6097Aminoterminal proB-type natriuretic peptide: a key parameter to optimise therapeutic management of low-flow, low-gradient aortic stenosis
Bibliographic record
Abstract
Abstract Background B-type natriuretic peptide (BNP) and aminoterminal-proBNP (NT-proBNP) are well established surrogates of LV function impairment. However, data are scarce regarding their prognostic value to risk-stratify patients with classical low-flow, low-gradient aortic stenosis (LFLG-AS, with low left ventricular [LV] ejection fraction). Methods The TOPAS study is a prospective observational cohort of 240 patients with aortic valve area <0.6 cm2/m2, mean gradient<40 mmHg and LVEF<50%. True severe AS was adjudicated using flow independent grading schemes. Results BNP significantly predicted one-year (area under the receiver operating-characteristic curve [AUC]) 0.62±0.04, p=0.026) but not three-year mortality. After adjustment for the severity of AS, initial treatment (aortic valve replacement [AVR] vs. conservative management [ConsRx]), age, sex and the EuroSCORE (Model#1), BNP-ratio>550 pg/ml had a trend to predict time to death (HR=2.14 [1.00–4.58], p=0.05). In contrast, NT-proBNP ratio significantly predicted both one and three-year mortality (AUC=0.67±0.04 and 0.66±0.05, both p=0.001), and independently predicted time to death (HR=1.39 per 1 unit of Log transformed NT-proBNP [1.11–1.74], p=0.004). In a head-to-head comparison (108 patients with both biomarkers), the AUCs to predict one and thre-year mortality were significantly higher with NT-proBNP versus BNP (p<0.009). NT-proBNP but not BNP independently predicted mortality and significantly improved Model#1 (Likelihood ratio test Chi2=15.95, p<0.001). The category-free net reclassification index of NT-proBNP was 0.71 (p=0.008) versus 0.38 (p=0.15) for BNP. Furthermore, there was a marked survival benefit associated with AVR in patients with NT-proBNP ≥1700 pg/ml (adjusted hazard ratio (aHR) associated to AVR vs conservative management=0.52 [0.31–0.85], p=0.009), while those<1700 pg/ml had excellent one-year survival under ConsRx (only one death [4.5±4.4%] at one year as compared to 23 [37±6.2%] for ConsRx-NTproBNP>1700, aHR=0.11 [0.01–0.83], p=0.033). The survival benefit associated with AVR interacted with NT-proBNP (p<0.001) but not with true or pseudosevere AS (p=0.53 for interaction), suggesting that NT-proBNP might identify moderate AS patients but sufficiently severe valvulo-ventricular disease to justify AVR. Survival according to NT-proBNP and AVR Conclusion NT-proBNP appears to be an excellent biomarker for the clinical purpose of risk-stratifying classical LFLG-AS. A threshold of 1700 pg/ml i.e. close to the diagnostic threshold for heart failure in acute dyspnea, was a strong independent determinant of the survival benefit associated with aortic valve replacement. Our findings suggest that NT-proBNP should be preferred over BNP. Acknowledgement/Funding Canadian Institute of Health Research
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".