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Cosci F, Chouinard VA, Chouinard G. Selective Serotonin Reuptake Inhibitor and Serotonin-Noradrenaline Reuptake Inhibitor Withdrawal Changes DSM Presentation of Mental Disorders: Results from the Diagnostic Clinical Interview for Drug Withdrawal. PSYCHOTHERAPY AND PSYCHOSOMATICS 2024:1-6. [PMID: 39043160 DOI: 10.1159/000540031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 06/25/2024] [Indexed: 07/25/2024]
Abstract
INTRODUCTION Selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs) may cause withdrawal at dose decrease, discontinuation, or switch. Current diagnostic methods (e.g., DSM) do not take such phenomenon into account. Using a new nosographic classification of withdrawal syndromes due to SSRI/SNRI decrease or discontinuation [by Psychother Psychosom. 2015;84(2):63-71], we explored whether DSM is adequate to identify DSM disorders when withdrawal occurs. METHODS Seventy-five self-referred patients with a diagnosis of withdrawal syndrome due to discontinuation of SSRI/SNRI, diagnosed via the Diagnostic Clinical Interview for Drug Withdrawal 1 - New Symptoms of Selective Serotonin Reuptake Inhibitors or Serotonin-Norepinephrine Reuptake Inhibitors (DID-W1), and at least one DSM-5 diagnosis were analyzed. RESULTS In 58 cases (77.3%), the DSM-5 diagnosis of current mental disorder was not confirmed when the DID-W1 diagnosis of current withdrawal syndrome was established. In 13 cases (17.3%), the DSM-5 diagnosis of past mental disorder was not confirmed when criteria for DID-W1 diagnosis of lifetime withdrawal syndrome were met. In 3 patients (4%), the DSM-5 diagnoses of current and past mental disorders were not confirmed when the DID-W1 diagnoses of current and lifetime withdrawal syndromes were taken into account. The DSM-5 diagnoses most frequently mis-formulated were current panic disorder (50.7%, n = 38) and past major depressive episode (18.7%, n = 14). CONCLUSION DSM needs to be complemented by clinimetric tools, such as the DID-W1, to detect withdrawal syndromes induced by SSRI/SNRI discontinuation, decrease, or switch, following long-term use.
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Affiliation(s)
- Fiammetta Cosci
- Department of Health Sciences, University of Florence, Florence, Italy
- International Lab of Clinical Measurements, University of Florence, Florence, Italy
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
| | - Virginie-Anne Chouinard
- Psychotic Disorders Division, McLean Hospital, Harvard Medical School, Belmont, Massachusetts, USA
| | - Guy Chouinard
- University Mental Health Institute of Montreal, University of Montreal, Montreal, Québec, Canada
- Clinical Pharmacology and Toxicology Program, Royal College of Physicians and Surgeons, McGill University, Montreal, Québec, Canada
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Hyam LE, Phillips M, Gracie L, Allen K, Schmidt U. Clinical staging across eating disorders: a scoping review protocol. BMJ Open 2023; 13:e077377. [PMID: 37993158 PMCID: PMC10668169 DOI: 10.1136/bmjopen-2023-077377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 11/09/2023] [Indexed: 11/24/2023] Open
Abstract
INTRODUCTION Clinical staging models in psychiatry assert that there are earlier, less severe or more malleable forms of illness that are distinguishable from later, more chronic forms of illness, and that these stages may have different prognostic and treatment implications. Previous reviews on clinical staging in eating disorders (EDs) suggest a staging heuristic could be useful for anorexia nervosa, but less research is available on how this applies to other EDs. An up-to-date review is required to synthesise new and heterogenous avenues of research. This scoping review aims to explore the extent and types of evidence in relation to illness staging for EDs and how these concepts are associated with treatment response and outcomes. METHODS AND ANALYSIS This protocol was developed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol extension for Scoping Reviews checklist and the Joanna Briggs Institute Reviewer's Manual. We will consider any documents providing evidence for clinical staging such as those which describe full or partial staging models, for all EDs, across various domains of assessment and functioning. Participants will include clinical or non-clinical population samples with full-syndrome EDs or disordered eating behaviour. PubMed, PsycINFO, MEDLINE and Web of Science databases will be systematically searched for relevant literature. Two authors will export documents and screen titles, abstracts and full texts. Data will be extracted into a charting form drafted by the authors. A narrative summary of the documents will be conducted in line with the study aims. Finally, clinical and research recommendations will be outlined. ETHICS AND DISSEMINATION Ethical approval will not be required to synthesise published and unpublished literature. The study will be published in a peer-reviewed journal and shared at conferences, via social media, and in other communications.
