Augmentation With Pregabalin in Schizophrenia
Bibliographic record
Abstract
Anxiety is a core symptom of schizophrenia that elicits significant subjective burden of disease and contributes to treatment resistance in schizophrenia. Anxious syndromes might be attributed to incompletely remitted delusions, the negative syndrome, depressive episodes, panic attacks, social phobia, avoidance after hospitalization, and down-tapering of benzodiazepine medication. Pregabalin, an antagonist at the alpha2delta subunit of voltage-gated Ca channels, modulates several neurotransmitter systems and was found to alleviate anxiety in different mental disorders. In schizophrenia, this treatment option has not been evaluated before.Here, we report a case series of 11 schizophrenic patients who had treatment-resistant anxiety and received augmentation with pregabalin. This observational analysis reveals that the strategy was able to significantly reduce scores on the Hamilton anxiety scale; furthermore, we observed improvements of psychotic positive and negative symptoms and mood as assessed by Positive and Negative Syndrome Scale, Scale for the Assessment of Negative Symptoms, and Calgary Depression Scale for Schizophrenia. After augmentation, both a complete discontinuation of concomitant benzodiazepine treatment as well as a dose reduction of antipsychotics could be achieved. We did not observe pharmacokinetic interactions or adverse events.These observations suggest that treating anxious syndromes in schizophrenia with pregabalin can be effective and tolerable. Further investigations should differentiate schizophrenic subsyndromes of anxiety and evaluate benefits and risks of pregabalin in comparison to placebo and active competitors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".