Enteral Nutrition With an Enteral Formula Containing Egg Yolk Lecithin After Percutaneous Endoscopic Gastrostomy: A Case Series
Bibliographic record
Abstract
The occurrence of diarrhea at the beginning of enteral nutrition complicates the continuation of enteral nutrition. Recently, studies in Japan indicated that diarrhea could be improved by changing the enteral formula to one that is emulsified with egg yolk lecithin. In this study, we administered the enteral formula K-2S plus, which is emulsified with egg yolk lecithin, to 15 patients (four men and 11 women; mean age, 79.9 ± 2.0 years) after they had undergone a percutaneous endoscopic gastrostomy (PEG) to prevent the occurrence of diarrhea related to enteral nutrition. Two days after the PEG, the patients would receive 200 mL K-2S plus intermittently three times daily; thereafter, the amount of K-2S plus was increased according to the patient's condition. The administration rate was scheduled as 200 mL/h when 200 mL were administered at one time. For ≥ 300 mL, the scheduled administration rate was 300 mL/h. When we administered K-2S plus at the beginning of enteral nutrition after the PEG, the dose of the enteral formula could be increased without any occurrence of diarrhea or vomiting. Five patients had received intravenous nutrition before the PEG; thus, we were concerned about diarrhea in these patients. In conclusion, an enteral formula emulsified with egg yolk lecithin may be safely used at the time of enteral nutrition initiation without causing diarrhea.
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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".