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Record W4406962857 · doi:10.1161/str.56.suppl_1.tmp92

Abstract TMP92: Circadian Variability in Pediatric Stroke

2025· article· en· W4406962857 on OpenAlexaff
Sarah Lee, Anirudh Sreekrishnan, Michael Mlynash, F. Balut, Rachel Pearson, Dana Harrar, Taryn L. Surtees, Janette Mailo, Sahar M. A. Hassanein, Nomazulu Dlamini

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicDietary Effects on Health
Canadian institutionsHospital for Sick ChildrenUniversity of Alberta
Fundersnot available
KeywordsMedicineCircadian rhythmStroke (engine)Internal medicine

Abstract

fetched live from OpenAlex

Introduction: Ischemic stroke in adults demonstrates circadian variation in the timing of onset of symptoms, with the highest risk between 6am and noon (1-4). The influence of circadian timing on stroke biology may differ between children and adults, possibly related to the immature circadian system, variations in school versus work schedules, and diverse stroke pathophysiology (5). The goal of our study was to assess whether timing of ischemic stroke onset demonstrates circadian variability in children. Methods: We queried the International Pediatric Stroke Study, an international multicenter observational registry of children <18 years with arterial ischemic stroke (AIS). Included patients were aged 29 days-18 years with outpatient AIS and known time of stroke symptom onset. Clinical and radiographic features were compared according to 4 distinct time epochs: 6:00-11:59 (morning), 12:00-17:59 (afternoon), 18:00-23:59 (evening) and 00:00-5:59 (night). Clinical outcomes were defined by the Pediatric Stroke Outcome Measure (PSOM). Baseline, clinical and outcome characteristics were compared between the 4 time epochs using independent samples Kruskal-Wallis and Chi-square tests. Pairwise comparisons were conducted where needed. Results: A total of 478 patients met inclusion criteria, 54% male, mean age 9.9±SD 5.7 years. Time of stroke onset by hour is shown in Figure 1. Most strokes occurred in the afternoon (n=185, 38.7%), followed by morning (n=156, 32.6%). Table 1 shows demographic and clinical characteristics by time epoch; clinical and arteriopathy risk factors were more prevalent in nighttime strokes (23/36, 70%, p=0.034). Median PSOM scores at 6 months appeared to be better after evening strokes (0.5, IQR 0-1.5) as compared to morning strokes (1, IQR 0.5-2) and afternoon strokes (1, IQR 0.5-3, p=0.033), but failed adjustment for multiple comparisons (figure 2). Conclusion: Circadian influence on stroke timing appears to differ between adults and children. Further prospective studies with larger sample sizes are needed to understand the impact of circadian rhythm on stroke in childhood.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.012
GPT teacher head0.298
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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