A Systematic Review of Feeding Interventions for Infants with Cleft Palate
Bibliographic record
Abstract
OBJECTIVE: Various devices and techniques have been proposed to reduce feeding difficulties experienced by infants with cleft palate. The aim of this review is to identify and assess the scope and quality of evidence for these interventions. METHODS: A systematic review of published literature evaluating feeding interventions for infants with cleft palate (with or without cleft lip) from database inception to 2021 was conducted using Preferred Reporting Items for Systematic Reviews guidelines. Quality appraisal of included studies was conducted using a methodological index for nonrandomized studies, Cochrane, or a measurement tool to assess systematic reviews 2 instruments, according to study type. RESULTS: Fourteen studies met inclusion criteria, with the majority (71%) of studies consisting of second-level evidence. Included interventions were specialty bottles (21%), alternative feeding delivery systems (14%), obturators (14%), and educational programs (14%). Specialty bottles and palatal obturators did not appear to offer any substantial growth advantages compared to traditional bottles or no intervention, respectively. Designated education programs for the mothers of infants with clefts had a positive impact on infant growth. CONCLUSIONS: Overall evidence evaluating feeding interventions for infants with cleft palate was moderate to low. While it does not appear that specialized feeding delivery systems or palatal obturators significantly improve growth in infants with clefts compared to children without cleft conditions, education programs do appear to be beneficial.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".