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Brouwer A, Carhart‐Harris RL, Raison CL. Psychotomimetic compensation versus sensitization. Pharmacol Res Perspect 2024; 12:e1217. [PMID: 38923845 PMCID: PMC11194300 DOI: 10.1002/prp2.1217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 05/08/2024] [Indexed: 06/28/2024] Open
Abstract
It is a paradox that psychotomimetic drugs can relieve symptoms that increase risk of and cooccur with psychosis, such as attention and motivational deficits (e.g., amphetamines), pain (e.g., cannabis) and symptoms of depression (e.g., psychedelics, dissociatives). We introduce the ideas of psychotomimetic compensation and psychotomimetic sensitization to explain this paradox. Psychotomimetic compensation refers to a short-term stressor or drug-induced compensation against stress that is facilitated by engagement of neurotransmitter/modulator systems (endocannabinoid, serotonergic, glutamatergic and dopaminergic) that mediate the effects of common psychotomimetic drugs. Psychotomimetic sensitization occurs after repeated exposure to stress and/or drugs and is evidenced by the gradual intensification and increase of psychotic-like experiences over time. Theoretical and practical implications of this model are discussed.
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Affiliation(s)
- Ari Brouwer
- Department of Human Development and Family Studies, School of Human EcologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Robin L. Carhart‐Harris
- Department of Neurology and PsychiatryUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Charles L. Raison
- Department of Psychiatry, School of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Vail Health Behavioral Health Innovation CenterVailColoradoUSA
- Center for the Study of Human HealthEmory UniversityAtlantaGeorgiaUSA
- Department of Spiritual HealthEmory University Woodruff Health Sciences CenterAtlantaGeorgiaUSA
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Lee TY, Lee H, Lee J, Lee Y, Rhee SJ, Park DY, Paek MJ, Kim EY, Kim E, Roh S, Jung HY, Kim M, Kim SH, Ahn YM, Ha K, Kwon JS. The characteristics and clinical outcomes of a pluripotent high-risk group with the potential to develop a diverse range of psychiatric disorders. J Psychiatr Res 2024; 174:237-244. [PMID: 38653032 DOI: 10.1016/j.jpsychires.2024.04.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 03/26/2024] [Accepted: 04/03/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND Recent studies have indicated that clinical high risk for psychosis (CHR-P) is highly specific for psychotic disorders other than pluripotential to various serious mental illnesses. However, not all CHR-P develop psychotic disorder only, and psychosis can occur in non-psychotic disorders as well. Our prospective cohort study aims to investigate the characteristics and clinical outcomes of a pluripotent high-risk group with the potential to develop a diverse range of psychiatric disorders. METHODS The SPRIM study is a prospective naturalistic cohort program that focuses on the early detection of those at risk of developing serious mental illness, including psychosis (CHR-P), bipolar (CHR-B), and depressive disorder (CHR-D), as well as undifferentiated risk participants (UCHR). Our study has a longitudinal design with a baseline assessment and eight follow-up evaluations at 6, 12, 18, 24, 30, 36, 42, and 48 months to determine whether participants have transitioned to psychosis or mood disorders. RESULTS The SPRIM sample consisted of 90 CHR participants. The total cumulative incidence rate of transition was 53.3% (95% CI 32.5-77.2). CHR-P, CHR-B, CHR-D, and UCHR had cumulative incidence rates of 13.7% (95% CI 3.4-46.4), 52.4% (95% CI 28.1-81.1), 66.7% (95% CI 24.6-98.6) and 54.3% (95% CI 20.5-93.1), respectively. The cumulative incidence of psychosis, bipolar, and depressive disorder among all participants was 3.3% (95% CI 0.8-11.5), 45.7% (95% CI 24.4-73.6), and 11.2% (95% CI 3.1-36.2), respectively. CONCLUSIONS Our study suggests that the concept of pluripotent high-risk for a diverse range of psychiatric disorders is an integrative approach to examining transdiagnostic interactions between illnesses with a high transition rate and minimizing stigma.
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Affiliation(s)
- Tae Young Lee
- Department of Psychiatry, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Hyunju Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Junhee Lee
- Department of Psychiatry, Seoul St. Mary's Hospital, Seoul, Republic of Korea
| | - Yunna Lee
- Department of Neuropsychiatry, Kosin University Gospel Hospital, Pusan, Republic of Korea
| | - Sang Jin Rhee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Dong Yeon Park
- Department of Psychiatry, National Center for Mental Health, Seoul, Republic of Korea
| | - Myung Jae Paek
- Department of Psychiatry, Kyung Hee University Hospital, Seoul, Republic of Korea
| | - Eun Young Kim
- Seoul National University Health Service Center, Seoul National University, Seoul, Republic of Korea
| | - Euitae Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Sungwon Roh
- Department of Neuropsychiatry, Hanyang University Hospital, Seoul, Republic of Korea
| | - Hee Yeon Jung
- Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Se Hyun Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Yong Min Ahn
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea; Department of Psychiatry and Behavioral Science, Seoul National University College of Medicine, Seoul, Republic of Korea; Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
| | - Kyooseob Ha
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada; Department of Psychiatry, Lions Gate Hospital - Vancouver Coastal Health, British Columbia, Canada.
