Identification of Serum Soluble ST2 Receptor as a Novel Heart Failure Biomarker
Bibliographic record
Abstract
BACKGROUND: Using genomic technology, we previously identified an interleukin-1 receptor family member, ST2, as a gene markedly induced by mechanical strain in cardiac myocytes. The soluble receptor form of ST2 is secreted and detectable in human serum. This study tested the hypothesis that soluble ST2 levels in the serum of patients with severe chronic heart failure are increased in patients with neurohormonal activation. METHODS AND RESULTS: Serum samples, clinical variables, and neurohormone levels from the PRAISE-2 heart failure trial (NYHA functional class III-IV; end point, mortality or transplantation) were analyzed. ST2 serum measurements were performed with ELISA on samples from 161 patients obtained at trial enrollment and from 139 of the same patients obtained 2 weeks after trial enrollment. Baseline ST2 levels were correlated with baseline B-type natriuretic peptide (BNP) levels (r=0.36, P<0.0001), baseline proatrial natriuretic peptide (ProANP) levels (r=0.36, P<0.0001), and baseline norepinephrine levels (r=0.39, P<0.0001). The change in ST2 was significant as a univariate predictor of subsequent mortality or transplantation (P=0.048), as was baseline BNP (P<0.0001) and baseline ProANP (P<0.0001). In multivariate models including BNP and ProANP, the change in ST2 remained significant as a predictor of mortality or transplantation independent of BNP and ProANP. CONCLUSIONS: Serum soluble ST2 is a novel biomarker for neurohormonal activation in patients with heart failure. In patients with severe chronic NYHA class III to IV heart failure, the change in ST2 levels is an independent predictor of subsequent mortality or transplantation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".