Prognostic value of cystatin C in patients with acute coronary syndrome: A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Circulating cystatin C has been considered as an independent predictor of cardiovascular and all-cause mortality in the general population. The purpose of this study was to evaluate the prognostic value of baseline circulating cystatin C levels in patients with acute coronary syndrome (ACS) through meta-analysis. METHODS: Prospective studies about the relationship between the level of cystatin C and the prognosis of ACS patients were searched on PubMed, Web of science, Cochrane Library and Embase databases from the establishment of the databases to July 2020. The prognostic values included in this analysis covered all-cause mortality, major adverse cardiovascular events (MACE) and recurrent myocardial infarction. The effect index between cystatin C level and ACS risk was carried out by hazard ratio (HR). Stata 15.0 software was used for statistical analysis. The quality of the included literature was evaluated according to Newcastle-Ottawa Scale (NOS). RESULTS: A total of 10 studies were included in this meta-analysis. The results showed that high cystatin C levels significantly predicted the all-cause mortality of ACS, HR = 2.53 (95%CI: 1.72 ~ 3.72). High cystatin C level significantly predicted MACE of patients with ACS, HR = 3.24 (95%CI: 1.30 ~ 8.07). However, it had no significant predictive significance for recurrent myocardial infarction, HR = 1.71 (95%CI:0.99 ~ 2.97). CONCLUSION: Our meta-analysis showed that high cystatin C levels were significantly associated with the death risk and MACE in ACS patients. Therefore, cystatin C can be included in the risk stratification model to guide the treatment of high-risk ACS patients.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".