aEEG vs cEEG’s sensivity for seizure detection in the setting of neonatal intensive care units: A systematic review and meta‐analysis
Bibliographic record
Abstract
AIM: Amplitude-integrated electroencephalography (aEEG)'s accuracy compared to conventional electroencephalography (cEEG) has not been fully established. The aim of our study was to conduct a systematic review on the sensitivity of the aEEG for neonatal seizure detection. METHODS: Studies from PubMed and Google Scholar databases comparing recordings of cEEG and aEEG in newborns were included according to the PRISMA method. A quality assessment using the QUADAS-2 tool was provided. A random-effect model was used to account for different sources of variations among studies. Publication biases were represented by a funnel plot, and funnel plot symmetry was assessed. RESULTS: Fourteen studies were reported; sensitivity of each diagnostic tool used (single-channel aEEG, two-channel aEEG, two-channel aEEG plus raw trace EEG) was compared to that of the gold-standard cEEG and to those of the other methods used. Overall sensitivity of the aEEG ranged from 31.25% to 90%. CONCLUSION: Our study provides evidence that sensitivity of aEEG varies significantly and that seizure detection rate is lower than that of cEEG. The two-channel aEEG with raw trace EEG shows a high sensitivity and might represent a valid alternative to the cEEG in the setting of neonatal intensive care units (NICUs).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".