Use of Natriuretic Peptides as a Guidance for Treating Patients with Chronic Heart Failure: Unresolved Issues and Novel Insights
Bibliographic record
Abstract
Serial measurements of natriuretic peptides (NPs), i.e. B-type natriuretic peptide (BNP) or amino-terminal fragment of pro B-type natriuretic peptide (NT-pro BNP), may serve as an objective guide to modulate the intensity of drug treatment for individuals with chronic heart failure (CHF). However, considerable uncertainty remains about the alleged useful role of NP-guided therapy in this context. Particularly, which NP level should be assumed as optimal target level for therapy is still matter of debate. Actually, a too low predetermined cut off is encumbered with the risk of inducing a dose escalation perhaps not founded on solid rationale but provided with the potential of propitiating adverse medication effects that may be associated with higher doses. Conversely, a too high predetermined level for NP would entail a poor sensitivity, with the potential of excluding from higher doses of medications, that are proven to increase survival, just the patients who above all would have benefitted from this uptitration. Another much debated issue is constituted by possible age-related differences concerning the effects on clinical endpoints of NP-guided therapy. In addition, some Authors dispute about the possible advantages for the cardiovascular system arising from the functional activation of NPs in CHF patients, so denying that their increased levels have to be per se blamed for hemodynamic upheaval, especially in elder CHF patients. After outlining the main RCTs carried out so far, the Authors stress the above reported issues and discuss the sometime contradictory results of the RCTs exploring NPs use as a guidance for therapy.
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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 | 0.018 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".