal models of cerebral microvascular disease and dementia, considering vascular biology, neurogliovascular coupling, blood-brain barrier function, neuroinflammation, cerebral drainage pathways, and methodological and translational challenges (see Figure 1 for the general organisation of the meeting including the key topics and themes discussed). This overview provides a summary of the key talks, with a particular focus on mechanisms of cerebral vascular disease (see Figure 2) and improving translation. These talks were followed by related themed discussion groups on the gaps in knowledge and requirements to advance knowledge, the outcomes of which are highlighted in Table 1. Additional related articles are published in the Special Edition of Clinical Science (http://www.portlandpresspublishing.com/cc/small-vessels).

  • Open Access English
    Authors: 
    Rebecca M. Todd; Taylor W. Schmitz; Josh Susskind; Adam K. Anderson;
    Publisher: Frontiers Media S.A.
    Country: Canada

    It is well known that emotionally salient events are remembered more vividly than mundane ones. Our recent research has demonstrated that such memory vividness is due in part to the subjective experience of emotional events as more perceptually vivid, an effect we call emotion-enhanced vividness, or EEV. The present study built on previously reported research in which fMRI data were collected while participants rated relative levels of visual noise overlaid on emotionally salient and neutral images. Ratings of greater EEV were associated with greater activation in the amygdala, visual cortex, and posterior insula. In the present study, we measured BOLD activation that predicted recognition memory vividness for these same images one week later. Results showed that, after controlling for differences between scenes in low-level objective features, hippocampus activation uniquely predicted subsequent memory vividness. In contrast, amygdala and visual cortex regions that were sensitive to EEV were also modulated by subsequent ratings of memory vividness. These findings suggest shared neural substrates for the influence of emotional salience on perceptual and mnemonic vividness, with amygdala and visual cortex activation at encoding contributing to the experience of both perception and subsequent memory. © 2013 Todd, Schmitz, Susskind and Anderson.

  • Open Access English
    Authors: 
    Robert Smith; Sze Chai Hung; Joyce Goh; Hoi Lam Ip; Daniel Y. T. Fong; Shehzad Ali; Claire A Wilson; Kris Yuet Wan Lok;
    Publisher: BMJ Publishing Group
    Country: Canada

    IntroductionPerinatal depression is common and can often lead to adverse health outcomes for mother and child. Multiple pharmacological and non-pharmacological treatments have been evaluated against usual care or placebo controls in meta-analyses for preventing and treating perinatal depression compared. It is not yet established which of these candidate treatments might be the optimal approach for prevention or treatment.Methods and analysisA systematic review and Bayesian network meta-analyses will be conducted. Eight electronic databases shall be searched for randomised controlled trials that have evaluated the effectiveness of treatments for prevention and/or treatment of perinatal depression. Screening of articles shall be conducted by two reviewers independently. One network meta-analysis shall evaluate the effectiveness of interventions in preventing depression during the perinatal period. A second network meta-analysis shall compare the effectiveness of treatments for depression symptoms in women with perinatal depression. Bayesian 95% credible intervals shall be used to estimate the pooled mean effect size of each treatment, and surface under cumulative ranking area will be used to rank the treatments’ effectiveness.Ethics and disseminationWe shall report our findings so that healthcare providers can make informed decisions on what might be the optimal approach for addressing perinatal depression to prevent cases and improve outcomes in those suffering from depression through knowledge exchange workshops, international conference presentations and journal article publications.PROSPERO registration numberCRD42020200081.

  • Open Access English
    Authors: 
    Patel, Priya; Robinson, Paula D.; Thackray, Jennifer; Flank, Jacqueline; Holdsworth, Mark T.; Gibson, Paul; Orsey, Andrea; Portwine, Carol; Freedman, Jason; Madden, Jennifer R.; +3 more
    Countries: United Kingdom, Canada

    This update of the 2013 clinical practice guideline provides clinicians with guidance regarding the use of aprepitant and palonosetron for the prevention of acute chemotherapy-induced nausea and vomiting (CINV) in children. The recommendations were based on three systematic reviews. Substantive changes were made to the guideline recommendations including the inclusion of palonosetron to the 5-HT3 antagonists recommended for children receiving highly emetogenic chemotherapy (HEC) and the recommendation of aprepitant for children 6 months of age or older receiving HEC. To optimize CINV control in children, future work must focus on closing critical research gaps.

