EPA-0251 - Poor outcome manic syndrome among first admitted manic patients : prevalence and longitudinal clinical correlates
Bibliographic record
Abstract
A First Manic Episode (FME) can evolve differently and some patients remain chronically ill (Poor Outcome Manic Syndrome = POMS). Even, the majority of subsequent episodes reoccur over the time; few studies have looked at the long-term course of a FME. The aim is therefore to look at the longitudinal clinical characteristics of FME in a hospital setting. The subjects, developing POMS, were patients admitted to hospital with at least 2 hospitalizations for mania and having received continuing psychiatric care for ≥ 5 years. The control group subjects were FME patients with only one admission. The data was gathered from hospital discharge summaries for all 472 subjects with FME (age 14–64) admitted to a Quebec regional psychiatric hospital for the first time during a 30 year period (1980-2011). Amongst all first admitted FME patients, 27% ended up with POMS. A logistic regression analysis indicates the subsequent development of POMS was correlated with younger age, male gender and alcohol misuse at the time of the initial admission to hospital. The historical data available (median=11 years) shows that the diagnosis evolved towards bipolar disorder (76%), schizoaffective disorder (17%) and schizophrenia (6%). The results indicate that development of POMS is an inevitable clinical reality. The influence of alcoholism on the evolution of FME is clearly adverse. It is particularly associated with more manic episodes. The results underline the necessity for concomitant intervention for alcoholism in the presence of FME.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".