A Reappraisal of Rhythmic Coma Patterns in Children
Bibliographic record
Abstract
OBJECTIVE: This study was designed to determine the prevalence of rhythmic coma patterns in comatose children and to ascertain the prognostic significance of reactive rhythmic coma patterns. METHODS: We retrospectively analyzed and classified electroencephalogram (EEGs) in comatose children between two months and 18 years of age during the period 1996 - 2003 according to modified Young's classification. Outcome at one-year was scored according to the Paediatric Cerebral and Overall Performance Category Scale. Outcomes were compared using Fisher's exact test and Mann-Whitney test. RESULTS: Analysis of 63 electroencephalogram (EEG) records in 38 patients showed rhythmic patterns in 19 records (30.2%; 9 alpha, 4 spindle, 4 theta and 2 beta coma patterns, total number of children = 14). Aetiology and outcome of alpha coma patterns and other rhythmic coma patterns were similar. In five children, one type of rhythmic pattern changed to another. Records with reactive rhythmic coma 66.7% (6/9), were associated with favourable outcome. Sixty percent of the records (6/10 records in seven children) with non-reactive pattern were associated with unfavourable outcome. This clinically significant difference did not reach statistical significance (lower Paediatric Cerebral and Overall Performance Category Scale score p= 0.14; favourable outcome p=0. 19). CONCLUSION: Rhythmic coma patterns in comatose children are not uncommon. Aetiology, reactivity and outcome of individual patterns are similar and thus make the rhythmic coma patterns distinct EEG signatures in comatose children. There was a clinically significant better outcome with reactive rhythmic coma patterns.
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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 | 0.003 |
| 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 | 0.000 |
| 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".