Challenges in Differentiating and Diagnosing Psychotic Depression
Bibliographic record
Abstract
<P>Major depression with psychotic features (MD-Psy), a disorder with considerable morbidity and mortality, is more common than is generally realized and is encountered frequently in clinical practice. Although studies conducted in both inpatient and outpatient settings have estimated that 16% to 54% of adults with depression are also psychotic, MD-Psy often is not diagnosed accurately because the psychosis may be subtle, intermittent, or concealed leading to a misdiagnosis of nonpsychotic depression.</P> <H4>ABOUT THE AUTHORS</H4> <P>Dr. Rothschild is Irving S. and Betty Brudnick Professor of Psychiatry, Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA. Dr. Mulsant is professor of psychiatry, Western Psychiatric Institute and Clinic, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA; clinical director, Geriatric Mental Health Program, Centre for Addiction and Mental Health, Toronto, and professor, Department of Psychiatry, University of Toronto. Dr. Meyers is professor of psychiatry, Department of Psychiatry, Weill Medical College of Cornell University and New York Presbyterian Hospital, Westchester, NY. Dr. Flint is professor, Department of Psychiatry, University of Toronto, and head, Geriatric Psychiatry Program, University Health Network, Toronto, Ontario, Canada; the Geriatric Program and Research Institute, Toronto Rehabilitation Institute, Toronto; and the Toronto General Research Institute, Toronto.</P> <P>Address reprint requests to: Anthony J. Rothschild, MD, University of Massachusetts Medical School, 361 Plantation Street, Worcester, MA 01605; or e-mail <a href="mailto:rothscha@ummhc.org">rothscha@ummhc.org</a>.</P> <P>Dr. Rothschild disclosed relevant financial relationships with Lilly and Pfizer. Dr. Mulsant disclosed relevant financial relationships with Pfizer, Eli Lilly, Forest/Lundbeck, AstraZeneca, Janssen, and Alkermes. Dr. Flint disclosed a relevant financial relationship with Pfizer Canada. Dr. Meyers disclosed no relevant financial relationships. </P> <P>This research was supported in part by National Institutes of Mental Health grants MH 62518, MH 62446, MH 62565, and MH 62624 and the Irving S. and Betty Brudnick Endowed Chair in Psychiatry, University of Massachusetts Medical School.</P>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".