A practical approach to nutritional screening and assessment in cirrhosis
Bibliographic record
Abstract
Malnutrition is one of the most common complications of cirrhosis, associated with an increased risk of morbidity and mortality. As a potentially modifiable condition, it is of particular importance to identify malnourished patients so that nutritional therapy can be instituted. Nutrition screening and assessment are infrequently performed in patients with cirrhosis. The reasons for this are multifactorial, including the absence of a validated "rapid" screening tool, multiple definitions of what constitutes malnutrition, and challenges with interpreting body composition and laboratory results in the setting of volume overload and liver dysfunction. This article summarizes the clinically relevant evidence and presents key issues, tools, and clinical options that are applicable to patients with cirrhosis. The definition, etiology, and clinically relevant outcomes associated with malnutrition are reviewed. Rapid nutritional screening is differentiated from more detailed nutritional assessment. Nutritional assessment in special populations, including women and the obese, and the role of inflammation are discussed. Multicenter studies using a common nutritional screening/assessment strategy are the next steps to fast-track adoption and implementation of nutrition-related evaluations into routine clinical practice. (Hepatology 2017;65:1044-1057).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 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".