Are Low Brain Derived Neurotrophic Factor Levels in the Blood a Biological Marker of Suicide Risk in Psychiatric Patients? A Systematic Review
Bibliographic record
Abstract
The functional polymorphism of the brain-derived neurotrophic factor (BDNF) in relation to suicidal behaviour has attracted a great deal of interest in recent research. Although genetic studies have indicated BDNF as a candidate gene in suicidal behaviour, no clear evidence exists for the role of BDNF levels in the blood of patients with mental illness who are at risk of suicide. Considering the ability of BDNF to cross the blood-brain barrier, the aim of the present study was to review evidence for a correlation between blood BDNF levels and suicidal behaviour among patients with psychiatric disorders. The systematic review that was performed (1966 - 2012) identified 64 studies as potential candidates for inclusion. After scrutiny, only seven studies appeared to focus on BDNF levels in plasma, serum and platelets. Studies consistently showed a significant decrease in BDNF levels among patients with previous suicide attempts, with the exception of one study, which included patients with schizophrenia. No significant differences were found between BDNF levels, gender and lethality of suicide attempts. Further evidence is required for which blood sample type to use when examining BDNF protein levels in terms of suicidal behaviour in mental illness sufferers, and more focus should be given to a potential blood BDNF threshold among patients at suicide risk. doi: http://dx.doi.org/10.4021/jnr171e
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".