Diarrhea in the critically ill: definitions, epidemiology, risk factors and outcomes
Bibliographic record
Abstract
PURPOSE OF REVIEW: In this paper, we review the current evidence with respect to definitions, risk factors, and outcomes of diarrhea in the critically ill and highlight research gaps in the literature. RECENT FINDINGS: Definitions of diarrhea in the intensive care unit (ICU) include the World Health Organization quantified as >3 liquid bowel movements per day and the Bristol Stool Chart score of 7. Diarrhea incidence is 37.7-73.8% and varies based on definition applied. Clostridioides difficile associated diarrhea (CDAD) is uncommon with an incidence of 2.2%. Risk factors for diarrhea include total number of antibiotics, enteral nutrition, and suppository use. The composition of enteral nutrition including high osmolarity and high fiber feeds contributed to diarrhea occurrence. Opiates decrease diarrhea incidence whereas probiotics have no effect on the incidence or duration of diarrhea. Outcomes of diarrhea include increased length of stay in the ICU and hospital, however its impact on mortality is unclear. SUMMARY: Diarrhea remains a common problem in clinical practice and attention must be paid to modifiable risk factors. Further research is needed on interventions to decrease its burden.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".