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

In brief

Electronic alerts raise one-year valve replacement rates by 11% in severe aortic stenosis

A systematic review of ~52,000 patients found that after diagnosis, an electronic provider notification boosted one-year aortic valve replacement from 37% to 48%, especially in women, the elderly, and inpatients. Missed detection before echocardiography remains a gap, and wait-list mortality stays near 5%, highlighting multiple points for workflow improvement.

Journal
European heart journal. Quality of care & clinical outcomes (Q1)
Published
1 August 2026
Study design
Systematic review of cohort studies
Evidence level
Level 2, Moderate (CEBM 2a)
Authors
Nicholas Fanous, Nicolas Zubrzycki, Lachlan Weir, Farhan Mohammed, Amy Pomeroy, Tom Meredith, et al.
PMID
42538860
DOI
10.1093/ehjqcco/qcag123

Why clinicians should know about it

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.

Abstract as published, via PubMed.

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For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.