Constipation Is More Frequent Than Diarrhea in Patients Fed Exclusively by Enteral Nutrition
Bibliographic record
Abstract
BACKGROUND: Digestive complications in enteral nutrition (EN) can negatively affect the nutrition clinical outcome of hospitalized patients. Diarrhea and constipation are intestinal motility disorders associated with pharmacotherapy, hydration, nutrition status, and age. The aim of this study was to analyze the frequency of these intestinal motility disorders in patients receiving EN and assess risk factors associated with diarrhea and constipation in hospitalized patients receiving exclusive EN therapy in a general hospital. MATERIALS AND METHODS: The authors performed a sequential and observational study of 110 hospitalized adult patients fed exclusively by EN through a feeding tube. Patients were categorized according to the type of intestinal transit disorder as follows: group D (diarrhea, 3 or more watery evacuations in 24 hours), group C (constipation, less than 1 evacuation during 3 days), and group N (absence of diarrhea or constipation). All prescription drugs were recorded, and patients were analyzed according to the type and amount of medication received. The authors also investigated the presence of fiber in the enteral formula. RESULTS: Patients classified in group C represented 70% of the study population; group D comprised 13%, and group N represented 17%. There was an association between group C and orotracheal intubation as the indication for EN (P < .001). Enteral formula without fiber was associated with constipation (logistic regression analysis: P < .001). CONCLUSION: Constipation is more frequent than diarrhea in patients fed exclusively by EN. Enteral diet with fiber may protect against medication-associated intestinal motility disorders. The addition of prokinetic drugs seems to be useful in preventing constipation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".