Pharmaconutrition With Selenium in Critically Ill Patients
Bibliographic record
Abstract
Selenium is a component of selenoproteins with antioxidant, anti-inflammatory, and immunomodulatory properties. Systemic inflammatory response syndrome (SIRS), multiorgan dysfunction (MOD), and multiorgan failure (MOF) are associated with an early reduction in plasma selenium and glutathione peroxidase activity (GPx), and both parameters correlate inversely with the severity of illness and outcomes. Several randomized clinical trials (RCTs) evaluated selenium therapy as monotherapy or in antioxidant cocktails in intensive care unit (ICU) patient populations, and more recently several meta-analyses suggested benefits with selenium therapy in the most seriously ill patients. However, the largest RCT on pharmaconutrition with glutamine and antioxidants, the REducing Deaths due to Oxidative Stress (REDOXS) Study, was unable to find any improvement in clinical outcomes with antioxidants provided by the enteral and parenteral route and suggested harm in patients with renal dysfunction. Subsequently, the MetaPlus study demonstrated increased mortality in medical patients when provided extra glutamine and selenium enterally. The treatment effect of selenium may be dependent on the dose, the route of administration, and whether administered with other nutrients and the patient population studied. Currently, there are few small studies evaluating the pharmacokinetic profile of intravenous (IV) selenium in SIRS, and therefore more data are necessary, particularly in patients with MOD, including those with renal dysfunction. According to current knowledge, high-dose pentahydrate sodium selenite could be given as an IV bolus injection (1000-2000 µg), which causes transient pro-oxidant, cytotoxic, and anti-inflammatory effects, and then followed by a continuous infusion of 1000-1600 µg/d for up to 10-14 days. Nonetheless, the optimum dose and efficacy still remain controversial and need to be definitively established.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".