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Record W2602762505 · doi:10.1093/schbul/sbx024.114

SU118. Cognitive Impairment and Clozapine Response in Treatment-Resistant Schizophrenia—A Cross-Sectional Study

2017· article· en· W2602762505 on OpenAlexaff
Shinichiro Nakajima, Yusuke Iwata, Eric Plitman, Jun Ku Chung, Philip Gerretsen, Wanna Mar, Vincenzo De Luca, Gary Remington, Ariel Graff‐Guerrero

Bibliographic record

VenueSchizophrenia Bulletin · 2017
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsClozapineTrail Making TestSchizophrenia (object-oriented programming)Stroop effectPsychologyRepeatable Battery for the Assessment of Neuropsychological StatusCognitionPsychiatryWechsler Adult Intelligence ScaleWechsler Memory ScaleInternal medicineClinical psychologyNeuropsychologyAudiologyMedicine

Abstract

fetched live from OpenAlex

Background: Response to clozapine is proposed to be a marker by which patients with schizophrenia can be stratified into biologically distinct subgroups. While cognitive impairment is a core symptom of schizophrenia, few studies have examined the relationship between cognitive function and response to clozapine in patients with treatment-resistant schizophrenia. Methods: This study included 16 patients with schizophrenia who responded to clozapine (age: 43.2 ± 11.9 y; female 37.5%), 19 patients who did not respond to clozapine (44.6 ± 11.3 y; 26.3%), and 19 healthy controls (HC) (44.1 ± 12.5 y; 31.6%). Participants were age and sex matched. The following cognitive assessments were administered: Executive Interview (EXIT), Finger Tapping (FT), Grooved Pegboard (GP), Letter Fluency (F, A, and S) (LF), Letter-Number Span (LNS), Mini-Mental Status Exam (MMSE), Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Stroop Test, Trail Making Test A and B (TMT), and Wechsler Test of Adult Reading (WTAR). Cognitive functions were compared among the 3 groups using analyses of variance with a significant P-value less than 0.0022 (0.05/23). If there was a significant difference among them, post hoc Tukey’s tests were conducted with a significant P-value less than 0.0038 (0.05/13). Results: PANSS total, positive subscale, and global subscale scores were higher in nonresponders than in responders (P < .001, P < .001, and P < .001, respectively). Significant differences were found in scores of WTAR, EXIT, RBANS Immediate Memory, Visuospatial/Constructional, Language, Attention, and Delayed Memory domains, GP, LF F test, LNS, Stroop Color-Word tests, and TMT B among the 3 groups (P < .001, P ≤ .001, P < .001, P = .001, P < .001, P < .001, P < .001, P < .001, P = .001, P < .001, P < .001, P < .001, respectively). No differences were found in MMSE, FT, LF A and S tests, Stroop Color test, and TMT A scores, and score ratios of Stroop Color and Color-Word tests and TMT A and B. Among these 13 domains, there was no domain where any difference was found between responders and nonresponders. WTAR, EXIT, RBANS Language domain, LF F test, and Stroop Color-Word test scores were lower in nonresponders than HC without any significant differences among other comparisons. Both responders and nonresponders performed significantly worse than HC on RBANS Total scale, Immediate Memory, Visuospatial/Constructional, Attention, and Delayed Memory domains, GP, LNS, and TMT B without any significant differences between responders and nonresponders. Conclusion: Regardless of response to clozapine, patients with treatment-resistant schizophrenia appear to have impairments in attention, processing speed, working memory, cognitive control/executive function, and visual learning. These results are consistent with the finding that cognitive symptoms are generally unresponsive to antipsychotic treatment.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.031
GPT teacher head0.341
Teacher spread0.310 · 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 designObservational
Domainnot available
GenreEmpirical

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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Citations0
Published2017
Admission routes1
Has abstractyes

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