The improved Clinical Global Impression Scale (iCGI): development and validation in depression

BACKGROUND: The Clinical Global Impression scale (CGI) is frequently used in medical care and clinical research because of its face validity and practicability. This study proposes to improve the reliability of the Clinical Global Impression (CGI) scale in depressive disorders by the use of a semi-standardized interview, a new response format, and a Delphi procedure. METHODS: Thirty patients hospitalised for a major depressive episode were filmed at T1 (first week in hospital) and at T2 (2 weeks later) during a 5' specific interview. The Hamilton Depressive Rating Scale and the Symptom Check List were also rated. Eleven psychiatrists rated these videos using either the usual CGI response format or an improved response format, with or without a Delphi procedure. RESULTS: The new response format slightly improved (but not significantly) the interrater agreement, the Delphi procedure did not. The best results were obtained when ratings by 4 independent raters were averaged. In this situation, intraclass correlation coefficients were about 0.9. CONCLUSION: The Clinical Global Impression is a useful approach in psychiatry since it apprehends patients in their entirety. This study shows that it is possible to quantify such impressions with a high level of interrater agreement

A method for biomarker measurements in peripheral blood mononuclear cells isolated from anxious and depressed mice: β-arrestin 1 protein levels in depression and treatment

A limited number of biomarkers in the central and peripheral systems which are known may be useful for diagnosing major depressive disorders and predicting the effectiveness of antidepressant (AD) treatments. Since 60% of depressed patients do not respond adequately to medication or are resistant to ADs, it is imperative to delineate more accurate biomarkers. Recent clinical studies suggest that β-arrestin 1 levels in human mononuclear leukocytes may be an efficient biomarker. If potential biomarkers such as β-arrestin 1 could be assessed from a source such as peripheral blood cells, then they could be easily monitored and used to predict therapeutic responses. However, no previous studies have measured β-arrestin 1 levels in peripheral blood mononuclear cells (PBMCs) in anxious/depressive rodents. This study aimed to develop a method to detect β-arrestin protein levels through immunoblot analyses of mouse PBMCs isolated from whole blood. In order to validate the approach, β-arrestin levels were then compared in naïve, anxious/depressed mice, and anxious/depressed mice treated with a selective serotonin reuptake inhibitor (fluoxetine, 18 mg/kg/day in the drinking water). The results demonstrated that mouse whole blood collected by submandibular bleeding permitted isolation of enough PBMCs to assess circulating proteins such as β-arrestin 1. β-Arrestin 1 levels were successfully measured in healthy human subject and naïve mouse PBMCs. Interestingly, PBMCs from anxious/depressed mice showed significantly reduced β-arrestin 1 levels. These decreased β-arrestin 1 expression levels were restored to normal levels with chronic fluoxetine treatment. The results suggest that isolation of PBMCs from mice by submandibular bleeding is a useful technique to screen putative biomarkers of the pathophysiology of mood disorders and the response to ADs. In addition, these results confirm that β-arrestin 1 is a potential biomarker for depression

Report of depressive symptoms on waiting list and mortality after liver and kidney transplantation: a prospective cohort study

International audienceABSTRACT: BACKGROUND: Little research has explored pre-transplantation psychological factors as predictors of outcome after liver or kidney transplantation. Our objective is to determine whether report of depressive symptoms on waiting list predicts outcome of liver and kidney transplantation. METHODS: Patients on waiting list for liver or kidney transplantation were classified for report or non-report of depressive symptoms on waiting list. 339 were transplanted 6 months later on average, and followed prospectively. The main outcome measures were graft failure and mortality 18 months post-transplantation. RESULTS: Among the 339 patients, 51.6% reported depressive symptoms on waiting list, 16.5% had a graft failure and 7.4% died post-transplantation. Report of depressive symptoms on waiting list predicted a 3 to 4-fold decreased risk of graft failure and mortality 18-months post-transplantation, independently from age, gender, current cigarette smoking, anxiety symptoms, main primary diagnosis, UNOS score, number of comorbid diagnoses and history of transplantation. Data were consistent for liver and kidney transplantations. Other baseline predictive factors were: for graft failure, the main primary diagnosis and a shorter length since this diagnosis, and for mortality, older age, male gender and the main primary diagnosis. CONCLUSION: Further studies are needed to understand the underlying mechanisms of the association between report of depressive symptoms on waiting list and decreased risk of graft failure and mortality after transplantation

DenseNet and Support Vector Machine classifications of major depressive disorder using vertex-wise cortical features

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing an extensive sample of people with MDD (N=2,772) and HC (N=4,240), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible

L'enjeu de la mortalité dans la schizophrénie

Les antipsychotiques de première puis de deuxième génération ont permis des avancées essentielles dans le traitement des schizophrénies. Ainsi, l'amélioration par les antipsychotiques des symptômes positifs n'est aujourd'hui plus remise en question. Plus encore, ces traitements ont permis depuis les années 50 la "désinstitutionnalisation" d'une majorité de patients schizophrènes et la naissance d'une psychiatrie moderne traitant ses patients dans la cité. Mais, de nombreuses cibles thérapeutiques n'ont pas encore été atteintes et demeurent des enjeux thérapeutiques. Celui qui retiendra notre attention dans cet article est la mortalité des patients schizophrènes, mortalité par suicide certes, mais aussi mortalité de causes somatiques. On peut espérer que la recherche thérapeutique dans le domaine des médicaments psychotropes s'orientera dans les prochaines années vers la mise en évidence, non seulement d'une efficacité plus marquée sur les paramètres psychiques et une meilleure tolérance, mais également, comme dans les autres domaines thérapeutiques, d'une amélioration de la mortalité des patients schizophrènes traités

Méthodes d'évaluation : échelles, paramètres cliniques et biologiques

L'évaluation de la symptomatologie dépressive dans les essais médicamenteux est limitée par une difficulté majeure : l'absence de validateur externe. De même, la standardisation requise par les autorités réglementaires d'enregistrement des nouvelles molécules a pour conséquence directe que les méthodes utilisées sont relativement anciennes et les évolutions récentes minimes. Les méthodes actuelles d'évaluation des antidépresseurs apparaissent donc très standardisées, et insuffisamment objectives. Leur amélioration pourrait émerger de la découverte de validateurs externes de la dépression d'une part, et d'antidépresseurs de nouveaux mécanismes d'action d'autre part