Peripheral Levels of the Brain-Derived Neurotrophic Factor in Coronary Artery Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Among its functions, brain-derived neurotrophic factor (BDNF) regulates endothelial and macrophage activation, possibly playing a role in atherosclerotic plaque pathophysiology. Given contradicting reports, this study sought to investigate whether blood levels of BDNF differed between patients with coronary heart disease (CHD) and controls. Methods: We explored PubMed, Embase, Web of Science, and Cochrane Library for studies comparing BDNF blood levels in patients with CHD and controls. Random-effect meta-analysis was conducted to calculate the standardized mean differences (SMD) and 95% confidence intervals (CI). The Newcastle-Ottawa scale was used to evaluate the quality of included articles, and statistical analyses were conducted using R version 4.0.4. Results: The final analysis comprised 12 investigations covering 1422 CHD cases and 929 controls with mean ages of 59.66±13.56 and 53.78±13.61 years, respectively. The initial analyses revealed a tendency toward low levels of BDNF in the CHD group compared with the control group (SMD= -0.41; 95% CI, -1.12 to 0.30; P=0.26). After the removal of outliers, the difference achieved statistical difference (SMD= -0.56; 95% CI, -0.93 to -0.19; P<0.01). Subgroup analysis demonstrated no significant difference between serum and plasma BDNF levels (P=0.54); however, subgroup analyses of studies investigating plasma BDNF showed that patients with CHD had significantly lower BDNF levels. Conclusion: Serum and plasma BDNF concentrations were considerably lower in patients with CHD than in healthy controls. Further studies of higher quality are required on the potential role of BDNF as a biomarker of CHD pathophysiology and severity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".