Association of Carbohydrate Antigen 125 on the Response to Dapagliflozin in Patients With Heart Failure
Bibliographic record
Abstract
BACKGROUND: Elevated circulating carbohydrate antigen 125 (CA125) is a marker of congestion and a predictor of outcomes in acute heart failure (HF). Less is known about CA125 in chronic ambulatory HF with reduced ejection fraction. OBJECTIVES: This study examined the association between baseline CA125 (and changes in CA125) and outcomes in patients with HF with reduced ejection fraction in the DAPA-HF (Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure; NCT03036124) trial and its relationship with the effect of dapagliflozin. METHODS: The primary outcome was a composite of a first episode of worsening HF or cardiovascular death. CA125 was measured at baseline and 12 months following randomization. RESULTS: Median baseline CA125 was 13.04 U/mL (IQR: 8.78-21.13 U/mL) in 3,123 of 4,774 patients with available data. Compared with CA125 ≤35 U/mL (upper limit of normal), patients with CA125 >35 U/mL were at a higher risk of the primary outcome (adjusted HR: 1.59; 95% CI: 1.29-1.96). The adjusted risks of the primary outcome relative to quartile 1 (Q1) (≤8.78 U/mL) were as follow: Q2, 8.79-13.04 U/mL (HR: 0.94; 95% CI: 0.71-1.24); Q3, 13.05-21.13 U/mL (HR: 1.22; 95% CI: 0.94-1.59); Q4, ≥21.14 U/mL (HR: 1.63; 95% CI: 1.28-2.09). The beneficial effect of dapagliflozin compared with placebo on the primary outcome was consistent whether CA125 was analyzed in quartiles (interaction P = 0.13) or as a continuous variable (interaction P = 0.75). The placebo-corrected relative change in CA125 at 12 months was -5.2% (95% CI: -10.6% to 0.5%; P = 0.07). CONCLUSIONS: In DAPA-HF, elevated CA125 levels were an independent predictor of the risk of worsening HF or cardiovascular death. Dapagliflozin reduced the risk of worsening HF or cardiovascular death regardless of baseline CA125.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".