Disclosure of psychiatric manifestations of 22q11.2 deletion syndrome in medical genetics: A 12‐year retrospective chart review
Bibliographic record
Abstract
Individuals with 22q11.2 deletion syndrome (22qDS) have increased risk for psychiatric disorders. However, while medical geneticists self-report discussing psychiatric features of 22qDS with families (though often only when the child is older), most parents of children with 22qDS report receiving information about the psychiatric manifestations of 22qDS from non-medical sources. In an attempt to reconcile these previous findings, we sought to objectively determine the frequency with which medical geneticists discuss the potential psychiatric manifestations of 22qDS: (i) in letters to referring physicians and (ii) with families, and to explore plans for follow-up. We abstracted data from charts of patients with 22qDS who were referred to a single medical genetics center between January 1, 2000 and December 31, 2012. Psychiatric disorders were discussed in consult letters to referring physicians for n = 57 (46%) of the 125 patients who met inclusion criteria-making them less frequently discussed than all other features of 22qDS. Despite exhaustive review of charts, the content of discussions with families was typically unclear. Follow-up in medical genetics was suggested for 50 people but only 18 (36%) of these patients returned. Disclosure of psychiatric features of 22qDS to families is necessary so that psychiatric disorders can be identified in time for early intervention to be implemented to achieve better prognosis for those affected. These empiric data offer some explanation as to why psychiatric services are underused by individuals with 22qDS.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| 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) | 0.001 | 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".