A52 OVERNUTRITION IN TREATED CELIAC DISEASE (CED) PATIENTS: THE NEED FOR PERSONALIZED NUTRITIONAL ASSESSMENT TO MANAGE THE METABOLIC SEQUELAE OF A GLUTEN-FREE DIET (GFD)
Bibliographic record
Abstract
Abstract Background Overnutrition, leading to overweight and obesity, is increasingly prevalent in celiac disease (CeD). A nutritionally imbalanced diet may contribute to overnutrition and the development of Metabolic Syndrome (MS) and Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD). Aims To investigate the factors contributing to the metabolic shift in treated CeD. Methods We enrolled patients with biopsy-proven CeD on a GFD and non-CeD (Inflammatory Bowel Disease and Irritable Bowel Syndrome) attending a tertiary care center adult Nutrition Assessment Clinic. We collected data on nutritional assessment (SGA), energy requirements determined by resting energy expenditure (REE: indirect calorimetry, QNRG, COSMED, US) and activity factor (IPAQ), body composition (3D scanner; Styku CA, US) and obesity risk (EOSS: Edmonton Obesity Staging System) to assess risk based on metabolic comorbidities such as diabetes, fatty liver, and cardiovascular disease. SPSS (version 22, US) was used for statistical analysis. Data are reported as median (IQR); Mann-U-Whitney was used for comparison between groups. Results From November 2021 to October 2024, 124 CeD [Female: 76%; Age: 45 (27) yr; time since diagnosis: 5 (6) yr] and 96 non-CeD [F:74%; 48 (27) yr] patients were enrolled. Nutritional assessment identified undernutrition (BMI<19) in 8% vs 20%, overweight (BMI 26-30) in 24% vs 14%, and obesity (BMI>30) in 49% vs 34% of CeD vs non-CeD (p<0.001). REE adjusted for weight was significantly lower in obese CeD compared with non-obese CeD [17 (3) vs 22 (4) kcal/kg/day; p<0.001]. Fat mass was significantly greater [19 (7) vs 40 (10) kg; p<0.001], and fat-free mass was significantly reduced [FFM:43 (11) vs 54 (10) kg; p=0.005] in CeD with overweight/obesity compared to normal BMI. FFM was positively correlated with REE (r=0.71; p<0.001). Metabolic comorbidities occurred in 26% of obese-CeD patients. MASLD was more frequent in CeD with overweight and obesity compared to normal BMI (81% vs 43%; p=0.04). Conclusions The high rate of overnutrition and reduced muscle mass in treated CeD patients is concerning, as this is associated with metabolic comorbidities. Personalized nutrition assessment with accurate measurements is crucial for nutritional guidance and will likely improve health in CeD. Funding Agencies:
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".