Modification of the Association of B-Type Natriuretic Peptides With Mortality and Hospitalization Outcomes by Sex
Bibliographic record
Abstract
BACKGROUND: The effects of sex on the prognostic implications of natriuretic peptide (NP) elevation have not been fully elucidated in the population. OBJECTIVES: The purpose of this study was to examine if sex modifies associations of NPs with mortality and hospitalization. METHODS: In a population-based retrospective cohort study, we identified all patients (aged ≥40 years) undergoing NP testing in Ontario, Canada (2015-2020). We examined for the presence of sex-by-NP interactions for 1-year outcomes and conducted sex-specific analyses for continuously increasing NP concentrations. RESULTS: We studied 91,017 individuals with B-type natriuretic peptide (BNP) tests (median 75 years; 48.0% females) and 81,578 individuals with N-terminal pro-BNP (NT-proBNP) tests (74 years; 48.6% females). Adjusted 1-year risks of all-cause mortality at any given NP concentration were higher in males than females. For example, 1-year mortality at a BNP of 400 ng/L was 16.8% in females and 21.6% in males. At an NT-proBNP of 900 ng/L, 1-year mortality was 14.2% in females and 18.5% in males. However, there were also significant sex interactions with BNP (P = 0.002) and NT-proBNP (P = 0.03) for mortality outcomes. When we examined cardiovascular hospitalizations, there was also a significant sex-by-NP interaction. For BNP, the risk of cardiovascular hospitalization was higher in males at lower concentrations but was higher in females at higher concentrations (P-interaction = 0.005). For NT-proBNP, the risk of cardiovascular hospitalization was higher in males at lower NP concentrations, but the gap narrowed at higher NP levels (P interaction = 0.03). CONCLUSIONS: Sex modifies the association between NP concentrations and all-cause mortality or cardiovascular hospitalizations. Prognostically, interpretation of NP levels should consider effect modification by sex.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".