| | - Jun Soo Kwon
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea; Department of Psychiatry and Behavioral Science, Seoul National University College of Medicine, Seoul, Republic of Korea; Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
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Choi WJ, Woo YS, Choi WS, Lee J, Bahk WM. Defining "High Recurrence" of Depressive Episodes for Predicting Diagnostic Conversion from Major Depressive Disorder to Bipolar Disorder: A 5-year Retrospective Study. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE : THE OFFICIAL SCIENTIFIC JOURNAL OF THE KOREAN COLLEGE OF NEUROPSYCHOPHARMACOLOGY 2024; 22:364-369. [PMID: 38627083 PMCID: PMC11024704 DOI: 10.9758/cpn.24.1183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 03/11/2024] [Accepted: 03/12/2024] [Indexed: 04/21/2024]
Abstract
Objective This study determined the threshold for recurrent depressive episodes that predicted conversion from major depressive disorder (MDD) to bipolar disorder (BD). Methods We retrospectively reviewed the medical records of 296 patients diagnosed with MDD for a minimum of 5 years in two university hospitals. We examined their the Diagnostic and Statistical Manual of Mental Disorders, 5th edition diagnoses and detailed clinical information at the initial admission and yearly assessments after discharge to establish the threshold for recurrent depressive episodes indicating a risk of diagnostic conversion from MDD to BD. Optimal cut-offs were derived using receiver operating characteristic (ROC) curves. Results ROC curve analysis revealed that more than four recurrent depressive episodes was indicative of potential diagnostic conversion from MDD to BD (area under the curve, 0.604; sensitivity, 0.353; specificity, 0.855; positive predictive value, 0.421; negative predictive value, 0.816). Conclusion These findings suggest that the best predictor of conversion from MDD to BD is more than four recurrent depressive episodes. Our findings have the potential to enhance diagnostic accuracy and treatment efficiency. To validate our results, longitudinal prospective studies are necessary.
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Affiliation(s)
| | - Young Sup Woo
- Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Won-Seok Choi
- Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jonghun Lee
- Department of Psychiatry, College of Medicine, Daegu Catholic University, Daegu, Korea
| | - Won-Myong Bahk
- Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seoul, Korea
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Ebrahimi OV, Borsboom D, Hoekstra RHA, Epskamp S, Ostinelli EG, Bastiaansen JA, Cipriani A. Towards precision in the diagnostic profiling of patients: leveraging symptom dynamics as a clinical characterisation dimension in the assessment of major depressive disorder. Br J Psychiatry 2024; 224:157-163. [PMID: 38584324 PMCID: PMC11039556 DOI: 10.1192/bjp.2024.19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 12/14/2023] [Accepted: 01/16/2024] [Indexed: 04/09/2024]
Abstract
BACKGROUND International guidelines present overall symptom severity as the key dimension for clinical characterisation of major depressive disorder (MDD). However, differences may reside within severity levels related to how symptoms interact in an individual patient, called symptom dynamics. AIMS To investigate these individual differences by estimating the proportion of patients that display differences in their symptom dynamics while sharing the same overall symptom severity. METHOD Participants with MDD (n = 73; mean age 34.6 years, s.d. = 13.1; 56.2% female) rated their baseline symptom severity using the Inventory for Depressive Symptomatology Self-Report (IDS-SR). Momentary indicators for depressive symptoms were then collected through ecological momentary assessments five times per day for 28 days; 8395 observations were conducted (average per person: 115; s.d. = 16.8). Each participant's symptom dynamics were estimated using person-specific dynamic network models. Individual differences in these symptom relationship patterns in groups of participants sharing the same symptom severity levels were estimated using individual network invariance tests. Subsequently, the overall proportion of participants that displayed differential symptom dynamics while sharing the same symptom severity was calculated. A supplementary simulation study was conducted to investigate the accuracy of our methodology against false-positive results. RESULTS Differential symptom dynamics were identified across 63.0% (95% bootstrapped CI 41.0-82.1) of participants within the same severity group. The average false detection of individual differences was 2.2%. CONCLUSIONS The majority of participants within the same depressive symptom severity group displayed differential symptom dynamics. Examining symptom dynamics provides information about person-specific psychopathological expression beyond severity levels by revealing how symptoms aggravate each other over time. These results suggest that symptom dynamics may be a promising new dimension for clinical characterisation, warranting replication in independent samples. To inform personalised treatment planning, a next step concerns linking different symptom relationship patterns to treatment response and clinical course, including patterns related to spontaneous recovery and forms of disorder progression.
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Affiliation(s)
- Omid V. Ebrahimi
- Department of Experimental Psychology, University of Oxford, Oxford, UK; and Department of Psychology , University of Oslo, Oslo, Norway
| | - Denny Borsboom
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - Ria H. A. Hoekstra
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - Sacha Epskamp
- Department of Psychology, National University of Singapore, Singapore, Singapore
| | - Edoardo G. Ostinelli
- Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Precision Psychiatry Laboratory, NIHR Oxford Health Biomedical Research Centre, Oxford, UK; and Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
| | - Jojanneke A. Bastiaansen
- Interdisciplinary Center Psychopathology and Emotion Regulation, Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; and Friesland Mental Health Care Services, Leeuwarden, The Netherlands
| | - Andrea Cipriani
- Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Precision Psychiatry Laboratory, NIHR Oxford Health Biomedical Research Centre, Oxford, UK; and Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
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Rhee SJ, Ohlsson H, Sundquist J, Sundquist K, Kendler KS. Predictors of diagnostic conversion from major depression to bipolar disorder: a Swedish national longitudinal study. Psychol Med 2023; 53:7805-7816. [PMID: 37427550 PMCID: PMC10755232 DOI: 10.1017/s0033291723001848] [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: 04/07/2023] [Revised: 05/31/2023] [Accepted: 06/13/2023] [Indexed: 07/11/2023]
Abstract
BACKGROUND It is clinically important to predict the conversion of major depression (MD) to bipolar disorder (BD). Therefore, we sought to identify related conversion rates and risk factors. METHODS This cohort study included the Swedish population born from 1941 onward. Data were collected from Swedish population-based registers. Potential risk factors, including family genetic risk scores (FGRS), which were calculated based on the phenotypes of relatives in the extended family and not molecular data, and demographic/clinical characteristics from these registers were retrieved. Those with first MD registrations from 2006 were followed up until 2018. The conversion rate to BD and related risk factors were analyzed using Cox proportional hazards models. Additional analyses were performed for late converters and with stratification by sex. RESULTS The cumulative incidence of conversion was 5.84% [95% confidence interval (95% CI) 5.72-5.96] for 13 years. In the multivariable analysis, the strongest risk factors for conversion were high FGRS of BD [hazard ratio (HR) = 2.73, 95% CI 2.43-3.08], inpatient treatment settings (HR = 2.64, 95% CI 2.44-2.84), and psychotic depression (HR = 2.58, 95% CI 2.14-3.11). For late converters, the first registration of MD during the teenage years was a stronger risk factor when compared with the baseline model. When the interactions between risk factors and sex were significant, stratification by sex revealed that they were more predictive in females. CONCLUSIONS Family history of BD, inpatient treatment, and psychotic symptoms were the strongest predictors of conversion from MD to BD.
