THE SIGNIFICANCE OF HIGH AMPLITUDE POSITIVE ROLANDIC SHARP WAVES IN NEONATAL EEG
Bibliographic record
Abstract
Objectives: Numerous electroencephalographic studies have been carried out on positive rolandic sharp waves (PRSW) in neonates. An additional EEG abnormality noted in our institution is the presence of High Amplitude Positive Rolandic Sharp waves (HAPRS) which have not been described in the English literature. Our objectives were to characterize the HAPRS and differentiate them from PRSW and to ascertain whether there is a clinical correlation of HAPRS and their significance on neurological outcome of neonates. Methods: A retrospective review was conducted of all neonatal patients who had standard neonatal EEG recordings performed in the Neonatal Intensive Care Unit (NICU) at The Hospital for Sick Children, Toronto, from January 2003 to December 2004. HAPRS were determined by their amplitude >200ìV, duration <400 mille seconds, their positive sharply contoured waveform and their maximal distribution over the mid-temporal area, all clearly distinguishable from the ongoing background activity and the PRSW. Results: Three hundred and sixty six EEGs were analyzed. HAPRS were observed in 34 out of 253 infants (13%). Mean follow-up=13.4 months (range: 3 days to 32 months). Out of 34 infants with recorded HAPRS, 19 (56%) had abnormal neurological development, including global delay, language delay or death. Neonates with HAPRS with associated abnormal EEG background activity were found to have poor neurological outcome in 71%. Conclusion: High Amplitude Positive Rolandic Sharp waves (HAPRS) appear to be a distinct neurophysiologic feature. HAPRS may be a unique EEG finding in neonatal recordings that may merit careful interpretation and description in EEG reports. This study provides additional insights into the prognostic value of neonatal EEG.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".