  • Open Access English
    Authors: 
    Christina Jerosch-Herold; Rachel Chester; Lee Shepstone; Joshua I. Vincent; Joy C. MacDermid;
    Countries: Canada, United Kingdom

    © 2017, Springer International Publishing AG, part of Springer Nature. Purpose: The shoulder pain and disability index (SPADI) has been extensively evaluated for its psychometric properties using classical test theory (CTT). The purpose of this study was to evaluate its structural validity using Rasch model analysis. Methods: Responses to the SPADI from 1030 patients referred for physiotherapy with shoulder pain and enrolled in a prospective cohort study were available for Rasch model analysis. Overall fit, individual person and item fit, response format, dependence, unidimensionality, targeting, reliability and differential item functioning (DIF) were examined. Results: The SPADI pain subscale initially demonstrated a misfit due to DIF by age and gender. After iterative analysis it showed good fit to the Rasch model with acceptable targeting and unidimensionality (overall fit Chi-square statistic 57.2, p = 0.1; mean item fit residual 0.19 (1.5) and mean person fit residual 0.44 (1.1); person separation index (PSI) of 0.83. The disability subscale however shows significant misfit due to uniform DIF even after iterative analyses were used to explore different solutions to the sources of misfit (overall fit (Chi-square statistic 57.2, p = 0.1); mean item fit residual 0.54 (1.26) and mean person fit residual 0.38 (1.0); PSI 0.84). Conclusions: Rasch Model analysis of the SPADI has identified some strengths and limitations not previously observed using CTT methods. The SPADI should be treated as two separate subscales. The SPADI is a widely used outcome measure in clinical practice and research; however, the scores derived from it must be interpreted with caution. The pain subscale fits the Rasch model expectations well. The disability subscale does not fit the Rasch model and its current format does not meet the criteria for true interval-level measurement required for use as a primary endpoint in clinical trials. Clinicians should therefore exercise caution when interpreting score changes on the disability subscale and attempt to compare their scores to age- and sex-stratified data.

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Include:
The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
227 Research products, page 1 of 23
  • Open Access English
    Authors: 
    Madiha Salman; Jason I. Gerhard; David W. Major; Paolo Pironi; Rory Hadden;
    Countries: United Kingdom, Canada

    Self-sustaining treatment for active remediation (STAR) is an innovative soil remediation approach based on smoldering combustion that has been demonstrated to effectively destroy complex hydrocarbon nonaqueous phase liquids (NAPLs) with minimal energy input. This is the first study to explore the smoldering remediation of sand contaminated by a volatile NAPL (trichloroethylene, TCE) and the first to consider utilizing vegetable oil as supplemental fuel for STAR. Thirty laboratory-scale experiments were conducted to evaluate the relationship between key outcomes (TCE destruction, rate of remediation) to initial conditions (vegetable oil type, oil: TCE mass ratio, neat versus emulsified oils). Several vegetable oils and emulsified vegetable oil formulations were shown to support remediation of TCE via self-sustaining smoldering. A minimum concentration of 14,000 mg/kg canola oil was found to treat sand exhibiting up to 80,000 mg/kg TCE. On average, 75% of the ICE mass was removed due to volatilization. This proof-of-concept study suggests that injection and smoldering of vegetable oil may provide a new alternative for driving volatile contaminants to traditional vapour extraction systems without supplying substantial external energy. (C) 2014 Elsevier B.V. All rights reserved.