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Affiliation(s)
- Sang Jin Rhee
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea
| | - Henrik Ohlsson
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
| | - Jan Sundquist
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
- Department of Family Medicine and Community Health and Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kristina Sundquist
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
- Department of Family Medicine and Community Health and Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kenneth S. Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
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Service SK, De La Hoz J, Diaz-Zuluaga AM, Arias A, Pimplaskar A, Luu C, Mena L, Valencia J, Ramírez MC, Bearden CE, Sabbati C, Reus VI, López-Jaramillo C, Freimer NB, Loohuis LMO. Predicting diagnostic conversion from major depressive disorder to bipolar disorder: an EHR based study from Colombia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.28.23296092. [PMID: 37873340 PMCID: PMC10593019 DOI: 10.1101/2023.09.28.23296092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Bipolar Disorder (BD) is a severe and chronic disorder characterized by recurrent episodes of depression, mania, and/or hypomania. Most BD patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study leverages electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia to identify features predictive of the transition from Major Depressive Disorder (MDD) to BD. Analyzing EHR data from 13,607 patients diagnosed with MDD over 15 years, we identified 1,610 cases of conversion to BD. Using a multivariate Cox regression model, we identified severity of the initial MDD episode, the presence of psychosis and hospitalization at first episode, family history of mood or psychotic disorders, female gender to be predictive of the conversion to BD. Additionally, we observed associations with medication classes (prescriptions of mood stabilizers, antipsychotics, and antidepressants) and clinical features (delusions, suicide attempt, suicidal ideation, use of marijuana and alcohol use/abuse) derived from natural language processing (NLP) of clinical notes. Together, these risk factors predicted BD conversion within five years of the initial MDD diagnosis, with a recall of 72% and a precision of 38%. Our study confirms many previously identified risk factors identified through registry-based studies (such as female gender and psychotic depression at the index MDD episode), and identifies novel ones (specifically, suicidal ideation and suicide attempt extracted from clinical notes). These results simultaneously demonstrate the validity of using EHR data for predicting BD conversion as well as underscore its potential for the identification of novel risk factors and improving early diagnosis.
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Affiliation(s)
- Susan K Service
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Juan De La Hoz
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Ana M Diaz-Zuluaga
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Alejandro Arias
- Research Group in Psychiatry (GIPSI), Institute of Medical Research, Department of Psychiatry, Faculty of Medicine, University of Antioquia, Medellín, Colombia
| | - Aditya Pimplaskar
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Chuc Luu
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Laura Mena
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Johanna Valencia
- Research Group in Psychiatry (GIPSI), Institute of Medical Research, Department of Psychiatry, Faculty of Medicine, University of Antioquia, Medellín, Colombia
| | | | - Carrie E Bearden
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Chiara Sabbati
- Department of Biomedical Data Science, Stanford University, Stanford, USA
| | - Victor I Reus
- Department of Psychiatry, University of California San Francisco, San Francisco, USA
| | - Carlos López-Jaramillo
- Research Group in Psychiatry (GIPSI), Institute of Medical Research, Department of Psychiatry, Faculty of Medicine, University of Antioquia, Medellín, Colombia
| | - Nelson B Freimer
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Loes M Olde Loohuis
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
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Mundy J, Hübel C, Adey BN, Davies HL, Davies MR, Coleman JRI, Hotopf M, Kalsi G, Lee SH, McIntosh AM, Rogers HC, Eley TC, Murray RM, Vassos E, Breen G. Genetic examination of the Mood Disorder Questionnaire and its relationship with bipolar disorder. Am J Med Genet B Neuropsychiatr Genet 2023; 192:147-160. [PMID: 37178379 PMCID: PMC10952822 DOI: 10.1002/ajmg.b.32938] [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: 11/22/2022] [Revised: 02/18/2023] [Accepted: 04/15/2023] [Indexed: 05/15/2023]
Abstract
The Mood Disorder Questionnaire (MDQ) is a common screening tool for bipolar disorder that assesses manic symptoms. Its utility for genetic studies of mania or bipolar traits has not been fully examined. We psychometrically compared the MDQ to self-reported bipolar disorder in participants from the United Kingdom National Institute of Health and Care Research Mental Health BioResource. We conducted genome-wide association studies of manic symptom quantitative traits and symptom subgroups, derived from the MDQ items (N = 11,568-19,859). We calculated genetic correlations with bipolar disorder and other psychiatric and behavioral traits. The MDQ screener showed low positive predictive value (0.29) for self-reported bipolar disorder. Neither concurrent nor lifetime manic symptoms were genetically correlated with bipolar disorder. Lifetime manic symptoms had a highest genetic correlation (rg = 1.0) with posttraumatic stress disorder although this was not confirmed by within-cohort phenotypic correlations (rp = 0.41). Other significant genetic correlations included attention deficit hyperactivity disorder (rg = 0.69), insomnia (rg = 0.55), and major depressive disorder (rg = 0.42). Our study adds to existing literature questioning the MDQ's validity and suggests it may capture symptoms of general distress or psychopathology, rather than hypomania/mania specifically, in at-risk populations.
