Xanthan‐ and Rice Cereal‐Based Thickeners in Infants
Bibliographic record
Abstract
Some infants aspirate thin liquids and must be fed thickened liquids in order to protect the lungs. However, thickeners have not been fully studied for safety. Xanthan-based thickeners have been implicated in the development of necrotizing enterocolitis and rice cereal-based thickeners have been associated with constipation and excessive weight gain. The aim of this study was to compare rates of adverse events between both thickeners. Methods: Single-center retrospective chart review conducted at a tertiary pediatric care center between January 2013 and July 2017. All infants deemed unsafe for oral feeding and treated with xanthan- or rice cereal-based milk thickeners were included. Data were extracted from the medical records and patients categorized according to the type of thickener. Primary outcome was the occurrence of diarrhea, constipation, overweight, and obesity at 3-6 and 6-12 months after thickener initiation. Appropriate statistical tests were used. In addition, an e-mail was sent to 14 level III Canadian Pediatric hospitals inquiring about their practice. Results: We identified 53 patients to be included in the study; 20 used xanthan-based- and 33 used rice cereal-based milk thickeners. Rates of diarrhea, constipation, overweight, and obesity at 3-6 and 6-12 months after initiation were not different between thickeners. Important variability concerning thickening practices was reported by the 8 centers that responded. Conclusions: In infants treated with milk thickeners, xanthan-based or rice cereal-based thickeners may have similar safety profiles that require further investigation including a larger number of patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".