  • Open Access English
    Authors: 
    Andrew S Moriarty; Nicholas Meader; Kym I E Snell; Richard D Riley; Lewis William Paton; Carolyn Chew-Graham; Simon Gilbody; Rachel Churchill; Robert S. Phillips; Shehzad Ali; +1 more
    Countries: United Kingdom, United Kingdom, Canada

    BACKGROUND: Relapse (the re-emergence of depressive symptoms after some level of improvement but preceding recovery) and recurrence (onset of a new depressive episode after recovery) are common in depression, lead to worse outcomes and quality of life for patients and exert a high economic cost on society. Outcomes can be predicted by using multivariable prognostic models, which use information about several predictors to produce an individualised risk estimate. The ability to accurately predict relapse or recurrence while patients are well (in remission) would allow the identification of high-risk individuals and may improve overall treatment outcomes for patients by enabling more efficient allocation of interventions to prevent relapse and recurrence. \ud \ud OBJECTIVES: To summarise the predictive performance of prognostic models developed to predict the risk of relapse, recurrence, sustained remission or recovery in adults with major depressive disorder who meet criteria for remission or recovery. \ud \ud SEARCH METHODS: We searched the Cochrane Library (current issue); Ovid MEDLINE (1946 onwards); Ovid Embase (1980 onwards); Ovid PsycINFO (1806 onwards); and Web of Science (1900 onwards) up to May 2020. We also searched sources of grey literature, screened the reference lists of included studies and performed a forward citation search. There were no restrictions applied to the searches by date, language or publication status . \ud \ud SELECTION CRITERIA: We included development and external validation (testing model performance in data separate from the development data) studies of any multivariable prognostic models (including two or more predictors) to predict relapse, recurrence, sustained remission, or recovery in adults (aged 18 years and over) with remitted depression, in any clinical setting. We included all study designs and accepted all definitions of relapse, recurrence and other related outcomes. We did not specify a comparator prognostic model. \ud \ud DATA COLLECTION AND ANALYSIS: Two review authors independently screened references; extracted data (using a template based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS)); and assessed risks of bias of included studies (using the Prediction model Risk Of Bias ASsessment Tool (PROBAST)). We referred any disagreements to a third independent review author. Where we found sufficient (10 or more) external validation studies of an individual model, we planned to perform a meta-analysis of its predictive performance, specifically with respect to its calibration (how well the predicted probabilities match the observed proportions of individuals that experience the outcome) and discrimination (the ability of the model to differentiate between those with and without the outcome). Recommendations could not be qualified using the GRADE system, as guidance is not yet available for prognostic model reviews. \ud \ud MAIN RESULTS: We identified 11 eligible prognostic model studies (10 unique prognostic models). Seven were model development studies; three were model development and external validation studies; and one was an external validation-only study. Multiple estimates of performance measures were not available for any of the models and, meta-analysis was therefore not possible. Ten out of the 11 included studies were assessed as being at high overall risk of bias. Common weaknesses included insufficient sample size, inappropriate handling of missing data and lack of information about discrimination and calibration. One paper (Klein 2018) was at low overall risk of bias and presented a prognostic model including the following predictors: number of previous depressive episodes, residual depressive symptoms and severity of the last depressive episode. The external predictive performance of this model was poor (C-statistic 0.59; calibration slope 0.56; confidence intervals not reported). None of the identified studies examined the clinical utility (net benefit) of the developed model.\ud \ud AUTHORS' CONCLUSIONS: Of the 10 prognostic models identified (across 11 studies), only four underwent external validation. Most of the studies (n = 10) were assessed as being at high overall risk of bias, and the one study that was at low risk of bias presented a model with poor predictive performance. There is a need for improved prognostic research in this clinical area, with future studies conforming to current best practice recommendations for prognostic model development/validation and reporting findings in line with the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement.

  • Open Access English
    Authors: 
    Amresh Shrivastava; Megan Johnston; Nilesh Shah; Marco Innamorati; Larry Stitt; Meghana Thakar; David Lester; Maurizio Pompili;
    Publisher: Dove Press
    Country: Canada

