The Changes That Occur in the Immune System During Immune Activation in Patients With Prediabetes From All Ethnicities, Aged 25-45 Years: Protocol for a Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Prediabetes is an asymptomatic, intermediate state between normoglycemia and the onset of type 2 diabetes mellitus. Recent reports indicate that during prediabetes, there are subclinical changes to immune cells and inflammatory markers. Therefore, this systematic review will provide a synthesis of the available data on the changes in the concentration of immune cells and selective inflammatory markers. It will also give evidence of a demographic impact on changes or complications in the prediabetes state. OBJECTIVE: The objectives of this study are to create a protocol that will be used to analyze the collected data of previously published research based on immune cells such as neutrophils, lymphocytes, monocytes, eosinophils, and basophils, as well as inflammatory markers such as C-reactive protein, tumor necrosis factor-alpha, interleukin-6, P-selectin, cluster of differentiation 40 ligand, and fibrinogen. Additionally, an impact of demographics will be determined using the previously published data collected. METHODS: This protocol was prepared through adhering to the PRISMA (Preferred Reporting Items for Systemic Reviews and Meta-Analysis) 2015 guidelines for reporting protocols. Published clinical studies that involve observational (cross-sectional, comparative cross-sectional, case-control, or cohort) study designs that include normal or nondiabetic and prediabetes reports will be used in this systematic review and meta-analysis. This will be accomplished by using clinical Medical Subject Headings to search on MEDLINE, Cochrane library, and African Journal Online. Reviewers (NCM, AMS, and AK) will screen all the results and select the studies that meet the eligibility criteria. Downs and Black Checklist will be used to check the risk of bias, and then a Review Manager v5.4 forest plot will be used for meta-analysis. Additionally, the forest plot will also be used for sensitivity analysis. The strength of evidence will then be assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. RESULTS: Since July 5, 2020, there are no participants recruited. Publicly available data will be used in the review and will be collected after this protocol publication. No ethics approval is required as no subjects will be used, and analysis will be based on reported data. Authors will be contacted if there was a misunderstanding related to reading their reported data. CONCLUSIONS: The findings will clarify changes that might be observed in a study of interest based in the eThekwini district in South Africa. TRIAL REGISTRATION: International Prospective Registry of Systematic Reviews (PROSPERO) CRD42020184828; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=184828. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/31619.
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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 | 0.055 | 0.088 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.018 | 0.025 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.040 | 0.004 |
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".