Use of long acting antipsychotics and relationship to newly diagnosed bipolar disorder: a pragmatic longitudinal study based on a Canadian health registry
Bibliographic record
Abstract
BACKGROUND: There is limited data from large naturalistic studies to inform prescribing of long-acting injectable medication (LAIs). Guidance is particularly rare in the case of primary mood disorders. METHODS: This study describes prescribing trends of LAIs in 3879 patients in Quebec, Canada, over a period of 4 years. Health register data from the Quebec provincial health plan were reviewed. RESULTS: In this specific registry, 32% of patients who received LAIs drugs for schizophrenia had a confirmed diagnosis of bipolar disorder and 17% had a diagnosis of major depressive disorder. Non-schizophrenia syndromes were preferentially prescribed risperidone long-acting antipsychotic, whereas patients with schizophrenia were prescribed an excess of haloperidol decanoate. Patients with non-schizophrenia disorders prescribed long-acting antipsychotics were more frequently treated in primary care compared with patients with schizophrenia. CONCLUSION: Data from a large number of patients treated naturalistically in Quebec with long-acting antipsychotics suggests that these compounds, prescribed to treat symptoms of schizophrenia and schizoaffective disorders, were maintained when mood symptoms emerged, even in cases when the diagnosis changed to bipolar disorder. This pragmatic study supports the need to explore this intervention as potential treatment for affective disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".