Outcome of EEGs ordered at a regional children's mental health service.
Bibliographic record
Abstract
INTRODUCTION: Clinical practice guidelines in child psychiatry recommend doing an EEG when warranted based upon a complete history and physical examination. The College of Physicians and Surgeons of Ontario published guidelines as to when an EEG is likely to provide useful information. METHOD: All the electroencephalograms ordered at a tertiary care children's mental health centre over about a 2 year period were reviewed and compared to the guidelines published by the Ontario College of Physicians and Surgeons for ordering EEGs. The outcome of the EEGs and what the ordering physician did after receiving the results were also reviewed. RESULTS: About 53% were ordered for reasons that the guidelines indicated would result in a significant probability of obtaining clinically useful information. EEG abnormalities were identified in 49% of the youth in this category. About 20% were ordered for reasons the guidelines indicated that an EEG was not likely to provide clinically useful information. EEG abnormalities were identified in 24% of the youth in this category. About 27% of EEGs were ordered for reasons not mentioned in the guidelines. EEG abnormalities were identified in 52% of those youth. Youth who had abnormal results were generally followed up with further investigations. Those youth with more severe abnormalities were often referred to a pediatric neurologist for assessment and treatment. CONCLUSIONS: Children with severe mental health problems have an increased probability of having neurological problems which might have an impact on the ability to assess and treat the mental health problem.
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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 | 0.010 |
| 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 | 0.001 | 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".