Extrapyramidal Symptoms Related to Adjunctive Nizatidine Therapy in an Adolescent Receiving Quetiapine and Paroxetine
Bibliographic record
Abstract
Weight gain is a serious problem with recently introduced atypical antipsychotic agents. Nizatidine, a histamine2 (H2)-receptor antagonist, may help reduce this weight gain. To our knowledge, no adverse effects have been reported when nizatidine is given at recommended doses with atypical antipyschotic agents. We describe, however, an adolescent who was receiving quetiapine and paroxetine for schizophrenia and depression, and developed extrapyramidal symptoms (EPS; parkinsonism and akathisia) after taking nizatidine for weight loss. Based on a report of another patient who developed EPS after taking higher-than-recommended doses of nizatidine, we reviewed the literature on treatment with H2-receptor antagonists for weight gain and on central nervous system adverse effects of nizatidine. Nizatidine may be effective for reducing weight gain associated with both medical and psychiatric conditions. Its safety profile is usually benign, although some patients may develop serious adverse effects, such as EPS and delirium. Therefore, the drug is recommended for short-term management of weight gain associated with atypical antipsychotic agents. Patients receiving nizatidine therapy should be monitored closely for development of EPS, particularly when high doses are prescribed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".