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Distinct Subcortical Volume Alterations in Pediatric and Adult OCD: A Worldwide Meta- and Mega-Analysis

2016· review· en· W2517818012 on OpenAlexfundno aff
Premika S.W. Boedhoe, Lianne Schmaal, Yoshinari Abe, Stephanie H. Ameis, Paul Arnold, Marcelo C. Batistuzzo, Francesco Benedetti, Jan C. Beucke, Irene Bollettini, Anushree Bose, Silvia Brem, Anna Calvo, Yuqi Cheng, Kang Ik K. Cho, Sara Dallaspezia, Damiaan Denys, Kate D. Fitzgerald, Jean‐Paul Fouché, Mònica Giménez, Patricia Gruner, Gregory L. Hanna, Derrek P. Hibar, Marcelo Q. Hoexter, Hao Hu, Chaim Huyser, Keisuke Ikari, Neda Jahanshad, Norbert Kathmann, Christian Kaufmann, Kathrin Koch, Jun Soo Kwon, Luisa Lázaro, Yanni Liu, Christine Löchner, Rachel Marsh, Ignacio Martínez‐Zalacaín, David Mataix-Cols, José M. Menchón, Luciano Minuzzi, Takashi Nakamae, Tomohiro Nakao, Janardhanan C. Narayanaswamy, Fabrizio Piras, Christopher Pittenger, Y.C. Janardhan Reddy, João Ricardo Sato, Blair Simpson, Noam Soreni, Carles Soriano‐Mas, Gianfranco Spalletta, Michael C. Stevens, Philip R. Szeszko, David F. Tolin, Ganesan Venkatasubramanian, Susanne Walitza, Zhen Wang, Guido van Wingen, Jian Xu, Xiufeng Xu, Je‐Yeon Yun, Paul M. Thompson, Dan J. Stein, Odile A. van den Heuvel, Pino Alonso, Núria Bargalló, Geraldo F. Busatto, Rosa Calvo, Daniëlle C. Cath, Froukje E. de Vries, Stella J. de Wit, Yu Fang, Martine Fontaine, Sabin Khadka, Eurı́pedes Constantino Miguel, Luciano Minuzzii, Ástrid Morer, Dick J. Veltman, Ysbrand D. van der Werf

Bibliographic record

VenueAmerican Journal of Psychiatry · 2016
Typereview
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Biomedical Imaging and BioengineeringNational Institute of Mental HealthInstituto de Salud Carlos IIIJapan Society for the Promotion of ScienceServierMedical Research CouncilCanadian Institutes of Health ResearchUniversiteit van AmsterdamCollege of Medicine, Seoul National UniversityCumming School of Medicine, University of CalgaryNational Institutes of HealthMinisterio de Ciencia e InnovaciónHamilton Health Sciences FoundationDepartment of Science and Technology, Ministry of Science and Technology, IndiaHospital for Sick ChildrenH. Lundbeck A/SUniversitat Autònoma de BarcelonaAgència de Gestió d'Ajuts Universitaris i de RecercaThe Wellcome Trust DBT India AllianceUniversity of Cape TownHumboldt-Universität zu BerlinMathison Centre for Mental Health Research and EducationUniversidade de São PauloEli Lilly and CompanyKoninklijke Nederlandse Akademie van WetenschappenCentro de Investigación Biomédica en Red de Salud MentalYale UniversityKarolinska InstitutetKunming Medical UniversityNational Institute of Mental Health and NeurosciencesSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungSeoul National UniversityUniversität ZürichMinistry of Education, Culture, Sports, Science and TechnologyBundesministerium für Bildung und ForschungEuropean Regional Development FundUniversitat de BarcelonaDeutsche ForschungsgemeinschaftTechnische Universität MünchenNederlandse Organisatie voor Wetenschappelijk OnderzoekUniversidade Federal do ABCNational Science FoundationDepartment of Biotechnology, Ministry of Science and Technology, IndiaCanadian Network for Mood and Anxiety TreatmentsUniversity of Southern CaliforniaWellcome TrustOntario Brain InstituteUniversity of CambridgeHamilton Health SciencesBristol-Myers SquibbMinistero della SaluteInternational OCD FoundationGlaxoSmithKline
KeywordsMeta-analysisMedicineSample size determinationBrain sizeInternal medicinePsychologyMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Structural brain imaging studies in obsessive-compulsive disorder (OCD) have produced inconsistent findings. This may be partially due to limited statistical power from relatively small samples and clinical heterogeneity related to variation in illness profile and developmental stage. To address these limitations, the authors conducted meta- and mega-analyses of data from OCD sites worldwide. METHOD: images from 1,830 OCD patients and 1,759 control subjects were analyzed, using coordinated and standardized processing, to identify subcortical brain volumes that differ between OCD patients and healthy subjects. The authors performed a meta-analysis on the mean of the left and right hemisphere measures of each subcortical structure, and they performed a mega-analysis by pooling these volumetric measurements from each site. The authors additionally examined potential modulating effects of clinical characteristics on morphological differences in OCD patients. RESULTS: The meta-analysis indicated that adult patients had significantly smaller hippocampal volumes (Cohen's d=-0.13; % difference=-2.80) and larger pallidum volumes (d=0.16; % difference=3.16) compared with adult controls. Both effects were stronger in medicated patients compared with controls (d=-0.29, % difference=-4.18, and d=0.29, % difference=4.38, respectively). Unmedicated pediatric patients had significantly larger thalamic volumes (d=0.38, % difference=3.08) compared with pediatric controls. None of these findings were mediated by sample characteristics, such as mean age or scanning field strength. The mega-analysis yielded similar results. CONCLUSIONS: The results indicate different patterns of subcortical abnormalities in pediatric and adult OCD patients. The pallidum and hippocampus seem to be of importance in adult OCD, whereas the thalamus seems to be key in pediatric OCD. These findings highlight the potential importance of neurodevelopmental alterations in OCD and suggest that further research on neuroplasticity in OCD may be useful.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.031
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.334
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations344
Published2016
Admission routes1
Has abstractyes

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Same venueAmerican Journal of PsychiatrySame topicObsessive-Compulsive Spectrum DisordersFrench-language works237,207