Understanding the use and tolerance of a pediatric and an adult commercial blenderized enteral formula through real‐world data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Home enteral nutrition (HEN) is frequently prescribed to individuals who cannot consume adequate food orally. Commercial blenderized enteral formulas (CBEF) containing real-food ingredients are becoming more popular and more widely available; however, the demographics of patients receiving these formulas have rarely been evaluated, and little data are available on patient tolerance in the community. METHODS: US claims data were obtained for children and adolescents/adults who used the CBEF of interest as the sole source of nutrition via enteral feeding tube in the community setting following discharge from acute care. Demographics, concomitant medications, clinical diagnoses, and Charlson Comorbidity Index scores were tabulated using descriptive statistics. Gastrointestinal (GI) symptoms before and after hospital discharge were compared using significance tests. RESULTS: The study included 231 participants (180 children, 51 adolescents/adults). CBEFs were prescribed to patients with a variety of diagnoses, of which the most common were digestive and respiratory disorders. Children experienced significantly lower rates of diarrhea, nausea, vomiting, constipation, and abdominal distension in the weeks following hospital discharge compared with the baseline (all P < 0.001). Adolescents/adults experienced significantly lower rates of constipation, nausea, and vomiting (all P < 0.05). Neither group increased their usage of GI medications following hospital discharge. CONCLUSION: These CBEFs, based on real-food ingredients, were prescribed to diverse patients in the community and were well tolerated. These formulas offer an alternative to standard polymeric formulas and an alternative or adjunct to homemade blenderized formulas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it