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Affiliation(s)
- Jessica Mundy
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
| | - Christopher Hübel
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
- National Centre for Register‐based Research, Aarhus Business and Social SciencesAarhus UniversityAarhusDenmark
| | - Brett N. Adey
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
| | - Helena L. Davies
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
| | - Molly R. Davies
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
| | - Jonathan R. I. Coleman
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
| | - Matthew Hotopf
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
- South London and Maudsley NHS Foundation TrustBethlem Royal HospitalKentUK
| | - Gursharan Kalsi
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
| | - Sang Hyuck Lee
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
| | - Andrew M. McIntosh
- Division of Psychiatry, Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
| | - Henry C. Rogers
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
| | - Thalia C. Eley
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
| | - Robin M. Murray
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Evangelos Vassos
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
| | - Gerome Breen
- Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research CentreSouth London and Maudsley HospitalLondonUK
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Liu F, Gao M, Wu Q, Yan M, Wu R, Shao P, Huang J. Diagnostic Stability in Psychiatric Patients From Hospital Admission to Discharge: A 10-Year Retrospective Study. Psychiatry Investig 2023; 20:461-470. [PMID: 37253472 DOI: 10.30773/pi.2022.0349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 03/08/2023] [Indexed: 06/01/2023] Open
Abstract
OBJECTIVE This study aimed to evaluate the consistency or stability of mental disorders diagnosed in the psychiatry ward setting, investigate factors associated with consistency, and observe the disease distribution over the decade. METHODS A total of 20,359 psychiatric inpatients were included in this retrospective study from June 2011 to December 2020. Diagnoses from the first admission to discharge were evaluated to determine the diagnostic consistency during hospitalization. Readmissions were selected as the subgroup, whose first and last discharge diagnoses were compared to analyze the relatively long-term diagnostic stability. Demographic and clinical characteristics were collected to identify predictors of diagnostic discrepancy. RESULTS From 2011-2020, the hospitalization rate decreased from 42.7% to 20.7% for schizophrenia and grew from 13.3% to 23.8% for depression. Diagnoses were retained by 92.6% of patients at their first discharge diagnosis, ranging from 100% for disorders of psychological development to 16.3% for unspecified mental disorders. About 33.9% of diagnostic conversions were to bipolar disorder in patients having inconsistent diagnoses. However, among rehospitalizations, the diagnostic stability notably dropped to 71.3%. For rehospitalizations, mood disorders and schizophrenia spectrum disorders were relatively stable diagnoses categories, with 72.6% to 76.7% of patients receiving the same diagnosis, although results of specified diagnoses within these categories ranged from 5.9% to 91.0%. Except for mood disorders and schizophrenia spectrum disorders, the diagnoses of all other categories were below 70%. Long lengths of hospitalization and old age were associated with short-term diagnosis alterations. CONCLUSION Longitudinal follow-up and integration of multiple aspects of information are essential for accurate diagnosis.
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Affiliation(s)
- Furu Liu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Hunan, China
| | - Menghui Gao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Hunan, China
| | - Qiongqiong Wu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Hunan, China
| | - Meiqi Yan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Hunan, China
| | - Renrong Wu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Hunan, China
| | - Ping Shao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Hunan, China
| | - Jing Huang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Hunan, China
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Nielssen O, Staples L, Karin E, Kayrouz R, Dear B, Titov N. Effectiveness of internet delivered cognitive behaviour therapy provided as routine care for people in the depressed phase of bipolar disorder treated with Lithium. PLOS DIGITAL HEALTH 2023; 2:e0000194. [PMID: 36812646 PMCID: PMC9946241 DOI: 10.1371/journal.pdig.0000194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 01/13/2023] [Indexed: 02/24/2023]
Abstract
There is little research reporting the outcome of internet delivered cognitive behaviour therapy, (iCBT), which helps patients identify and modify unhelpful cognitions and behaviours, for the depressed phase of bipolar disorder as part of routine care. Demographic information, baseline scores and treatment outcomes were examined for patients of MindSpot Clinic, a national iCBT service who reported taking Lithium and their clinic records confirmed the diagnosis of bipolar disorder. Outcomes were completion rates, patient satisfaction and changes in measures of psychological distress, depression and anxiety measured by the Kessler-10 item (K-10), Patient Health Questionnaire 9 Item (PHQ-9), and Generalized Anxiety Disorder Scale 7 Item (GAD-7), compared to clinic benchmarks. Out of 21,745 people who completed a MindSpot assessment and enrolled in a MindSpot treatment course in a 7 year period, 83 reported taking Lithium and had a confirmed a diagnosis of bipolar disorder. Outcomes of reductions in symptoms were large on all measures (effect sizes > 1.0 on all measures, percentage change between 32.4% and 40%), and lesson completion and satisfaction with the course were also high. MindSpot treatments appear to be effective in treating anxiety and depression in people diagnosed with bipolar, and suggest that iCBT has the potential to overcome the under-use of evidence based psychological treatments of people with bipolar depression.
