The Effect of Single Nucleotide Polymorphisms on Depression in Combination With Coronary Diseases: Protocol for a Systematic Review and Meta-analysis
Bibliographic record
Abstract
Abstract Background: Depression and coronary heart disease (CHD) have common risk mechanisms. Common single nucleotide polymorphisms (SNPs) may be associated with the risk of depression combined with coronary heart disease. Methods: This protocol was designed according to the PRISMA-P guidelines. CENTRAL in the Cochrane Library, MEDLINE Ovid, Embase Ovid, Web of Science, CNKI, CQVIP, SinoMed, Wanfang Data, and ChiCTR will be systematically searched. We will include case-control studies and cohort studies investigating the relationship between gene SNPs and depression and coronary heart disease comorbidities. The Newcastle-Ottawa Scale (NOS) will be used to assess the risk of bias. When measuring dichotomous outcomes, we will use the risk ratio (RR) and 95% confidence interval (95%CIs) in a cohort study and use the odds ratio (OR) and 95% confidence interval (95%CIs) in a case-control study. Five genetic models (allele model, homozygous model, heterozygous model, dominant model, and recessive model) will be evaluated for each included study. Subgroup analysis by ethnicity will be performed. If necessary, post hoc analysis will be made according to different types.Discussion: The purpose of this meta-analysis is to comprehensively study the current evidence and assess the association between single nucleotide polymorphisms and susceptibility of depression in combination with coronary heart disease.Systematic review registration: This protocol was prospectively registered in the PROSPERO (registration number CRD42021229371).
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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 | 0.049 | 0.086 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.023 | 0.024 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.076 | 0.007 |
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".