Emergency physician referrals to the pediatric crisis clinic: reasons for referral, diagnosis and disposition.
Bibliographic record
Abstract
OBJECTIVE: To describe the patient population, diagnoses, and disposition of children and adolescents referred by Pediatric Emergency Medicine (PEM) physicians to a Pediatric Psychiatric Crisis Clinic (PCC) for urgent consultation; to describe the percent agreement between PEM physician discharge diagnosis and subsequent child psychiatrist diagnoses. METHOD: Data were obtained prospectively over a one-year period for consecutive patients referred to the PCC (n=174). Patients and families were contacted for information regarding subsequent emergency department (ED) visitation following PCC consultation. RESULTS: Referred patients were commonly male (63%) with a mean age of 12.2 ± 3.2 years diagnosed with adjustment disorder (29%), mood disorder (17%) and anxiety disorder (17%) and significant psychosocial stressors. Five percent of patients required hospitalization. PEM physician discharge diagnosis and child psychiatrist diagnosis were in agreement in 21% of cases. CONCLUSION: Patients referred by PEM physicians for urgent outpatient psychiatric assessment were most commonly early adolescent males. The majority of patients did not require ongoing psychiatric care. Further investigation into the differences between PEM physician and child psychiatrist diagnoses is needed to ensure patients and families receive accurate and consistent mental health information and recommendations from all members of their health care team.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".