A Conceptual Analysis of Post-psychotic Depression
Bibliographic record
Abstract
"The conundrum of post-psychotic depression (PPD) is still present in the psychiatric literature, for more than a century since it was first described by Mayer-Gross. After a short existence in the DSM-IV and ICD-10, this nosological construct was excluded from newer versions of the mental disorders classifications. Therefore, an exploratory analysis of the PPD concept was considered useful both from clinical and theoretical perspectives. There is a high prevalence of depressive symptoms in patients with schizophrenia spectrum disorders (SSD) and, although not all of them represent cases of PPD, they are considered risk factors for suicide. The arguments and contra-arguments for/against PPD were reviewed, and the potential pharmacological interventions for this disorder were analyzed. The explored evidence indicates that PPD is worth further investigation, and in order to differentiate it from schizoaffective disorder, negative symptoms of SSD, or depressive manifestations within the acute psychotic episodes, clearly defined criteria should be found. The use of validated scales, like the Calgary Depression Scale for Schizophrenia and the InterSePT Scale for Suicidal Thinking, is recommended for the initial assessment of depression and suicidal risk in patients with SSD, but also for their monitoring during the acute and maintenance phases. Besides the administration of combined, antidepressant and antipsychotic treatment, the use of clozapine, and the recommendation to initiate treatment for SSD with atypical antipsychotics whenever possible, there is a dearth of studies exploring specific interventions for PPD. Future studies are expected to address the validity of the nosological construct of PPD and the most adequate therapeutic and prophylactic interventions in patients with SSD."
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".