Zinc Supplementation in Critically Ill Patients: A Key Pharmaconutrient?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of the present paper is to provide a rationale for zinc supplementation as a potential therapeutic agent in critically ill patients by describing its role in health and disease, conducting a systematic review of current randomized trials in critical care, considering optimum route and dose of administration, and making recommendations for future research. Normal zinc homeostasis is required for a functional immune system, adequate antioxidant capacity, glucose homeostasis, and wound healing. In addition, zinc is a required cofactor for many enzymes, transcription factors, and replication factors. In non-critically ill patients, zinc supplementation has been associated with an improvement in markers of immune function. In critically ill patients, only 4 randomized trials have examined the effect of zinc supplementation on clinical outcomes. When all 4 studies were aggregated, zinc supplementation was associated with a nonsignificant reduction in mortality (relative risk = 0.63, 95% confidence intervals 0.25-1.59, P = .33) and length of stay in intensive care (-0.35 days, -0.85 to 0.15; P = .17). Thus, because of the paucity of clinical data, there is inadequate evidence to recommend the routine use of high-dose zinc supplementation in the critically ill. A first step would be to determine the optimal dose that has a maximal positive effect on underlying inflammatory, immunologic, and metabolic processes yet is safe and tolerated by critically ill patients. Subsequently, large, rigorously designed, randomized trials are required to elucidate the efficacy of such doses of zinc supplementation in this patient population.
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.
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 | 0.001 |
| Open science | 0.000 | 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 it