Is it NICE to Measure Natriuretic Peptides After a Hospitalization for Heart Failure?
Bibliographic record
Abstract
This article refers to ‘N-terminal pro-B-type natriuretic peptide post-discharge monitoring in the management of patients with heart failure and preserved ejection fraction – a randomized trial: The NICE study’ by D.A. Pascual-Figal et al., published in this issue on pages 776–784. The role of natriuretic peptides (NPs) in the diagnosis of heart failure (HF) is well established, as shown by guidelines and consensus statements.1,2 However, it is still unclear how to use these biomarkers to guide HF treatment. Indeed, recent randomized trials evaluating the usefulness of NPs for optimization of guideline-directed medical therapy (GDMT) have shown conflicting results.3–6 In this context, studies aimed at assessing the role of NPs for the management of patients with HF are extremely welcome. In this issue of the Journal, Pascual-Figal et al.7 report the results of the multicentre, prospective, open-label, randomized NICE (NT-proBNP in the Management of Discharged Patients with Acutely Decompensated Heart Failure and Preserved Ejection Fraction) trial testing the benefit of serial post-discharge N-terminal pro-B-type natriuretic peptide (NT-proBNP) measurement after a hospitalization for HF in patients with HF with preserved ejection fraction (HFpEF). In this trial, patients hospitalized for acute HF caused by HFpEF were randomized in a 1:1 ratio at the time of discharge to a usual care arm and a NT-proBNP arm. In the latter, on top of usual care, the investigators had access to NT-proBNP concentrations at three pre-specified post-discharge clinical visits performed at 2, 4 and 12 weeks. Out of a planned sample size of 420 patients, a total of only 157 patients (37.4%) were enrolled in the study due to coronavirus disease 2019 (COVID-19) restrictions and anticipated futility at the first interim analysis. Although patients randomized to NT-proBNP-based care were treated with higher doses of diuretics and renin–angiotensin system inhibitors, the primary endpoint of HF rehospitalizations at 6 months was similar between the two groups (12.8% in the NT-proBNP arm vs. 11.4% in the control arm).7 Worsening HF may include also events not followed by patients' hospitalization.8 However, no differences were found also for other HF events, including urgent and outpatient visits. Rather unexpectedly, instead, a significantly lower risk of all-cause death at 6 months was observed in the NT-proBNP versus control arm (1 death, 1.3%, vs. 8 deaths, 10.1%; hazard ratio 0.12, 95% confidence interval 0.02–0.98). However, the low number of events in the context of a relatively small sample size, leaves the doubt that this secondary finding may be due to chance.7 Quality of life and the 6-min walking test distance also had similar changes in both treatment arms with no significant difference.7
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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 | 0.023 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".