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Affiliation(s)
- Olav Nielssen
- Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia
- MindSpot Clinic, Macquarie Health, Macquarie University, Sydney, Australia
- * E-mail:
| | - Lauren Staples
- MindSpot Clinic, Macquarie Health, Macquarie University, Sydney, Australia
| | - Eyal Karin
- eCentreClinic, Macquarie University, Sydney, Australia
| | - Rony Kayrouz
- MindSpot Clinic, Macquarie Health, Macquarie University, Sydney, Australia
| | - Blake Dear
- MindSpot Clinic, Macquarie Health, Macquarie University, Sydney, Australia
- eCentreClinic, Macquarie University, Sydney, Australia
| | - Nickolai Titov
- MindSpot Clinic, Macquarie Health, Macquarie University, Sydney, Australia
- eCentreClinic, Macquarie University, Sydney, Australia
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10
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Paljärvi T, Tiihonen J, Lähteenvuo M, Tanskanen A, Fazel S, Taipale H. Mortality in psychotic depression: 18-year follow-up study. Br J Psychiatry 2023; 222:37-43. [PMID: 36250518 PMCID: PMC10895511 DOI: 10.1192/bjp.2022.140] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 07/25/2022] [Accepted: 08/30/2022] [Indexed: 11/23/2022]
Abstract
BACKGROUND Evidence on the role of co-occurring psychiatric disorders in mortality associated with psychotic depression is limited. AIMS To estimate the risk of cause-specific mortality in psychotic depression compared with severe non-psychotic depression while controlling for comorbid psychiatric disorders. METHOD This cohort study used routine data from nationwide health registers in Finland. Eligible participants had their first diagnosis for psychotic depression or for severe non-psychotic depression between the years 2000 and 2018, had no pre-existing diagnoses for schizophrenia spectrum disorders or bipolar disorder, and were aged 18-65 years at the index diagnosis. Causes of death were defined by ICD-10 codes. The follow-up time was up to 18 years. RESULTS We included 19 064 individuals with incident psychotic depression and 90 877 individuals with incident non-psychotic depression. Half (1199/2188) of the deaths in those with psychotic depression occurred within 5 years from the index diagnosis and the highest relative risk was during the first year after the diagnosis. Compared with individuals with non-psychotic depression, those with psychotic depression had a higher risk of all-cause mortality (adjusted hazard ratio, aHR = 1.59, 95% CI 1.48-1.70), suicides (aHR = 2.36, 95% CI 2.11-2.64) and fatal accidents (aHR 1.63, 95% CI 1.26-2.10) during the subsequent 5-year period after the index diagnosis. CONCLUSIONS Psychotic symptoms markedly added to the mortality risk associated with severe depression after controlling for psychiatric comorbidity. Prompt treatment and enhanced monitoring for psychotic symptoms is warranted in all patients with severe depression to prevent deaths because of suicides and other external causes.
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Affiliation(s)
- Tapio Paljärvi
- Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Finland; and Department of Psychiatry, Oxford University, Warneford Hospital, UK
| | - Jari Tiihonen
- Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Finland; and Department of Clinical Neuroscience, Karolinska Institutet, Sweden
| | - Markku Lähteenvuo
- Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Finland
| | - Antti Tanskanen
- Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Finland; and Department of Clinical Neuroscience, Karolinska Institutet, Sweden
| | - Seena Fazel
- Department of Psychiatry, Oxford University, Warneford Hospital, UK; and Oxford Health NHS Foundation Trust, Warneford Hospital, UK
| | - Heidi Taipale
- Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Finland; Department of Clinical Neuroscience, Karolinska Institutet, Sweden; and School of Pharmacy, University of Eastern Finland, Finland
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11
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Törmälehto S, Svirskis T, Partonen T, Isometsä E, Pirkola S, Virtanen M, Sund R. Seasonal Effects on Hospitalizations Due to Mood and Psychotic Disorders: A Nationwide 31-Year Register Study. Clin Epidemiol 2022; 14:1177-1191. [PMID: 36304786 PMCID: PMC9595069 DOI: 10.2147/clep.s372341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 09/30/2022] [Indexed: 11/24/2022] Open
Abstract
Purpose To examine seasonal patterns of hospital admissions due to mood and psychotic disorders and to investigate whether the admission rates show variation according to the seasonal daylength (photoperiods). Patients and Methods A retrospective nationwide register-based cohort of all psychiatric admissions (N=978,079) during 1987–2017 in Finland was utilized. The smoothed time-series of adjusted ratio of observed and expected (O/E) daily counts were estimated to examine seasonal variation. The mean O/E with 95% confidence intervals (CI) was used to study the admission rates by photoperiods. The calendar days were classified into the 71-day photoperiods based on the daylength (long/summer, short/winter, equal/spring, equal/fall) and the pace of change in daylength (slowly/rapidly increasing/decreasing daylength). Results Manic episodes peaked in summer during the long (mean O/E=1.10, 95% CI=1.06–1.13) and slowly decreasing (1.09, 1.06–1.13) photoperiods and had a nadir in winter during the slowly increasing (0.93, 0.89–0.98) photoperiod. Admissions for unipolar depressive (UPD) episodes peaked in autumn and in spring at the end of the rapidly decreasing (1.03, 1.02–1.04) and increasing (1.03, 1.01–1.04) photoperiod, and dropped in summer during the long and slowly decreasing (0.95, 0.94–0.96) photoperiods. Bipolar depressive (BPD) and mixed episodes signaled excess admissions in autumn and in spring. Admissions for schizophrenia were higher than expected from summer to early-autumn, during the long and slowly decreasing photoperiods (1.02, 1.02–1.03), and lower than expected in other seasons, especially in mid-spring during the rapidly increasing photoperiod (0.98, 0.98–0.99). Conclusion The study indicates the seasonality and photoperiodicity of mental disorders, especially for manic episodes. The seasonal pattern is similar between schizophrenia and manic episodes, and between UPD, BPD, and mixed episodes.
