GR.4 Circadian rhythm influences ischemic core and penumbra volumes in pediatric and young adult populations
Bibliographic record
Abstract
Background: Circadian rhythms are implicated in timing of stroke onset and infarct progression in adults, but this has not been studied in pediatric/young adult populations. Methods: We queried the RAPID Insights database from centers in USA for unique patients <25 years with a CTP (10/05/2018-09/29/2023) and a minimum ischemic core volume (defined as relative cerebral blood flow (rCBF) reduction of <30%) of >0 cc and minimum mismatch of >0 cc. Imaging time was subdivided into three epochs: Nigh (23:00 h-06:59 h), Day (07:00 h-14:59 h), and Evening (15:00 h-22:59 h). We analyzed age by pre-defined strata: <2 years, 2-5, 6-11, 12-18 and 19-25. Perfusion parameters (core, perfusion volume, mismatch ratio) were analyzed using descriptive statistics. Results: 836 patients were included; 52.3% were in the 19-25 category. Median ischemic cores were larger during the Night (23.0cc [10.0 – 58.0]) compared to Day (19.0cc [8.0-42.0]) or Evening (15.0cc [7.0-33.0]), p=0.009. There was a trend towards larger perfusion volumes in the Night epoch. In the 19-25 group, perfusion volumes were significantly larger at Night (127.5cc [51.5 – 203.5]) compared to Day (74.0cc [33.0 – 139.0]) or Evening (76.0cc [38.0 – 157.5]), with larger mismatch volumes at Night. Conclusions: This is the first study to demonstrate diurnal fluctuations in perfusion parameters in a predominantly pediatric cohort.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".