    Amresh Shrivastava1, Megan E Johnston2, Nilesh Shah3, Marco Innamorati4, Larry Stitt5, Meghana Thakar3, David Lester6, Maurizio Pompili4,71Silver Mind Hospital and Mental Health Foundation of India, Mumbai, India; 2Department of Psychology, University of Toronto, Toronto, ON, Canada; 3Lokmanya Tilak Municipal General Hospital, University of Mumbai, India; 4Department of Neurosciences, Mental Health and Sensory Functions, Suicide Prevention Center, Sant&rsquo;Andrea Hospital, Sapienza University of Rome, Rome, Italy; 5Department of Biostatistics, The University of Western Ontario, London, ON, Canada; 6The Richard Stockton College of New Jersey, Pomona, NJ, USA; 7McLean Hospital, Harvard Medical School, Boston, MA, USABackground: Suicide is a major problem in schizophrenia, estimated to affect 9%&ndash;13% of patients. About 25% of schizophrenic patients make at least one suicide attempt in their lifetime. Current outcome measures do not address this problem, even though it affects quality of life and patient safety. The aim of this study was to assess suicidality in long-term clinically improved schizophrenia patients who were treated in a nongovernmental psychiatric treatment centre in Mumbai, India.Method: Participants were 61 patients out of 200 consecutive hospitalized first-episode patients with schizophrenia diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders who were much improved on the Clinical Global Impression Scale-Improvement (CGI-I) scale at the endpoint of a 10-year follow-up. Clinical assessment tools included the Positive and Negative Syndrome Scale for Schizophrenia, CGI-I, Global Assessment of Functioning, and suicidality.Results: Many of the patients, although clinically improved, experienced emerging suicidality during the 10-year follow-up period. All of the patients reported significant suicidality (ie, suicide attempts, suicidal crises, or suicidal ideation) at the end of the study, whereas only 83% had reported previous significant suicidality at baseline. No sociodemographic and clinical variables at baseline were predictive of suicidal status at the end of the 10-year follow-up.Conclusion: Schizophrenia is a complex neurobehavioral disorder that appears to be closely associated with suicidal behavior. Adequate assessment and management of suicidality needs to be a continual process, even in patients who respond well to treatment.Keywords: schizophrenia, suicide risk, prevention&nbsp;

  • Open Access English
    Authors: 
    Craig Campbell; Richard J. Barohn; Enrico Bertini; Brigitte Chabrol; Giacomo P. Comi; Basil T. Darras; Richard S. Finkel; Kevin M. Flanigan; Nathalie Goemans; Susan T. Iannaccone; +25 more
    Publisher: FUTURE MEDICINE LTD
    Countries: Canada, Belgium, Germany

    Aim: Assess the totality of efficacy evidence for ataluren in patients with nonsense mutation Duchenne muscular dystrophy (nmDMD). Materials & methods: Data from the two completed randomized controlled trials (ClinicalTrials.gov: NCT00592553; NCT01826487) of ataluren in nmDMD were combined to examine the intent-to-treat (ITT) populations and two patient subgroups (baseline 6-min walk distance [6MWD] ≥300-<400 or <400 m). Meta-analyses examined 6MWD change from baseline to week 48. Results: Statistically significant differences in 6MWD change with ataluren versus placebo were observed across all three meta-analyses. Least-squares mean difference (95% CI): ITT (n = 342), +17.2 (0.2-34.1) m, p = 0.0473; ≥300-<400 m (n = 143), +43.9 (18.2-69.6) m, p = 0.0008; <400 m (n = 216), +27.7 (6.4-49.0) m, p = 0.0109. Conclusion: These meta-analyses support previous evidence for ataluren in slowing disease progression versus placebo in patients with nmDMD over 48 weeks. Treatment benefit was most evident in patients with a baseline 6MWD ≥300-<400 m (the ambulatory transition phase), thereby informing future trial design. ispartof: JOURNAL OF COMPARATIVE EFFECTIVENESS RESEARCH vol:9 issue:14 pages:973-984 ispartof: location:England status: published

  • Open Access English
    Authors: 
    Steven G. Greening; Derek G.V. Mitchell; Fraser W. Smith;
    Countries: Canada, United Kingdom
    Project: SSHRC

    A network of cortical and sub-cortical regions is known to be important in the processing of facial expression. However, to date no study has investigated whether representations of facial expressions present in this network permit generalization across independent samples of face information (e.g., eye region vs mouth region). We presented participants with partial face samples of five expression categories in a rapid event-related fMRI experiment. We reveal a network of face-sensitive regions that contain information about facial expression categories regardless of which part of the face is presented. We further reveal that the neural information present in a subset of these regions: dorsal prefrontal cortex (dPFC), superior temporal sulcus (STS), lateral occipital and ventral temporal cortex, and even early visual cortex, enables reliable generalization across independent visual inputs (faces depicting the 'eyes only' vs 'eyes removed'). Furthermore, classification performance was correlated to behavioral performance in STS and dPFC. Our results demonstrate that both higher (e.g., STS, dPFC) and lower level cortical regions contain information useful for facial expression decoding that go beyond the visual information presented, and implicate a key role for contextual mechanisms such as cortical feedback in facial expression perception under challenging conditions of visual occlusion. (C) 2017 Elsevier Ltd. All rights reserved.

