The science of micronutrients in clinical practice – Report on the ESPEN symposium
Bibliographic record
Abstract
BACKGROUND & AIMS: The European Society for Clinical Nutrition and Metabolism published its first clinical guidelines for use of micronutrients (MNs) in 2022. A two-day web symposium was organized in November 2022 discussing how to apply the guidelines in clinical practice. The present paper reports the main findings of this symposium. METHODS: Current evidence was discussed, the first day being devoted to clarifying the biology underlying the guidelines, especially regarding the definition of deficiency, the impact of inflammation, and the roles in antioxidant defences and immunity. The second day focused on clinical situations with high prevalence of MN depletion and deficiency. RESULTS: The importance of the determination of MN status in patients at risk and diagnosis of deficiencies is still insufficiently perceived, considering the essential role of MNs in immune and antioxidant defences. Epidemiological data show that deficiencies of several MNs (iron, iodine, vitamin D) are a global problem that affects human health and well-being including immune responses such as to vaccination. Clinical conditions frequently associated with MN deficiencies were discussed including cancer, obesity with impact of bariatric surgery, diseases of the gastrointestinal tract, critical illness, and aging. In all these conditions, MN deficiency is associated with worsening of outcomes. The recurrent problem of shortage of MN products, but also lack of individual MN-products is a worldwide problem. CONCLUSION: Despite important progress in epidemiology and clinical nutrition, numerous gaps in practice persist. MN depletion and deficiency are frequently insufficiently searched for in clinical conditions, leading to inadequate treatment. The symposium concluded that more research and continued education are required to improve patient outcome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 | 0.030 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".