Transcranial direct current stimulation (tDCS) improved psychomotor slowness and decreased catatonia in a patient with schizophrenia: Case report
Bibliographic record
Abstract
Transcranial direct current stimulation (tDCS) improved psychomotor slowness and decreased catatonia in a patient with schizophrenia: Case report Dear Editor,Psychomotor slowness and catatonia in schizophrenia could be associated with the limbic system, the hippocampus, and the dorsolateral prefrontal cortex (DLPFC) [1].Transcranial direct current stimulation (tDCS) is getting known as a safe, non-invasive neurostimulation technique for treating patients suffering from these conditions; however, the clinical evidence regarding the efficacy of tDCS in treating psychomotor slowness and catatonia is very scarce [2,3].A 40-year-old female patient with schizophrenia had received a long-acting antipsychotic (flupentixol decanoate, 20 mg per 4 weeks) for 17 years.However, motor slowing, mild depression, a lesser influence of external stimuli, motor stereotypies, and sometimes reaching the point of immobility were gradually noted over several months.She demonstrated mild catatonic excitement and stupor.Sometimes the patient stayed in her car at the parking lot for hours, after finish her working hours, while the patient was unable to explain why demonstrate this behavior when she was found by family members.Also the patients would park her car on the roadside until night, without any explanation.Given the presence of psychomotor retardation and mild depression, the prescription was changed to different kinds of oral antipsychotics several times.Under treatment with bupropion 150 mg/ day, amantadine 100 mg/day, propranolol 20 mg/day, amisulpride 400 mg/day and diazepam 10 mg/day for 6 weeks, little to get improved.Add-on treatment with tDCS was therefore recommended, and the patient and her legal proxy consented to participate in this trial.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".