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Affiliation(s)
- Soili Törmälehto
- School of Educational Sciences and Psychology, University of Eastern Finland, Joensuu, Finland,Correspondence: Soili Törmälehto, School of Educational Sciences and Psychology C/O Institute of Clinical Medicine, University of Eastern Finland, P.O. Box 1627, Kuopio, FI-70211, Finland, Email
| | - Tanja Svirskis
- Department of Psychiatry, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Timo Partonen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Erkki Isometsä
- Department of Psychiatry, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Sami Pirkola
- Faculty of Social Sciences, University of Tampere and Pirkanmaa Hospital District, Tampere, Finland
| | - Marianna Virtanen
- School of Educational Sciences and Psychology, University of Eastern Finland, Joensuu, Finland,Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Reijo Sund
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
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12
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Ahti J, Kieseppä T, Suvisaari J, Suokas K, Holm M, Wegelius A, Ahola-Olli A, Häkkinen K, Kampman O, Lähteenvuo M, Paunio T, Tiihonen J, Tuulio-Henriksson A, Isometsä E. Differences in psychosocial functioning between psychotic disorders in the Finnish SUPER study. Schizophr Res 2022; 244:10-17. [PMID: 35537381 DOI: 10.1016/j.schres.2022.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 03/16/2022] [Accepted: 04/30/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Psychotic disorders differ in their impact on psychosocial functioning. However, few studies have directly compared psychosocial functioning and its determinants between schizophrenia, schizoaffective disorder (SAD), bipolar disorder (BD), and major depressive disorder with psychotic features (psychotic MDD). OBJECTIVE We compared rates of independent living, employment, marriage, and having children between these diagnostic groups in a large national sample of participants with psychotic disorders in Finland. METHODS A cross-sectional substudy of participants (N = 9148) aged 18 to 65 years in the Finnish SUPER study, recruited nationwide from health- and social care settings and with advertisements. Psychosis diagnoses, age of onset, and hospitalizations were collected from healthcare registers. Participants were interviewed for psychosocial functioning. Associations of age of onset, hospitalizations, gender, and education with psychosocial functioning were analyzed using logistic regression models. RESULTS Of participants, 13.8% were employed or studying, 72.0% living independently and 32.5% had children. Overall, BD was associated with best, SAD and psychotic MDD with intermediate, and schizophrenia with worst level of psychosocial functioning. Greatest differences were found in independent living (OR 4.06 for BD vs. schizophrenia). In multivariate models, gender and number of hospitalizations predicted employment, marriage, and independent living in all diagnostic categories, and age of onset in some diagnostic categories. CONCLUSIONS Level of functioning and psychosocial outcomes differed markedly between psychotic disorders, particularly in independent living. Outcomes were worst for schizophrenia and best for BD. Across all psychotic disorders, female gender and lifetime number of hospitalizations had strong independent associations with marriage, employment, and independent living.
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Affiliation(s)
- Johan Ahti
- Department of Psychiatry, University of Helsinki and Helsinki University Hospital, Finland
| | - Tuula Kieseppä
- Department of Psychiatry, University of Helsinki and Helsinki University Hospital, Finland; Mental Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Jaana Suvisaari
- Mental Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Kimmo Suokas
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland; Tampere University Hospital, Tampere, Finland; Department of Psychiatry, Pirkanmaa Hospital District, Tampere, Finland
| | - Minna Holm
- Mental Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Asko Wegelius
- Department of Psychiatry, University of Helsinki and Helsinki University Hospital, Finland; Mental Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland; Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Ari Ahola-Olli
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland; Stanley Center for Psychiatric Research, The Broad Institute of MIT (Massachusetts Institute of Technology) and Harvard, Cambridge, MA, USA; Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Katja Häkkinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland; Department of Forensic Psychiatry, Niuvanniemi Hospital, University of Eastern Finland, Kuopio, Finland
| | - Olli Kampman
- Tampere University Hospital, Tampere, Finland; Department of Psychiatry, Pirkanmaa Hospital District, Tampere, Finland; Department of Psychiatry, Pirkanmaa Hospital District, Tampere, Finland
| | - Markku Lähteenvuo
- Department of Forensic Psychiatry, Niuvanniemi Hospital, University of Eastern Finland, Kuopio, Finland
| | - Tiina Paunio
- Department of Psychiatry, University of Helsinki and Helsinki University Hospital, Finland; Mental Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Jari Tiihonen
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Forensic Psychiatry, Niuvanniemi Hospital, University of Eastern Finland, Kuopio, Finland; Center for Psychiatry Research, Stockholm City Council, Stockholm, Sweden
| | | | - Erkki Isometsä
- Department of Psychiatry, University of Helsinki and Helsinki University Hospital, Finland.
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13
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Longitudinal Course of Illness in Congenitally Deaf Patient with Auditory Verbal Hallucination. Case Rep Psychiatry 2022; 2022:7426850. [PMID: 35190781 PMCID: PMC8858041 DOI: 10.1155/2022/7426850] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 02/04/2022] [Indexed: 11/18/2022] Open
Abstract
Auditory verbal hallucination is one of the core symptoms of schizophrenia, same as delusions, and also occurs in many other psychiatric disorders. Significant numbers of people with congenital deafness experience auditory verbal hallucinations; however, there are only a few reports regarding the course of psychosis in people with congenital deafness. Herein, we report the case of a patient with congenital deafness and auditory verbal hallucinations whose diagnosis was changed from psychotic major depression to schizophrenia 7 years after the onset of the disease. His psychotic symptoms decreased when his primary medication was changed from an antidepressant to antipsychotic drugs, based on the change of diagnosis. In the treatment of congenitally deaf patients with auditory verbal hallucinations, the inability to communicate through spoken language may interfere with proper diagnosis and treatment. The ability to collect detailed information in ways other than through verbal language is imperative for psychiatrists to determine the appropriate diagnosis and treatment for these patients during the longitudinal course of illness.
