Nutritional Status and Its Detection in Patients with Inflammatory Bowel Diseases
Bibliographic record
Abstract
Malnutrition is an important issue in patients with inflammatory bowel diseases (IBDs) including Crohn's disease (CD) and ulcerative colitis (UC). It is caused by altered digestion and absorption within the small bowel, inadequate food intake, and drug-nutrient interactions in patients. Malnutrition is an essential problem because it is related to an increased risk of infections and poor prognosis in patients. It is known that malnutrition is also related to an increased risk of postsurgery complications in IBD patients. Basic nutritional screening involves anthropometric parameters with body mass index (BMI) and others (fat mass, waist-to-hip ratio, muscle strength), medical history concerning weight loss, and biochemical parameters (including the Prognostic Nutritional Index). Besides standard nutritional screening tools, including the Subjective Global Assessment (SGA), Nutritional Risk Score 2002 (NRS 2002), and Malnutrition Universal Screening Tool (MUST), specific nutritional screening tools are used in IBD patients, such as the Saskatchewan Inflammatory Bowel Disease-Nutrition Risk Tool (SaskIBD-NR Tool and IBD-specific Nutritional Screening Tool). There is a higher risk of nutrient deficiencies (including iron, zinc, magnesium) and vitamin deficiencies (including folic acid, vitamin B12 and D) in IBD patients. Therefore, regular evaluation of nutritional status is important in IBD patients because many of them are undernourished. An association between plasma ghrelin and leptin and nutritional status in IBD patients has been observed. According to some authors, anti-tumor necrosis factor (anti-TNFα) therapy (infliximab) can improve nutritional status in IBD patients. On the other hand, improvement in nutritional status may increase the response rate to infliximab therapy in CD patients. Optimization of nutritional parameters is necessary to improve results of conservative and surgical treatment and to prevent postoperative complications in patients with IBDs. This review presents basic nutritional screening tools, anthropometric and laboratory parameters, dietary risk factors for IBDs, common nutrient deficiencies, associations between anti-TNFα therapy and nutritional status, selected features regarding the influence of nutritional status, and surgical outcome in IBD patients.
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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 | 0.001 | 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 | 0.000 |
| 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".