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Affiliation(s)
- Lucy Elizabeth Hyam
- Centre for Research in Eating and Weight Disorders, Department of Psychological Medicine, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
| | - Matthew Phillips
- Centre for Research in Eating and Weight Disorders, Department of Psychological Medicine, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
| | - Lara Gracie
- Department of Population Health, London School of Hygiene & Tropical Medicine, London, UK
- College of Medical and Dental Sciences, University of Birmingham, Birmingham Medical School, Birmingham, UK
| | - Karina Allen
- Centre for Research in Eating and Weight Disorders, Department of Psychological Medicine, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
- Eating Disorder Outpatients Service, South London and Maudsley NHS Foundation Trust, London, UK
| | - Ulrike Schmidt
- Centre for Research in Eating and Weight Disorders, Department of Psychological Medicine, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
- Eating Disorder Outpatients Service, South London and Maudsley NHS Foundation Trust, London, UK
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Hartman CA, Chen Q, Solberg BS, Du Rietz E, Klungsøyr K, Cortese S, Dalsgaard S, Haavik J, Ribasés M, Mostert JC, Libutzki B, Kittel-Schneider S, Cormand B, Vos M, Larsson H, Reif A, Faraone SV, Bellato A. Anxiety, mood, and substance use disorders in adult men and women with and without Attention-Deficit/Hyperactivity Disorder: a substantive and methodological overview. Neurosci Biobehav Rev 2023; 151:105209. [PMID: 37149075 DOI: 10.1016/j.neubiorev.2023.105209] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 04/16/2023] [Accepted: 05/01/2023] [Indexed: 05/08/2023]
Abstract
Knowledge on psychiatric comorbidity in adult ADHD is essential for prevention, detection, and treatment of these conditions. This review (1) focuses on large studies (n> 10,000; surveys, claims data, population registries) to identify (a) overall, (b) sex- and (c) age-specific patterns of comorbidity of anxiety disorders (ADs), major depressive disorder (MDD), bipolar disorder (BD) and substance use disorders (SUDs) in adults with ADHD relative to adults without ADHD; and (2) describes methodological challenges relating to establishing comorbidity in ADHD in adults as well as priorities for future research. Meta-analyses (ADHD: n=550,748; no ADHD n=14,546,814) yielded pooled odds ratios of 5.0(CI:3.29-7.46) for AD, 4.5(CI:2.44-8.34) for MDD, 8.7(CI:5.47-13.89) for BD and 4.6(CI:2.72-7.80) for SUDs, indicating strong differences in adults with compared to adults without ADHD. Moderation by sex was not found: high comorbidity held for both men and women with sex-specific patterns as in the general population: higher prevalences of ADs, MDD and BD in women and a higher prevalence of SUDs in men. Insufficient data on different phases of the adult lifespan prevented conclusions on developmental changes in comorbidity. We discuss methodological challenges, knowledge gaps, and future research priorities.
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Affiliation(s)
- Catharina A Hartman
- University Medical Center Groningen, Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University of Groningen, the Netherlands.
| | - Qi Chen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Berit Skretting Solberg
- Child- and adolescent psychiatric outpatient unit, Hospital Betanien, Bergen, Norway; Department of Biomedicine, University of Bergen, Norway
| | - Ebba Du Rietz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kari Klungsøyr
- Department of Global Public Health and Primary Care, University of Bergen, Norway; Department of Health Promotion, Norwegian Institute of Public Health, Bergen, Norway
| | - Samuele Cortese
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK; Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK; Solent NHS Trust, Southampton, UK; Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York City, New York, USA; Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK
| | - Søren Dalsgaard
- NCRR - National Centre for Register-based Research, Aarhus University, Aarhus, Denmark; iPSYCH - The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen and Aarhus, Denmark; CIRRAU - Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Norway; Bergen Center of Brain Plasticity, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Marta Ribasés
- Department of Psychiatry, Mental Health and Addictions, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain; Department of Genetics, Microbiology & Statistics, University of Barcelona, Barcelona, Spain
| | - Jeanette C Mostert
- Department of Psychiatry, Donders Institute for Brain, Behaviour and Cognition, Radboud University Medical Center Nijmegen, the Netherlands; Department of Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Berit Libutzki
- University Medical Center Groningen, Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University of Groningen, the Netherlands
| | - Sarah Kittel-Schneider
- Department of Psychiatry, Psychotherapy and Psychosomatic, University Hospital Würzburg, Würzburg, Germany
| | - Bru Cormand
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Rare Diseases (CIBERER), Instituto de Salud Carlos III, Spain; Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain; Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Catalonia, Spain
| | - Melissa Vos
- University Medical Center Groningen, Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University of Groningen, the Netherlands
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt - Goethe University, Frankfurt am Main, Germany
| | - Stephen V Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Alessio Bellato
- School of Psychology, University of Nottingham, Semenyih, Malaysia
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Research and Diagnostic Algorithmic Rules (RADAR) for mood disorders, recurrence of illness, suicidal behaviours, and the patient's lifetime trajectory. Acta Neuropsychiatr 2023; 35:104-117. [PMID: 36380512 DOI: 10.1017/neu.2022.31] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The top-down Diagnostic and Statistical Manual/International Statistical Classification of Diseases categories of mood disorders are inaccurate, and their dogmatic nature precludes both deductive (as indisputable) and inductive (as top-down) remodelling of case definitions. In trials, psychiatric rating scale scores employed as outcome variables are invalid and rely on folk psychology-like narratives. Using machine learning techniques, we developed a new precision nomothetic model of mood disorders with a recurrence of illness (ROI) index, a new endophenotype class, namely Major Dysmood Disorder (MDMD), characterised by increased ROI, a more severe phenome, and more disabilities. Nonetheless, our previous studies did not compute Research and Diagnostic Algorithmic Rules (RADAR) to diagnose MDMD and score ROI, lifetime (LT), and current suicidal behaviours, as well as the phenome of mood disorders. Here, we provide rules to compute bottom-up RADAR scores for MDMD, ROI, LT and current suicidal ideation and attempts, the phenome of mood disorders, and the lifetime trajectory of mood disorder patients from a family history of mood disorders and substance abuse to adverse childhood experiences, ROI, and the phenome. We also demonstrate how to plot the 12 major scores in a single RADAR graph, which displays all features in a two-dimensional plot. These graphs allow the characteristics of a patient to be displayed as an idiomatic fingerprint, allowing one to estimate the key traits and severity of the illness at a glance. Consequently, biomarker research into mood disorders should use our RADAR scores to examine pan-omics data, which should be used to enlarge our precision models and RADAR graph.
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