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14
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Lee DY, Kim C, Lee S, Son SJ, Cho SM, Cho YH, Lim J, Park RW. Psychosis Relapse Prediction Leveraging Electronic Health Records Data and Natural Language Processing Enrichment Methods. Front Psychiatry 2022; 13:844442. [PMID: 35479497 PMCID: PMC9037331 DOI: 10.3389/fpsyt.2022.844442] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 03/09/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Identifying patients at a high risk of psychosis relapse is crucial for early interventions. A relevant psychiatric clinical context is often recorded in clinical notes; however, the utilization of unstructured data remains limited. This study aimed to develop psychosis-relapse prediction models using various types of clinical notes and structured data. METHODS Clinical data were extracted from the electronic health records of the Ajou University Medical Center in South Korea. The study population included patients with psychotic disorders, and outcome was psychosis relapse within 1 year. Using only structured data, we developed an initial prediction model, then three natural language processing (NLP)-enriched models using three types of clinical notes (psychological tests, admission notes, and initial nursing assessment) and one complete model. Latent Dirichlet Allocation was used to cluster the clinical context into similar topics. All models applied the least absolute shrinkage and selection operator logistic regression algorithm. We also performed an external validation using another hospital database. RESULTS A total of 330 patients were included, and 62 (18.8%) experienced psychosis relapse. Six predictors were used in the initial model and 10 additional topics from Latent Dirichlet Allocation processing were added in the enriched models. The model derived from all notes showed the highest value of the area under the receiver operating characteristic (AUROC = 0.946) in the internal validation, followed by models based on the psychological test notes, admission notes, initial nursing assessments, and structured data only (0.902, 0.855, 0.798, and 0.784, respectively). The external validation was performed using only the initial nursing assessment note, and the AUROC was 0.616. CONCLUSIONS We developed prediction models for psychosis relapse using the NLP-enrichment method. Models using clinical notes were more effective than models using only structured data, suggesting the importance of unstructured data in psychosis prediction.
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Affiliation(s)
- Dong Yun Lee
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea
| | - Chungsoo Kim
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, South Korea
| | - Seongwon Lee
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea.,Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, South Korea
| | - Sang Joon Son
- Department of Psychiatry, Ajou University School of Medicine, Suwon, South Korea
| | - Sun-Mi Cho
- Department of Psychiatry, Ajou University School of Medicine, Suwon, South Korea
| | - Yong Hyuk Cho
- Department of Psychiatry, Ajou University School of Medicine, Suwon, South Korea
| | - Jaegyun Lim
- Department of Laboratory Medicine, Myongji Hospital, Hanyang University College of Medicine, Goyang, South Korea
| | - Rae Woong Park
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea.,Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, South Korea
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15
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Skibinska M, Rajewska-Rager A, Dmitrzak-Weglarz M, Kapelski P, Lepczynska N, Kaczmarek M, Pawlak J. Interleukin-8 and tumor necrosis factor-alpha in youth with mood disorders-A longitudinal study. Front Psychiatry 2022; 13:964538. [PMID: 36032249 PMCID: PMC9403049 DOI: 10.3389/fpsyt.2022.964538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 07/25/2022] [Indexed: 11/13/2022] Open
Abstract
Bipolar disorder (BD) is one of the most disabling psychiatric illnesses. Over half of BD patients experienced early onset of the disease, and in most cases, it begins with a depressed mood episode. Up to 50% of adolescents initially diagnosed with major depressive disorder (MDD) convert to bipolar spectrum disorder. Diagnostic tools or biomarkers to facilitate the prediction of diagnosis conversion from MDD to BD are still lacking. Our study aimed to find biomarkers of diagnosis conversion in young patients with mood disorders. We performed a 2-year follow-up study on 69 adolescent patients diagnosed with MDD or BD. The control group consisted of 31 healthy youths. We monitored diagnosis change from MDD to BD. Impulsiveness was assessed using Barratt Impulsiveness Scale (BIS-11) and defense mechanisms using Defense Style Questionnaire (DSQ-40). According to the immunological hypothesis of mood disorders, we investigated baseline cytokines levels either in depressive or hypomanic/manic episodes. We correlated interleukin 8 (IL-8) and Tumor Necrosis Factor-alpha (TNF-alpha) levels with clinical factors. We detected higher IL-8 and TNF-alpha in patients in hypomanic/manic compared to depressed episodes. We found correlations of cytokine levels with immature defense style. We did not discover predictors of diagnosis conversion from MDD to BD.
