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Record W2139501100 · doi:10.1155/2014/384783

Tackling Negative Symptoms of Schizophrenia with Memantine

2014· article· en· W2139501100 on OpenAlexaboutno aff
Antonios Paraschakis

Bibliographic record

VenueCase Reports in Psychiatry · 2014
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMemantineSchizophrenia (object-oriented programming)Scale for the Assessment of Negative SymptomsMedicineDelusionInternal medicinePsychiatryAmisulprideRisperidonePositive and Negative Syndrome ScalePsychosisNMDA receptorNegative symptomReceptor

Abstract

fetched live from OpenAlex

We present a case of a 52-year-old male patient suffering from chronic schizophrenia stabilized on risperidone long-acting injection (37,5 mg/2 weeks) and biperiden 4 mg/day. Residual symptoms are affective flattening, alogia, avolition, and asociality. Memantine 10 mg/day was added. After 1.5 months, the patient spontaneously referred to "feel better being in company of my relatives." The following scales have been completed: the Scale for the Assessment of Negative Symptoms (96), the Scale for the Assessment of Positive Symptoms (3), the Mini Mental Scale Examination (26), and the Calgary Depression for Schizophrenia Scale (2). Memantine was increased to 20 mg/day and biperiden was decreased to 2 mg/day. Two months later, apathy and asociality considerably improved and affective flattening, alogia, and attention slightly got better (SANS 76, SAPS 1, MMSE 26, and CDSS 1). After two more months, the improvement continued in the same domains (SANS: 70, SAPS: 1 MMSE: 27, and CDSS: 1). Positive symptoms remained in full remission. It has been hypothesized that one of the causes of schizophrenia is glutamate excitotoxicity. Memantine, a glutamate receptor antagonist, could possibly ameliorate schizophrenia symptoms, the negative ones among them, used as add-on therapy to atypical antipsychotics. Memantine could be of potential help in schizophrenia patients with severe residual negative symptoms.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.008
GPT teacher head0.276
Teacher spread0.268 · 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

Citations11
Published2014
Admission routes1
Has abstractyes

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