Risk Estimates of Imminent Cardiovascular Death and Heart Failure Hospitalization Are Improved Using Serial Natriuretic Peptide Measurements in Patients With Coronary Artery Disease and Type 2 Diabetes
Bibliographic record
Abstract
Background Baseline and temporal changes in natriuretic peptide (NP) concentrations have strong prognostic value with regard to long‐term cardiovascular risk stratification. To increase the clinical utility of NP sampling for patient management, we wanted to assess the incremental predictive value of 2 serial NP measurements compared with a single measurement and provide absolute risk estimates for cardiovascular death or heart failure hospitalization (HFH) within 6 months based on 2 serial NP measurements. Methods and Results Consecutive NP samples obtained from 5393 patients with a recent coronary event and type 2 diabetes enrolled in the ELIXA (Evaluation of Cardiovascular Outcomes in Patients With Type 2 Diabetes After Acute Coronary Syndrome During Treatment With Lixisenatide) trial were used to construct best logistic regression models with outcome of cardiovascular death or HFH (136 events). Absolute risk estimates of cardiovascular death or HFH within 6 months using either BNP (B‐type natriuretic peptide) or NT‐proBNP (N‐terminal pro‐BNP) serial measurements were depicted based on the concentrations of 2 serial NP measurements. During the 6‐month follow‐up periods, the incidence rate (±95% CIs) of cardiovascular death or HFH for patients was 14.0 (11.8‒16.6) per 1000 patient‐years. Risk prediction depended on NP concentrations from both prior and current sampling. NP sampling 6 months apart improved the predictive value and reclassification of patients compared with a single sample (AUROC [Area Under the Receiver Operating Characteristic curve]: BNP, P =0.003. NT‐proBNP, P <0.0001), with a majority of moderate‐risk patients (6‐month risk between 1% and 10%) being reclassified on the basis of the second NP sample. Conclusions Serial NP measurements improved prediction of imminent cardiovascular death or HFH in patients with coronary artery disease and type 2 diabetes. The absolute risk estimates provided may aid clinicians in decision‐making and help patients understand their short‐term risk profile.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".