Medical Multimorbidity in Patients With Treatment‐Resistant Psychosis and Rare Copy Number Variants: A Retrospective Case Series of 24 Patients
Bibliographic record
Abstract
Neurodevelopmental disorder-risk copy number variations (NDD CNVs) are associated with complex neuropsychiatric phenotypes. These CNVs also confer risk for a host of medical outcomes in adults; yet, the long-term health consequences in the context of comorbid psychiatric illness have not been well documented. Twenty-four psychiatric inpatients with treatment-resistant psychosis were identified as carriers of NDD CNVs as part of a larger Pennsylvania State Hospital genomics study. Comprehensive life course phenotyping was performed through review of medical records, specialized neurobehavioral evaluation, and synthesis of data using the Human Phenotype Ontology. Phenotypes examined across the cohort indicated comorbid medical manifestations across multiple organ systems. Cardiovascular disorders were present in 96% of patients and motor disorders in 92%. All patients had multiple organ system involvement, and most organ systems (12/17 systems) were affected in 50% or more of patients, culminating in a high degree of individual-level multimorbidity. Comparing our observations to previously known CNV-associated phenotypes indicated several potentially novel health outcomes for individual CNV loci. Our descriptive case series supports a complex and multidimensional course of illness. Thorough reporting on the long-term implications of these variants is the first step toward advancing clinical care for these complex psychiatric patients carrying NDD CNVs.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".