A Core Outcome Set for Children With Feeding Tubes and Neurologic Impairment: A Systematic Review
Bibliographic record
Abstract
CONTEXT: Uncertainty exists about the impacts of feeding tubes on neurologically impaired children. Core outcome sets (COS) standardize outcome selection, definition, measurement, and reporting. OBJECTIVE: To synthesize an evidence base of qualitative data on all outcomes selected and/or reported for neurologically impaired children 0 to 18 years living with gastrostomy/gastrojejunostomy tubes. DATA SOURCES: Medline, Embase, and Cochrane Register databases searched from inception to March 2014. STUDY SELECTION: Articles examining health outcomes of neurologically impaired children living with feeding tubes. DATA EXTRACTION: Outcomes were extracted and assigned to modified Outcome Measures in Rheumatology 2.0 Filter core areas; death, life impact, resource use, pathophysiological manifestations, growth and development. RESULTS: We identified 120 unique outcomes with substantial heterogeneity in definition, measurement, and frequency of selection and/or reporting: "pathophysiological manifestation" outcomes (n = 83) in 79% of articles; "growth and development" outcomes (n = 13) in 55% of articles; "death" outcomes (n = 3) and "life impact" outcomes (n = 17) in 39% and 37% of articles, respectively; "resource use" outcomes (n = 4) in 14%. Weight (50%), gastroesophageal reflux (35%), and site infection (25%) were the most frequently reported outcomes. LIMITATIONS: We were unable to investigate effect size of outcomes because quantitative data were not collected. CONCLUSIONS: The paucity of outcomes assessed for life impact, resource use and death hinders meaningful evidence synthesis. A COS could help overcome the current wide heterogeneity in selection and definition. These results will form the basis of a consensus process to produce a final COS.
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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 | 0.038 | 0.184 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".