Overview of oxidative stress and the role of micronutrients in critical illness
Bibliographic record
Abstract
Inflammation and oxidative stress represent physiological response mechanisms to different types of stimuli and injury during critical illness. Its proper regulation is fundamental to cellular and organismal survival and are paramount to outcomes and recovery from critical illness. A proper maintenance of the delicate balance between inflammation, oxidative stress, and immune response is crucial for resolution from critical illness with important implications for patient outcome. The extent of inflammation and oxidative stress under normal conditions is limited by the antioxidant defense system of the human body, whereas the antioxidant capacity is commonly significantly compromised, and serum levels of micronutrients and vitamins significantly depleted in patients who are critically ill. Hence, the provision of antioxidants and anti-inflammatory nutrients may help to reduce the extent of oxidative stress and therefore improve clinical outcomes in patients who are critically ill. As existing evidence of the beneficial effects of antioxidant supplementation in patients who are critically ill is still unclear, actual findings about the most promising anti-inflammatory and antioxidative candidates selenium, vitamin C, zinc, and vitamin D will be discussed in this narrative review. The existing evidence provided so far demonstrates that several factors need to be considered to determine the efficacy of an antioxidant supplementation strategy in patients who are critically ill and indicates the need for adequately designed multicenter prospective randomized control trials to evaluate the clinical significance of different types and doses of micronutrients and vitamins in selected groups of patients with different types of critical illness.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".