  • Publication . Article . Other literature type . 2018
    Open Access English
    Authors: 
    Karen Horsburgh; Joanna M. Wardlaw; Tom van Agtmael; Stuart M. Allan; Mike L.J. Ashford; Philip M. Bath; Rosalind Brown; Jason Berwick; M. Zameel Cader; Roxana O. Carare; +36 more
    Publisher: Portland Press
    Countries: United Kingdom, United Kingdom, United Kingdom, Canada, United Kingdom, United Kingdom, United Kingdom, United Kingdom, United Kingdom, United Kingdom

    Cerebral small vessel disease (SVD) is a major health challenge. Therapeutic approaches remain limited, hampered by the lack of mechanistic understanding and identification of therapeutic targets. Relevant animal models could provide a cornerstone to basic scientific studies of disease mechanisms and pre-clinical studies of potential therapies, but there is a critical need to improve the current translational gap that exists between pre-clinical research and treatments in patients. The Medical Research Council Dementias Platform UK (MRC DPUK) Vascular Experimental Medicine Theme identified that a comprehensive assessment of the latest developments in animal models and of their contribution to understanding of cerebral microvascular disease would reduce the translational gap. In response to this, a two day workshop took place in late January 2017 at the British Heart Foundation Centre of Research Excellence in Glasgow, Scotland in conjunction with MRC DPUK and brought together experts from several disciplines in cerebrovascular disease, dementia and cardiovascular biology, to highlight current advances in these fields, explore synergies and scope for development. There were presentations from UK and international researchers and a specific focus on animal models of cerebral microvascular disease and dementia, considering vascular biology, neurogliovascular coupling, blood-brain barrier function, neuroinflammation, cerebral drainage pathways, and methodological and translational challenges (see Figure 1 for the general organisation of the meeting including the key topics and themes discussed). This overview provides a summary of the key talks, with a particular focus on mechanisms of cerebral vascular disease (see Figure 2) and improving translation. These talks were followed by related themed discussion groups on the gaps in knowledge and requirements to advance knowledge, the outcomes of which are highlighted in Table 1. Additional related articles are published in the Special Edition of Clinical Science (http://www.portlandpresspublishing.com/cc/small-vessels).

  • Open Access English
    Authors: 
    Rebecca M. Todd; Taylor W. Schmitz; Josh Susskind; Adam K. Anderson;
    Publisher: Frontiers Media S.A.
    Country: Canada

    It is well known that emotionally salient events are remembered more vividly than mundane ones. Our recent research has demonstrated that such memory vividness is due in part to the subjective experience of emotional events as more perceptually vivid, an effect we call emotion-enhanced vividness, or EEV. The present study built on previously reported research in which fMRI data were collected while participants rated relative levels of visual noise overlaid on emotionally salient and neutral images. Ratings of greater EEV were associated with greater activation in the amygdala, visual cortex, and posterior insula. In the present study, we measured BOLD activation that predicted recognition memory vividness for these same images one week later. Results showed that, after controlling for differences between scenes in low-level objective features, hippocampus activation uniquely predicted subsequent memory vividness. In contrast, amygdala and visual cortex regions that were sensitive to EEV were also modulated by subsequent ratings of memory vividness. These findings suggest shared neural substrates for the influence of emotional salience on perceptual and mnemonic vividness, with amygdala and visual cortex activation at encoding contributing to the experience of both perception and subsequent memory. © 2013 Todd, Schmitz, Susskind and Anderson.

