Cancer antigen-125 and outcomes in acute heart failure: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Carbohydrate antigen-125 (CA125) is an ovarian cancer marker, but recent work has examined its role in risk stratification in heart failure. A recent meta-analysis examined its prognostic value in heart failure generally. However, there has been no systematic evaluation of its role specifically in acute heart failure (AHF). Methods PubMed and EMBASE databases were searched until 11 May 2018 for studies that evaluated the prognostic value of CA125 in AHF. Results A total of 129 and 179 entries were retrieved from PubMed and EMBASE. Sixteen studies (15 cohort studies, 1 randomised trial) including 8401 subjects with AHF (mean age 71 years old, 52% male, mean follow-up 13 months, range of patients 525.1±598.2) were included. High CA125 levels were associated with a 68% increase in all-cause mortality (8 studies, HRs: 1.68, 95% CI 1.36 to 2.07; p<0.0001; I 2 : 74%) and 77% increase in heart failure-related readmissions (5 studies, HRs: 1.77, 95% CI 1.22 to 2.59; p<0.01; I 2 : 73%). CA125 levels were higher in patients with fluid overload symptoms and signs compared with those without them, with a mean difference of 54.8 U/mL (5 studies, SE: 13.2 U/mL; p<0.0001; I 2 : 78%). Conclusion Our meta-analysis found that high CA125 levels are associated with AHF symptoms, heart failure-related hospital readmissions and all-cause mortality. Therefore, CA125 emerges as a useful risk stratification tool for identifying high-risk patients with more severe fluid overload, as well as for monitoring following an AHF episode.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.027 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".