Health-related quality of life and its determinants in paediatric arterial ischaemic stroke survivors
Bibliographic record
Abstract
OBJECTIVE: Health-related quality of life (HRQL) instruments are patient or proxy-reported outcome measures that provide a comprehensive and subjective assessment of patient's well-being and hence vital for health outcomes evaluation. A clear and thorough understanding of HRQL and its determinants is especially important to appropriately guide health-improving interventions. In this study, HRQL of paediatric arterial ischaemic stroke survivors was assessed using guidelines recommended for interpretation and reporting of the patient-reported outcome data. Determinants of HRQL were also explored. METHODS: Children diagnosed with arterial ischaemic stroke between 2003 and 2012 were assessed at least 1 year poststroke using the parent-proxy report versions of the Pediatric Quality of Life Inventory 4.0 and Pediatric Stroke Recurrence and Recovery Questionnaire. HRQL data were compared with population norms and used as outcome in multiple linear regression analysis. RESULTS: 59 children were evaluated. Mean age at diagnosis of stroke was 2.2 years. Mean age at assessment and time elapsed since stroke was 7 years and 5 years, respectively. A total of 41% children had normal global outcome, whereas 51% had moderate to severe deficits. A lower overall HRQL was observed in both self and proxy reports. Parents reported the maximum impairment in emotional domain, whereas children indicated physical functioning to be the most affected. Neurological outcome, site of stroke and socioeconomic status were independently associated with overall HRQL. CONCLUSIONS: Lower HRQL was demonstrated in children who survived arterial ischaemic stroke. Socioeconomic status of families was an important determinant of HRQL, over and above clinical parameters.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".