| Title: | Real-world evaluation of an algorithmic machine-learning-guided testing approach in stable chest pain: a multinational, multicohort study |
| Journal: | European Heart Journal - Digital Health |
| Published: | 8 Apr 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38774380/ |
| DOI: | https://doi.org/10.1093/ehjdh/ztae023 |
| URL: | https://academic.oup.com/ehjdh/advance-article-pdf/doi/10.1093/ehjdh/ztae023/57173215/ztae023.pdf |
Publication 9944
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Abstract
Aims: An algorithmic strategy for anatomical vs. functional testing in suspected coronary artery disease (CAD) (Anatomical vs. Stress teSting decIsion Support Tool; ASSIST) is associated with better outcomes than random selection. However, in the real world, this decision is rarely random. We explored the agreement between a provider-driven vs. simulated algorithmic approach to cardiac testing and its association with outcomes across multinational cohorts.</p>
Methods and results: In two cohorts of functional vs. anatomical testing in a US hospital health system [Yale; 2013-2023; n = 130 196 (97.0%) vs. n = 4020 (3.0%), respectively], and the UK Biobank [n = 3320 (85.1%) vs. n = 581 (14.9%), respectively], we examined outcomes stratified by agreement between the real-world and ASSIST-recommended strategies. Younger age, female sex, Black race, and diabetes history were independently associated with lower odds of ASSIST-aligned testing. Over a median of 4.9 (interquartile range [IQR]: 2.4-7.1) and 5.4 (IQR: 2.6-8.8) years, referral to the ASSIST-recommended strategy was associated with a lower risk of acute myocardial infarction or death (hazard ratioadjusted: 0.81, 95% confidence interval [CI] 0.77-0.85, P < 0.001 and 0.74 [95% CI 0.60-0.90], P = 0.003, respectively), an effect that remained significant across years, test types, and risk profiles. In post hoc analyses of anatomical-first testing in the Prospective Multicentre Imaging Study for Evaluation of Chest Pain (PROMISE) trial, alignment with ASSIST was independently associated with a 17% and 30% higher risk of detecting CAD in any vessel or the left main artery/proximal left anterior descending coronary artery, respectively.</p>
Conclusion: In cohorts where historical practices largely favour functional testing, alignment with an algorithmic approach to cardiac testing defined by ASSIST was associated with a lower risk of adverse outcomes. This highlights the potential utility of a data-driven approach in the diagnostic management of CAD.</p>
9 Authors
- Evangelos K Oikonomou
- Arya Aminorroaya
- Lovedeep S Dhingra
- Caitlin Partridge
- Eric J Velazquez
- Nihar R Desai
- Harlan M Krumholz
- Edward J Miller
- Rohan Khera
1 Application
| Application ID | Title |
|---|---|
| 71033 | A framework to assess causal effects in observational data through deep digital phenotyping and creating digital twins |
Enabling scientific discoveries that improve human health