Association between HTR2C gene variants and suicidal behaviour: a protocol for the systematic review and meta-analysis of genetic studies
Bibliographic record
Abstract
INTRODUCTION: Suicide is an important public health problem and one of the most common causes of death throughout the world. Suicidal behaviour is complex, and its causes are multifactorial. Case-control studies have reported an association between an alteration of the serotonin system and suicidal behaviour. Recently, it has been suggested that the 5-HTRC2 serotonin receptor gene is involved in the pathogenesis of suicidal behaviour. METHODS AND ANALYSIS: To evaluate the role of the 5-HTR2C gene in suicidal behaviour, we will perform a systematic review and a meta-analysis of worldwide reports that have investigated the association between the serotonin system and suicidal behaviour. This analysis will be reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. Studies deemed fit for inclusion in the systematic review will be scored for methodological quality using the Newcastle-Ottawa Assessment Scale (NOS). The inclusion criteria will be to present independent data, to be case-control studies and to be published in journal peer reviews. To generate more accurate analyses, we will grade the reports using the GRADES scale procedures. ETHICS AND DISSEMINATION: This study will describe the association between the HTR2C gene and suicidal behaviour. The results will be reported in a peer-reviewed publication and in scientific presentations in Mexico and throughout the world. TRIAL REGISTRATION NUMBER: PROSPERO CRD42014009213.
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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 | 0.111 | 0.154 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.021 | 0.023 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.064 | 0.008 |
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".