A naturalistic controlled study of relapsing schizophrenic patients with tardive dyskinesia and supersensitivity psychosis
Bibliographic record
Abstract
Despite advances in treatments, relapses in schizophrenia still occur. The causes of relapse are not always apparent, especially for patients that are compliant with medication. One possibility is that the brain adapts to long-term antipsychotic drug treatment, leading to tolerance and withdrawal symptoms. This has been described as supersensitivity psychosis. Tardive dyskinesia is also thought to occur as a consequence of dopamine supersensitivity caused by chronic treatment with antipsychotics. Another associated feature is sensitivity to life stress. This study investigated the relationship between abnormal movements, life events and drug treatment in patients relapsing on antipsychotics with high potency at the dopamine D2 receptor. Twenty-two patients from a cohort of 128 patients experiencing a psychotic relapse were assessed; of these, seven (32%) met criteria for the presence of abnormal involuntary movements. These subjects were found to be clinically distinct from the subjects without abnormal movements. They tended to be older with a greater duration of illness and higher dosage of antipsychotics but more symptoms of psychosis compared with the other subjects. Relapse was also associated with minor life events. The association between abnormal involuntary movements and high levels of psychotic symptoms suggests that dopamine sensitization/supersensitivity may underlie both phenomena. These results suggest that clinicians may have to consider alternative dosing strategies, novel agents or switching to one of the antipsychotics that have a lower affinity for the D2 receptor.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".