Clinical characteristics of children with severe neurologic impairment: A scoping review
Bibliographic record
Abstract
OBJECTIVE: The aim of this study is to extrapolate the clinical features of children with severe neurologic impairment (SNI) based on the functional characteristics and comorbidities described in published studies. METHODS: Four databases were searched. We included studies that describe clinical features of a group of children with SNI (≥20 subjects <19 years of age with >1 neurologic diagnosis and severe functional limitation) using data from caregivers, medical charts, or prospective collection. Studies that were not written in English were excluded. We extracted data about functional characteristics, comorbidities, and study topics. RESULTS: We included 102 studies, spanning 5 continents over 43 years, using 41 distinct terms for SNI. The terms SNI and neurologic impairment (NI) were used in 59 studies (58%). Most studies (n = 81, 79%) described ≥3 types of functional characteristics, such as technology assistance and motor impairment. Studies noted 59 comorbidities and surgeries across 10 categories. The most common comorbidities were related to feeding, nutrition, and the gastrointestinal system, which were described in 79 studies (77%). Most comorbidities (76%) were noted in <10 studies. Studies investigated seven clinical topics, with "Gastrointestinal reflux and feeding tubes" as the most common research focus (n = 57, 56%). The next most common topic, "Aspiration and respiratory issues," included 13 studies (13%). Most studies (n = 54, 53%) were retrospective cohorts or case series; there were no clinical trials. CONCLUSIONS: Despite the breadth of described comorbidities, studies focused on a narrow set of clinical topics. Further research is required to understand the prevalence, clinical impact, and interaction of the multiple comorbidities that are common in children with SNI.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".