Survival and Health Care Use After Feeding Tube Placement in Children With Neurologic Impairment
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Children with neurologic impairment (NI) often undergo feeding tube placement for undernutrition or aspiration. We evaluated survival and acute health care use after tube placement in this population. METHODS: This is a population-based exposure-crossover study for which we use linked administrative data from Ontario, Canada. We identified children aged 13 months to 17 years with a diagnosis of NI undergoing primary gastrostomy or gastrojejunostomy tube placement between 1993 and 2015. We determined survival time from procedure until date of death or last clinical encounter and calculated mean weekly rates of unplanned hospital days overall and for reflux-related diagnoses, emergency department visits, and outpatient visits. Rate ratios were estimated from negative binomial generalized estimating equation models adjusting for time and age. RESULTS: Two-year survival after feeding tube placement was 87.4% (95% confidence interval [CI]: 85.2%-89.4%) and 5-year survival was 75.8% (95% CI: 72.8%-78.4%). The adjusted rate ratio comparing weekly rates of unplanned hospital days during the 2 years after versus before tube placement was 0.92 (95% CI: 0.57-1.48). Similarly, rates of reflux-related hospital days, emergency department visits, and outpatient visits were unchanged. Unplanned hospital days were stable within subgroups, although rates across subgroups varied. CONCLUSIONS: Mortality is high among children with NI after feeding tube placement. However, the stability of health care use before and after the procedure suggests that the high mortality may reflect underlying fragility rather than increased risk from nonoral feeding. Further research to inform risk stratification and prognostic accuracy is needed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".