Nationwide prevalence and prognostic significance of clinically diagnosable protein-calorie malnutrition in hospitalized inflammatory bowel disease patients
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD) patients are at increased risk of protein-calorie malnutrition. We sought to determine the prevalence of clinically diagnosable malnutrition among those hospitalized for IBD throughout the United States and whether this malnutrition influenced health outcomes. METHODS: We queried the Nationwide Inpatient Sample between 1998 and 2004 to identify admissions for Crohn's disease (CD) or ulcerative colitis (UC) and a representative sample of non-IBD discharges. We assessed the prevalence and predictors of malnutrition and its association with in-hospital mortality and resource utilization. RESULTS: The prevalence of malnutrition was greater in CD and UC patients than in non-IBD patients (6.1% and 7.2% versus 1.8%, P < 0.0001). The adjusted odds ratio for malnutrition among IBD admissions compared with non-IBD admissions was 5.57 [95% confidence interval (CI): 5.29-5.86]. More IBD discharges than non-IBD discharges with malnutrition received parenteral nutrition (26% versus 6%, P < 0.0001). There was increased likelihood of malnutrition among those with fistulizing CD (OR 1.65; 95% CI: 1.50-1.82) and among those who had undergone bowel resection (OR 1.37; 95% CI: 1.27-1.48). Malnutrition was associated with increased in-hospital mortality 3.49 (95% CI: 2.89-4.23), length of stay (11.9 days versus 5.8 days, P < 0.00001), and total charges ($45,188 versus $20,295, P < 0.0001). CONCLUSIONS: Clinically apparent malnutrition is more frequent among IBD admissions than among non-IBD admissions. Its association with greater mortality and resource utilization may reflect more severe underlying disease that can lead to both malnutrition and worse outcomes. Nonetheless, diagnosable malnutrition may serve as a clinical marker of poor IBD prognosis in hospitalized patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".