Artificial intelligence-derived physiological aging is associated with coronary endothelial dysfunction. (25th November 2020)
- Record Type:
- Journal Article
- Title:
- Artificial intelligence-derived physiological aging is associated with coronary endothelial dysfunction. (25th November 2020)
- Main Title:
- Artificial intelligence-derived physiological aging is associated with coronary endothelial dysfunction
- Authors:
- Ahmad, A
Toya, T
Corban, M
Attia, Z.I
Lopez-Jimenez, F
Shelly Cohen, M
Noseworthy, P.A
Kapa, S
Friedman, P.A
Lerman, A - Abstract:
- Abstract: Background: An Artificial intelligence (AI)-enabled algorithm can provide an age estimate from a single standard resting ECG. The gap between AI-estimated age (ECG age) and chronological age (Age-Gap) has been associated with total and cardiovascular mortality. We hypothesized that coronary endothelial dysfunction (CED), an early feature of coronary atherosclerosis, is associated with physiological aging, as measured by ECG age. Purpose: The aim of this study is to investigate the association of CED, a potential index of cardiac aging, and AI-estimated physiological aging. Methods: 1902 patients with signs and/or symptoms of ischemia and with non-obstructive coronary artery disease (<40% angiographic stenosis) who underwent functional coronary angiography with intracoronary (IC) acetylcholine (Ach) infusions and a resting ECG within one year were included in this analysis. CED was defined as coronary artery constriction [%ΔCoronary artery diameter (CAD) <0] in response to IC Ach. Patients were categorized as CED+ or CED−. The ECG age were calculated by a previously-trained AI algorithm that was built using the Keras framework with Tensorflow backend and Python. The association between ECG-age and Age-Gap, with CED was investigated. Results: Average chronological age was 50.9±12.5, ECG age was 54.1±11.6, 1261 (66%) were females. Compared to CED−, the CED+ group had more males and hyperlipidaemia (p<0.05 for both). Age-gap was significantly higher in patients withAbstract: Background: An Artificial intelligence (AI)-enabled algorithm can provide an age estimate from a single standard resting ECG. The gap between AI-estimated age (ECG age) and chronological age (Age-Gap) has been associated with total and cardiovascular mortality. We hypothesized that coronary endothelial dysfunction (CED), an early feature of coronary atherosclerosis, is associated with physiological aging, as measured by ECG age. Purpose: The aim of this study is to investigate the association of CED, a potential index of cardiac aging, and AI-estimated physiological aging. Methods: 1902 patients with signs and/or symptoms of ischemia and with non-obstructive coronary artery disease (<40% angiographic stenosis) who underwent functional coronary angiography with intracoronary (IC) acetylcholine (Ach) infusions and a resting ECG within one year were included in this analysis. CED was defined as coronary artery constriction [%ΔCoronary artery diameter (CAD) <0] in response to IC Ach. Patients were categorized as CED+ or CED−. The ECG age were calculated by a previously-trained AI algorithm that was built using the Keras framework with Tensorflow backend and Python. The association between ECG-age and Age-Gap, with CED was investigated. Results: Average chronological age was 50.9±12.5, ECG age was 54.1±11.6, 1261 (66%) were females. Compared to CED−, the CED+ group had more males and hyperlipidaemia (p<0.05 for both). Age-gap was significantly higher in patients with CED+ (Fig. A). Multiple regression analysis showed that CED+ was associated with Age-gap (standardized β [sβ] coefficient = 0.08, P=0.001) even after adjustment for chronological age (sβ coefficient = 0.07, P=0.001), and even after adjusting for other cardiovascular risk factors like gender and obesity (sβ coefficient = 0.07, P<0.0001). Furthermore, there is a significant gradual increase in vasoconstriction, in response to IC Ach, with increasing Age-gap (Fig. B). Conclusion: Abnormal coronary endothelial function is associated with an increased AI-estimated age which could indicate a higher physiological age. Funding Acknowledgement: Type of funding source: None … (more)
- Is Part Of:
- European heart journal. Volume 41:(2020)Supplement 2
- Journal:
- European heart journal
- Issue:
- Volume 41:(2020)Supplement 2
- Issue Display:
- Volume 41, Issue 2 (2020)
- Year:
- 2020
- Volume:
- 41
- Issue:
- 2
- Issue Sort Value:
- 2020-0041-0002-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-11-25
- Subjects:
- Coronary Circulation, Flow, and Flow Reserve
Cardiology -- Periodicals
Heart -- Diseases -- Periodicals
616.12005 - Journal URLs:
- http://eurheartj.oxfordjournals.org/ ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/ehjci/ehaa946.1271 ↗
- Languages:
- English
- ISSNs:
- 0195-668X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3829.717500
British Library DSC - BLDSS-3PM
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- 26678.xml