Relationship between blood concentration of zinc and selenium and prognosis in post-acute myocardial infarction: A protocol for systematic review and meta-analysis
Bibliographic record
Abstract
Acute Myocardial Infarction (AMI) is characterized by the presence of injury caused by an ischemic event, which leads to various complications, including Heart Failure (HF), the most severe functional stage of the heart, reducing both quality of life and life expectancy. Among the factors involved in this process, essential trace elements such as zinc and selenium stand out, as they are related to cardiovascular health and may help mitigate the harmful changes resulting from AMI. The objective of this protocol is to detail the development of two systematic reviews to gather scientific evidence on the relationship between zinc and selenium and the prognosis following AMI. This protocol was developed in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guideline and registered in the International Prospective Register of Systematic Reviews (PROSPERO) under the code CRD42024574424. Search strategies will be conducted using a combination of controlled and uncontrolled terms combined with Boolean operators, and the following databases will be used: MEDLINE/PubMed, EMBASE, LILACS, Scopus, Web of Science, Trip database, and World Wide Science. Cohort studies that evaluated zinc and selenium in the prognosis after AMI will be included. Two trained researchers will independently select articles, extract data, and assess the risk of bias and the quality of the evidence. A narrative synthesis will be performed, and the main findings will be presented in tables. If possible, a meta-analysis will also be conducted.
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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 | 0.071 | 0.122 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.020 | 0.029 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.049 | 0.005 |
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".