Predictive Value of Weight Gain and Airway Obstruction in Isolated Robin Sequence
Bibliographic record
Abstract
OBJECTIVE: Treatment of airway obstruction and feeding difficulties among newborns with isolated Robin sequence is challenging. The lack of clear guidelines may lead to prolonged hospital stays and delays in treatment. Appropriate risk stratification can facilitate treatment planning. We aim to identify factors that prognosticate prolonged hospital stay in children with isolated Robin sequence. SETTING: We used a retrospective multivariate analysis of 46 patients admitted with isolated Robin sequence at the Hospital for Sick Children, in Toronto, between 2000 and 2007. During the initial 4 weeks following admission, data regarding duration of hospital stay, management of airway obstruction, respiratory rate, management of feeding difficulties, and reflux therapy were collected. RESULTS: Correlation between length of hospital stay, airway management, and weight gain during the initial 4 weeks was noted. No correlation was found between length of hospital stay and respiratory rate, supplemental oxygen requirement, or reflux therapy. CONCLUSIONS: Risk stratification is possible in children with isolated Robin sequence. Delayed weight gain in Robin sequence correlates with the degree of airway obstruction. The need for a nasopharyngeal tube and weight gain during the initial 4 weeks of life in newborns with Robin sequence reliably predict length of hospital stay. These prognosticators should contribute to parent and physician expectations, as well as assist in treatment and discharge planning.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.003 | 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".