Screening and therapy for malnutrition and related gastro-intestinal disorders in systemic sclerosis: recommendations of a North American expert panel.
Bibliographic record
Abstract
OBJECTIVES: To develop a set of recommendations for clinicians caring for patients with systemic sclerosis (SSc) to guide their approach to the patient with malnutrition and possible malabsorption. METHODS: The Canadian Scleroderma Research Group convened a meeting of experts in the areas of nutrition, speech pathology, oral health in SSc, SSc and gastroenterology to discuss the nutrition-GI paradigm in SSc. This meeting generated a set of recommendations based on expert opinion. RESULTS: Physicians should screen ALL patients with SSc for malnutrition. The physician should ask a series of questions that pertain to GI involvement. Patients who screen positive for malnutrition should be referred to a dietitian and gastroenterologist. Referral to a patient support group should be considered and if screening reveals oral health problems, referral to a dentist, preferably with expertise in treating patients with SSc, should be done. All SSc patients should weigh themselves monthly and report any sudden significant changes in weight. They should be assessed by a rheumatologist once a year for signs of malnutrition. CONCLUSIONS: Malnutrition may be common in SSc and a multidisciplinary approach is important.
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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 | 0.019 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".