  • Open Access English
    Authors: 
    Robert Smith; Sze Chai Hung; Joyce Goh; Hoi Lam Ip; Daniel Y. T. Fong; Shehzad Ali; Claire A Wilson; Kris Yuet Wan Lok;
    Publisher: BMJ Publishing Group
    Country: Canada

    IntroductionPerinatal depression is common and can often lead to adverse health outcomes for mother and child. Multiple pharmacological and non-pharmacological treatments have been evaluated against usual care or placebo controls in meta-analyses for preventing and treating perinatal depression compared. It is not yet established which of these candidate treatments might be the optimal approach for prevention or treatment.Methods and analysisA systematic review and Bayesian network meta-analyses will be conducted. Eight electronic databases shall be searched for randomised controlled trials that have evaluated the effectiveness of treatments for prevention and/or treatment of perinatal depression. Screening of articles shall be conducted by two reviewers independently. One network meta-analysis shall evaluate the effectiveness of interventions in preventing depression during the perinatal period. A second network meta-analysis shall compare the effectiveness of treatments for depression symptoms in women with perinatal depression. Bayesian 95% credible intervals shall be used to estimate the pooled mean effect size of each treatment, and surface under cumulative ranking area will be used to rank the treatments’ effectiveness.Ethics and disseminationWe shall report our findings so that healthcare providers can make informed decisions on what might be the optimal approach for addressing perinatal depression to prevent cases and improve outcomes in those suffering from depression through knowledge exchange workshops, international conference presentations and journal article publications.PROSPERO registration numberCRD42020200081.

  • Open Access English
    Authors: 
    Patel, Priya; Robinson, Paula D.; Thackray, Jennifer; Flank, Jacqueline; Holdsworth, Mark T.; Gibson, Paul; Orsey, Andrea; Portwine, Carol; Freedman, Jason; Madden, Jennifer R.; +3 more
    Countries: United Kingdom, Canada

    This update of the 2013 clinical practice guideline provides clinicians with guidance regarding the use of aprepitant and palonosetron for the prevention of acute chemotherapy-induced nausea and vomiting (CINV) in children. The recommendations were based on three systematic reviews. Substantive changes were made to the guideline recommendations including the inclusion of palonosetron to the 5-HT3 antagonists recommended for children receiving highly emetogenic chemotherapy (HEC) and the recommendation of aprepitant for children 6 months of age or older receiving HEC. To optimize CINV control in children, future work must focus on closing critical research gaps.

  • Open Access English
    Authors: 
    Christina Jerosch-Herold; Rachel Chester; Lee Shepstone; Joshua I. Vincent; Joy C. MacDermid;
    Countries: Canada, United Kingdom

    © 2017, Springer International Publishing AG, part of Springer Nature. Purpose: The shoulder pain and disability index (SPADI) has been extensively evaluated for its psychometric properties using classical test theory (CTT). The purpose of this study was to evaluate its structural validity using Rasch model analysis. Methods: Responses to the SPADI from 1030 patients referred for physiotherapy with shoulder pain and enrolled in a prospective cohort study were available for Rasch model analysis. Overall fit, individual person and item fit, response format, dependence, unidimensionality, targeting, reliability and differential item functioning (DIF) were examined. Results: The SPADI pain subscale initially demonstrated a misfit due to DIF by age and gender. After iterative analysis it showed good fit to the Rasch model with acceptable targeting and unidimensionality (overall fit Chi-square statistic 57.2, p = 0.1; mean item fit residual 0.19 (1.5) and mean person fit residual 0.44 (1.1); person separation index (PSI) of 0.83. The disability subscale however shows significant misfit due to uniform DIF even after iterative analyses were used to explore different solutions to the sources of misfit (overall fit (Chi-square statistic 57.2, p = 0.1); mean item fit residual 0.54 (1.26) and mean person fit residual 0.38 (1.0); PSI 0.84). Conclusions: Rasch Model analysis of the SPADI has identified some strengths and limitations not previously observed using CTT methods. The SPADI should be treated as two separate subscales. The SPADI is a widely used outcome measure in clinical practice and research; however, the scores derived from it must be interpreted with caution. The pain subscale fits the Rasch model expectations well. The disability subscale does not fit the Rasch model and its current format does not meet the criteria for true interval-level measurement required for use as a primary endpoint in clinical trials. Clinicians should therefore exercise caution when interpreting score changes on the disability subscale and attempt to compare their scores to age- and sex-stratified data.