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Affiliation(s)
- Maria Skibinska
- Protein Biomarkers Unit, Department of Psychiatric Genetics, Poznan University of Medical Sciences, Poznan, Poland.,Department of Psychiatric Genetics, Poznan University of Medical Sciences, Poznan, Poland
| | | | | | - Pawel Kapelski
- Department of Psychiatric Genetics, Poznan University of Medical Sciences, Poznan, Poland
| | - Natalia Lepczynska
- Department of Child and Adolescent Psychiatry, Poznan University of Medical Sciences, Poznan, Poland
| | - Mariusz Kaczmarek
- Department of Cancer Immunology, Poznan University of Medical Sciences, Poznan, Poland
| | - Joanna Pawlak
- Department of Psychiatric Genetics, Poznan University of Medical Sciences, Poznan, Poland
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16
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St Clair D, Lang B. Schizophrenia: a classic battle ground of nature versus nurture debate. Sci Bull (Beijing) 2021; 66:1037-1046. [PMID: 36654248 DOI: 10.1016/j.scib.2021.01.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 07/29/2020] [Accepted: 10/13/2020] [Indexed: 01/20/2023]
Abstract
Much has been learned about the etiology and pathogenesis of schizophrenia since the term was first used by Eugene Bleuler over a century ago to describe one of the most important forms of major mental illness to affect mankind. Both nature and nurture feature prominently in our understanding of the genesis of the overall risk of developing schizophrenia. We now have a firm grasp of the broad structure of the genetic architecture and several key environmental risk factors have been identified and delineated. However, much of the heritability of schizophrenia remains unexplained and the reported environmental risk factors do not explain all the variances not attributable to genetic risk factors. The biggest problem at present is that our understanding of the causal mechanisms involved is still in its infancy. In this review, we describe the extent and limits of our knowledge of the specific genetic/constitutional and non-genetic/environmental factors that contribute to the overall risk of schizophrenia. We suggest novel methods may be required to understand the almost certainly immensely complex multi-level causal mechanisms that contribute to the generation of the schizophrenia phenotype.
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Affiliation(s)
- David St Clair
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, National Clinical Research Center for Mental Disorders, Changsha 410011, China; Institute of Medical Sciences, University of Aberdeen, Aberdeen AB25 2ZD, UK; Bio-X Life Science Research Center, Shanghai Jiao Tong University, Shanghai 200030, China.
| | - Bing Lang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, National Clinical Research Center for Mental Disorders, Changsha 410011, China; Institute of Medical Sciences, University of Aberdeen, Aberdeen AB25 2ZD, UK.
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17
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Ludvigsson JF, Olén O, Larsson H, Halfvarson J, Almqvist C, Lichtenstein P, Butwicka A. Association Between Inflammatory Bowel Disease and Psychiatric Morbidity and Suicide: A Swedish Nationwide Population-Based Cohort Study With Sibling Comparisons. J Crohns Colitis 2021; 15:1824-1836. [PMID: 33640971 PMCID: PMC8675324 DOI: 10.1093/ecco-jcc/jjab039] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND AND AIMS Inflammatory bowel disease [IBD] is linked to psychiatric morbidity, but few studies have assessed general population comparators. We aimed to investigate the risk of psychiatric morbidity and suicide in adult-onset IBD patients. METHODS We used a nationwide population-based cohort study in Sweden [1973-2013]. We studied the risk of psychiatric disorders and suicide in 69,865 adult-onset IBD patients [ulcerative colitis, UC: n = 43,557; Crohn's disease, CD: n = 21,245; and IBD-unclassified: n = 5063] compared to 3,472,913 general population references and 66 292 siblings. RESULTS During a median follow-up of 11 years, we found 7465 [10.7%] first psychiatric disorders in IBD [incidence rate, IR/1000 person-years 8.4] and 306 911 [9.9%] in the general population [IR 6.6], resulting in 1.8 extra psychiatric morbidity per 100 patients followed-up for 10 years and a hazard ratio [HR] of 1.3 [95% confidence interval, 95%CI = 1.2-1.3]. The highest risk of overall psychiatric morbidity was seen in the first year after IBD diagnosis [HR = 1.4, 95%CI = 1.2-1.6] and in patients with extraintestinal manifestations [HR = 1.6, 95%CI = 1.5-1.7]. Psychiatric morbidity was more common in all IBD subtypes [HR 1.3-1.5]. An increased risk of suicide attempts was observed among all IBD types [HR = 1.2-1.4], whereas completed suicide was explicitly associated with CD [HR = 1.5] and elderly-onset [diagnosed at the age of > 60 years] IBD [HR = 1.7]. CONCLUSION Adult-onset IBD was associated with an increased risk of psychiatric disorders and suicide attempts. Psychological follow-up should be provided to patients with IBD, especially those with extraintestinal manifestations and elderly-onset IBD. This follow-up should be within the first year after IBD diagnosis.
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Affiliation(s)
- Jonas F Ludvigsson
- Department of Medical Epidemiology and Biostatistics,
Karolinska Institutet, Solna, Sweden,Department of Pediatrics, Orebro University
Hospital, Orebro, Sweden,Division of Epidemiology and Public Health, School of
Medicine, University of Nottingham, UK,Department of Medicine, Columbia University College of
Physicians and Surgeons, New York, NY,
USA
| | - Ola Olén
- Sachs’ Children and Youth Hospital, Stockholm South
General Hospital, Stockholm, Sweden,Department of Clinical Science and Education
Södersjukhuset, Karolinska Institutet,
Stockholm, Sweden,Clinical Epidemiology Division, Department of Medicine
Solna, Karolinska Institutet, Stockholm,
Sweden
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics,
Karolinska Institutet, Solna, Sweden,School of Medical Sciences, Örebro
University, Sweden
| | - Jonas Halfvarson
- Department of Gastroenterology, Faculty of Medicine and
Health, Örebro University,
Örebro, Sweden
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatistics,
Karolinska Institutet, Solna, Sweden,Pediatric Allergy and Pulmonology Unit, Astrid Lindgren
Children’s Hospital, Karolinska University Hospital,
Stockholm, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics,
Karolinska Institutet, Solna, Sweden
| | - Agnieszka Butwicka
- Department of Medical Epidemiology and Biostatistics,
Karolinska Institutet, Solna, Sweden,Child and Adolescent Psychiatry Stockholm, Stockholm
Health Care Services, Region Stockholm,
Sweden,Department of Child Psychiatry, Medical University of
Warsaw, Warsaw, Poland,Corresponding author: A. Butwicka, Department of Medical
Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden.
Tel: +46 (0) 8-5248 2428; Fax: +46 (0) 8-31 49
75;
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