Abstract TMP90: Hidden Challenges: Mental Health Outcomes in Pediatric Stroke Survivors
Bibliographic record
Abstract
Introduction: The burden of disease from pediatric arterial ischemic stroke (AIS) includes non-visible disability in the form of mental health conditions such as depression and anxiety which impact the quality of life of children and families affected by stroke. Objectives: To determine the scale of the mental health phenomenon in the pediatric AIS population in a large single-center study, and to educate clinicians about this significant risk in pediatric stroke survivors. Methods: A retrospective analysis of a prospective single-center cohort of school-aged children diagnosed with AIS, enrolled between 2002 and 2020 was conducted. Depression and anxiety were evaluated with the Behavior Assessment System for Children (BASC, versions 1 and 3). Prevalence and scores for depression and anxiety were ascertained children with AIS and compared with general pediatric population scores. Somatization, a third internalizing subscale in the BASC questionnaire, was also included in the analysis. Results: AIS patients (N=161, 98 male; median age and range at stroke 1.9 years [0 – 13.8 years]) were assessed with neuropsychological measures at median age and range 9.1 years (5.6 – 16.7 years). Clinical scores for depression, anxiety and somatization, i.e., T= ≥ 70 in the Depression (mean = 81.0, SD= 8.7), Anxiety (mean= 76.6, SD=8.3) and Somatization (mean= 81.9, SD= 11.0) subscales, were found in 13%, 13.7% and 17.4% of school-age children with AIS respectively, with the median age ranging between 8.5 and 9.6 years,representing the age of greatest vulnerability in our cohort. In AIS patients, mean scores for mood, anxiety and somatization were higher compared to the general pediatric population. Age at stroke in the children within the Somatization Clinical group were older than 2 years age at time of stroke(p=0.034). Conclusions: Mental health disorders represent a significant problem in pediatric stroke survivors, with the end of primary school appearing to be the time of greatest vulnerability. These mental health outcomes, (depression, anxiety, somatization) could be associated with age at stroke. The symptoms manifested due to these mental health challenges are frequently overlooked. Therefore, early detection and intervention are essential to change patient trajectories and improve outcomes and quality of life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".