Prognostic Value of Fibrinogen in Acute Coronary Syndrome: A Meta-Analysis
Bibliographic record
Abstract
Background: Acute coronary syndrome (ACS) is one of the leading causes of cardiovascular mortality worldwide. Fibrinogen, a key mediator of coagulation and inflammation, remains controversial in its prognostic value. This meta-analysis aims to evaluate the predictive role of fibrinogen in ACS patient outcomes. Methods: Following PRISMA guidelines, we systematically searched PubMed, Embase, and other databases (from inception to November 2024) for cohort or case-control studies assessing the association between fibrinogen and ACS outcomes (all-cause mortality/major adverse cardiovascular events [1]). Study quality was evaluated using the Newcastle-Ottawa Scale (NOS), and pooled effect sizes were calculated using random- or fixed-effects models. Subgroup and sensitivity analyses were performed. Results: Nine studies (12,714 patients) were included. Elevated fibrinogen levels significantly increased the risk of all-cause mortality (HR = 1.51, 95% CI: 1.27-1.81, p < 0.001), but no significant association was found with MACE (HR = 3.00, 95% CI: 0.96-9.39, p > 0.05). Subgroup analysis suggested regional differences as a source of heterogeneity. Conclusion: Fibrinogen may serve as an independent predictor of all-cause mortality in ACS patients, but its prognostic value for MACE requires further investigation. Future studies should explore its potential in clinical risk stratification.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".