Clinical Significance of Positive Spike Wave Discharges in the Pediatric Population: Insights Beyond Neonates
Bibliographic record
Abstract
INTRODUCTION: Positive spike wave (PSW) discharges on EEG are well-documented in neonates, but data regarding their significance in other populations are limited. This study aimed to assess the clinical significance of PSW in children aged 1 month to 19 years at a single tertiary care center over approximately three decades. METHODS: Clinical information of children with focal PSW ( n = 326) was compared with control patients with focal negative interictal epileptiform discharges ( n = 898). RESULTS: From 77,500 pediatric EEGs in our laboratory from 1992 to 2020, PSW were identified in 445 (0.57%) children, of which 326 met inclusion criteria. Positive spike waves were located in the following brain regions: occipital (139), central (65), frontal (63), temporal (43), parietal (9), and centro-temporal (7). Positive spike wave patients had a younger median age of seizure onset than control patients (1.1 years [0.30, 4.00] versus 4 years [1.3, 7.5], P < 0.001).Logistic regression analysis confirmed that PSW were associated with high odds of seizures [odds ratios (OR) 3.78; CI: 2.14-2.14; P < 0.005], epilepsy [OR 2.05; CI: 1.39-1.39; P < 0.005], and drug-resistant epilepsy, [OR 3.51; CI: 2.67-2.67; P < 0.005]. Furthermore, PSW correlated with a greater odd of developmental delay [OR 3.69; CI: 2.77-2.77; P < 0.005], school difficulties [OR 2.85; CI: 2.07-2.07; P < 0.005], abnormal neurologic exam [OR 2.8; CI: 2.15-2.15; P < <0.005], and structural brain abnormalities [OR 1.74; CI: 1.32-1.32; P < 0.005], such as malformation of cortical development, compared with control patients. CONCLUSIONS: Positive spike waves on pediatric EEG are associated with congenital or acquired brain abnormalities and less favorable seizure and neurodevelopmental outcomes.
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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 | 0.002 |
| 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".