Delay and Attrition in Severe Aortic Stenosis: A Four-Checkpoint Systematic Review of Pathway Bottlenecks and Interventions

Clicks: 10
ID: 323210
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #35 of 70 articles by views in european heart journal - quality of care and clinical outcomes

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The care pathway for severe aortic stenosis (AS) remains vulnerable to diagnostic delay, referral inertia, undertreatment, and procedural waiting times despite the availability of definitive intervention with surgical or transcatheter aortic valve replacement. This systematic review with narrative synthesis aimed to identify where delay and attrition occur across the contemporary severe AS pathway and to summarise evidence for digital, organisational, and workflow interventions designed to improve timely care. Randomised and non-randomised studies examining diagnostic, referral, treatment-decision, or procedural-access delays in adults with severe AS were eligible. Findings were mapped onto a four-checkpoint framework: pre-echocardiographic recognition, echocardiographic detection, post-diagnostic referral and decision-making, and procedural access. Nineteen studies met inclusion criteria. After de-duplication of overlapping registries and exclusion of studies without a verifiable unique severe-AS or severe-AS pathway denominator, the synthesis represented approximately 52,000 patients. Evidence was unevenly distributed, with no included study providing severe-AS-specific data before echocardiography. At echocardiographic detection, missed or delayed recognition was concentrated in low-gradient phenotypes and women; an artificial-intelligence-assisted alert system increased severe-AS detection from 2.4% to 4.1%. After diagnosis, undertreatment persisted despite guideline indications, and non-cardiology ordering of the diagnostic echocardiogram was associated with lower early follow-up or AVR and higher mortality. Electronic provider notification increased one-year AVR rates from 37.2% to 48.2%, with the largest observed effects in women, patients older than 80 years, and inpatient echocardiography. At procedural access, wait-list mortality was approximately 4.5%-5.8%, with deaths occurring early after referral. Risk-based triage reduced modelled wait-list mortality, while decentralised pre-procedural work-up shortened referral-to-TAVI time from 126 to 32 days. Severe AS care is characterised by measurable delay and attrition across multiple post-diagnostic transitions, while pre-echocardiographic recognition remains an important evidence gap. A four-checkpoint framework may support benchmarking and targeted pathway improvement through structured reporting, electronic referral prompts, risk-based triage, and decentralised workflows.
Reference Key
openalex_W7172119999 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Nicholas Fanous, Nicolas Zubrzycki, L Weir, Farhan Mohammed, Amy Pomeroy, Tom Meredith, David Roy, Andrew Roy, Jason Kovacic, David Muller, Michael Feneley, Sammy Elmariah, Mayooran Namasivayam
Journal european heart journal - quality of care and clinical outcomes
Year 2026
DOI
10.1093/ehjqcco/qcag123
URL
https://doi.org/10.1093/ehjqcco/qcag123
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.