Effects of Bupropion on Cognitive Function in Schizophrenia: A Double Blind Randomized Controlled Trial
Bibliographic record
Abstract
Smoking habits are common in schizophrenic patients. Nicotine can suppress negative symptoms and cognitive impairments. The aim of this study was to determine the efficacy of bupropion on cognitive function in schizophrenic patients. This study is a double blind randomized controlled trial in a large referral psychiatric university hospital in Iran. Ninety smoker schizophrenic patients were randomly allocated (based on DSM -IV TR criteria) in two groups (46 patients for case group and 44 patients in control group). They get risperidone up to 6 mg/d and bupropion up to 400 mg/d .clinical assessment (Positive and Negative Syndrome Scale (PANSS), Brief psychiatric rating scale (BPRS) were taken in beginning of study, 14th and 28th days of study. Cognitive assessment (Stroop, Digit Span, and Wechsler, Wisconsin) were taken in begging of study, the days 2nd, 7th, 14th, 28th. All data were analyzed by SPSS Ver. 17 with analytic and descriptive tests. Mean age of patients was 37.66±1.01. Mean duration of disorder was 11.63±.98 years. The scores were significantly lower at the day 28th compared to the beginning of the study in both groups in Wechsler, Stroop color word , Stroop word , Stroop color , BPRS, PANSS p value ≤0.05 .The difference between the two treatments was not significant as indicated by the effect of group, the between-subjects factor p value ≥0.05. In this study, the side effects were examined and there was no significant difference between the two groups p value ≥0.05. Augmentation of bupropion to routine treatment improves cognitive symptoms of schizophrenia in abstinence of tobacco.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".