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Record W2607344842 · doi:10.1080/24750573.2017.1293242

Differential effects of clozapine and risperidone on facial emotion recognition ability in patients with treatment-resistant schizophrenia

2017· article· en· W2607344842 on OpenAlexaboutno aff
Gözde Gültekin, Erhan Yuksek, Tevfik Kalelioğlu, Alper Baş, Tuba Öcek Baş, Alaattin Duran

Bibliographic record

VenuePsychiatry and Clinical Psychopharmacology · 2017
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsRisperidoneClozapineSchizophrenia (object-oriented programming)Positive and Negative Syndrome ScalePsychologyAtypical antipsychoticPsychosocialPsychopathologyPsychiatryClinical psychologyInternal medicinePsychosisAntipsychoticMedicine

Abstract

fetched live from OpenAlex

Objective: Clozapine and risperidone are used for treatment-resistant schizophrenia and known to improve the positive and negative symptoms. However, there are some conflicts about effects on social cognition, which is measured with facial emotion recognition ability. The impairments in facial emotion recognition ability have frequently been in different stages of the illness and might have negative influences on psychosocial functioning. In the present study, we aimed to examine clozapine and risperidone effects recognizing facial emotions in patient with treatment-resistant schizophrenia.Methods: Thirty-four patients were screened for the study, and 19 patients were included. All patients were evaluated with Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale for Schizophrenia, and Functional Remission of General Schizophrenia Scale at baseline and after 16–20 weeks of clozapine (n = 12) or risperidone (n = 7) treatment. Furthermore, the Facial Emotion Recognition Test was performed before and after treatment. The test included the photos of four male and four female models (totally 56 mixed photos) with happy, surprised, fearful, sad, angry, disgusted, and neutral facial expressions from Ekman and Friesen’s catalog.Results: The mean dose of the index drug in clozapine group was 295.83 ± 103.26 mg/day. The mean positive (p = .002), negative (p = .050) general psychopathology (p = .002), and total score (p = .002) according to the PANSS were significantly improved after treatment. The mean dose of the index drug in risperidone group was 6.86 ± 1.57 mg/day. The mean positive symptom (p = .018) and total score (p = .041) were significantly improved after treatment but negative symptom scale (p = .396) and general psychopathology (p = .149) scores did not change. There were no significant differences between baseline and after treatment in clozapine and risperidone group according to the accuracy rate of facial emotion recognition expressions (p > .05 for each). At baseline phase, the patients were significantly impaired in recognizing disgusted faces in risperidone than those in clozapine group (p = .032) and it was significantly poorer after treatment with risperidone than with clozapine (p = .031). The patients responded significantly faster after the treatment to all facial emotions except for fearful faces (p = .355).Conclusions: Clozapine and risperidone were not found to have extensive effects on the ability to recognize facial emotions because of ineffectiveness to negative symptoms as in our study. We speculated that the higher dopaminergic receptor occupancy rate of risperidone in insular cortex than that of clozapine might be related with hypo-activation of insula that was associated with particular deficit in ability to recognize expressions of disgust in patients with schizophrenia. Impaired facial emotion recognition ability is present even in first-episode psychosis, which might be a trait marker in schizophrenia.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.225
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.361
Teacher spread0.340 · 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 teacher head, 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".

Quick stats

Citations8
Published2017
Admission routes1
Has abstractyes

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