Pro-inflammatory cytokines level in depressed patients with suicidal behaviour: a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: The study assesses proinflammatory factors in major depressive disorder (MDD) patients with and without suicidal behaviors, and healthy controls, to identify potential biomarkers for suicidal behaviors and prevention strategies. METHODS: We conducted a systematic review, which we have registered in Prospero (#CRD42024547764), and searched through five databases until March 2024. We included observational studies in English that reported on depressed patients with and without suicidal behaviors, as well as healthy controls, and measured the levels of pro-inflammatory cytokines. The Newcastle- Ottawa Scale was used for quality evaluation of the studies and the main analysis was performed using Stata 17. RESULTS: One systematic review resulted in 4,369 articles but only 24 were selected for the review. The meta-analysis showed depressed patients with suicidal behaviors had significantly higher interleukin (IL)-6 levels compared to the control group with a standardized mean difference (SMD) of 1.26 [0.07, 2.45]; I² = 98.81%. There was no significant difference noted between the depressed patients suffering from suicidal behaviors and those not suffering (SMD 0.42 [-0.58, 1.42]; I² = 98.50%). There is no significant difference between the groups in the levels of tumor necrosis factor-alpha (TNF-α) and IL-10. Further analysis of IL-4, IL-2, IL-1β, IF-γ, and TGF-β1 also indicated no significant group differences. CONCLUSION: The review found no significant cytokine differences (including IFN-γ, IL-1β, IL-2, IL-4, IL-8, IL-10, TGF-β1, TNF-α) between depressed individuals with or without suicidal ideation and controls. Variations likely reflect methodological differences, highlighting the need for standardized, longitudinal research.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.030 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".