Global Longitudinal Strain and Brain Natriuretic Peptide as Prognostic Biomarkers for Asymptomatic Severe Aortic Regurgitation with Preserved Ejection Fraction: A Protocol for Systematic Review and Meta-Analysis (Preprint)
Bibliographic record
Abstract
Background: Brain natriuretic peptide (BNP) and global longitudinal strain (GLS) are emerging biomarkers used to risk-stratify patients with asymptomatic severe aortic regurgitation (AR) and preserved ejection fraction (EF). Although numerous clinical trials have investigated the efficacy of these biomarkers in patients with aortic stenosis, only a limited number have examined these biomarkers in patients with AR. Therefore, the proposed systematic review and meta-analysis seeks to assess the prognostic value of BNP and/or GLS in patients with severe asymptomatic AR and preserved EF. Objective: This is a protocol for a systematic review and meta-analysis that will aggregate and synthesize high-quality clinical data on the usefulness of BNP and GLS as prognostic indicators for asymptomatic severe AR with preserved EF. By providing a comprehensive review, our study will have a significant impact in determining surgical candidacy in this patient population. Methods: In accordance with the PRISMA-S (Preferred Reporting Items for Systematic reviews and Meta-Analyses literature search extension), which is an extension of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement for reporting literature searches in systematic reviews, a comprehensive search of databases, including PubMed, Cochrane, and Embase, will be performed to retrieve peer-reviewed, English-language, observational, and experimental studies published from inception to November 2024. Studies that investigated patients aged ≥18 years with severe AR and preserved EF will be included. The National Heart, Lung, and Blood Institute tool will be used to assess the quality of the studies. Results: Search strategy development for this systematic review began in November 2024. A Peer Review of Electronic Search Strategies review of the search strategy with 2 academic librarians occurred in December 2024, and the final search strategy was finalized by the team of investigators in January 2025. Database queries and screening of studies began in January 2025 with title screening, followed by abstract screening in January and February 2025. Full-text screening took place from February to April 2025. Data extraction occurred between April and May 2025. Synthesis and risk of bias assessment occurred between April and May 2026, followed by data analysis between June and July 2026. Manuscript drafting will begin between June 2026 and July 2026, with manuscript writing and data dissemination continuing from May 2026 to August 2026. Findings will be submitted to a peer-reviewed journal by August 2026. Conclusions: This systematic review will synthesize the existing evidence to determine the prognostic value of BNP and GLS in patients with asymptomatic severe AR and preserved EF, which could inform future clinical guidelines for the management of this population.
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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 | 0.040 | 0.101 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.017 | 0.022 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.063 | 0.006 |
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".