A Systematic Review of Risk Factors Associated With Cognitive Impairment After Pediatric Critical Illness*
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: To identify risk factors associated with cognitive impairment as assessed by neuropsychologic tests in neurotypical children after critical illness. DATA SOURCES: For this systematic review, we searched the Cochrane Library, Scopus, PubMed, Ovid, Embase, and CINAHL databases from January 1960 to March 2017. STUDY SELECTION: Included were studies with subjects 3-18 years old at the time of post PICU follow-up evaluation and use of an objective standardized neuropsychologic test with at least one cognitive functioning dimension. Excluded were studies featuring patients with a history of cardiac arrest, traumatic brain injury, or genetic anomalies associated with neurocognitive impairment. DATA EXTRACTION: Twelve studies met the sampling criteria and were rated using the Newcastle-Ottawa Quality Assessment Scale. DATA SYNTHESIS: Ten studies reported significantly lower scores in at least one cognitive domain as compared to healthy controls or normed population data; seven of these-four case-control and three prospective cohort studies-reported significant lower scores in more than one cognitive domain. Risk factors associated with post critical illness cognitive impairment included younger age at critical illness and/or older age at follow-up, low socioeconomic status, high oxygen requirements, and use of mechanical ventilation, sedation, and pain medications. CONCLUSIONS: Identifying risk factors for poor cognitive outcomes post critical illness may help healthcare teams modify patient risk and/or provide follow-up services to improve long-term cognitive outcomes in high-risk children.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.353 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 it