Antecedent Predictors of Feeding Outcomes in Premature Infants With Protracted Mechanical Ventilation
Bibliographic record
Abstract
OBJECTIVES: The aim of the present study was to define risk factors associated with gastrostomy in premature infants receiving protracted mechanical ventilation (≥30 days). METHODS: Retrospective data collected on 170 preterm neonates (birth weight <1500 g) who received uninterrupted mechanical ventilation for ≥30 days were analyzed with logistic regression methods to predict the association of gastrostomy with cardiorespiratory, infectious, and neurological morbidities. RESULTS: A total of 32 of 170 infants had gastrostomy tubes. Including all of the covariates in 1 model, duration of cumulative ventilation (P < 0.001) and uninterrupted ventilation (P < 0.001), and ventriculoperitoneal shunt (P = 0.02) were significant predictors, whereas sepsis, intraventrical hemorrhage grade III or IV, and patent ductus arteriosus ligation were not. Respiratory severity score (mean airway pressure × fraction of inspired oxygen) calculated at 30 days of life was also a significant predictor (P = 0.01). CONCLUSIONS: In infants with protracted mechanical ventilation, the degree of respiratory support at 1 month of age, prolonged respiratory morbidity, and neuropathology are the significant predictors for gastrostomy.
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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 | 0.001 |
| 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".