TY - JOUR
T1 - Inflammatory risk and cardiovascular events in patients without obstructive coronary artery disease
T2 - The ORFAN multicentre, longitudinal cohort study
AU - Chan, Kenneth
AU - Wahome, Elizabeth
AU - Tsiachristas, Apostolos
AU - Antonopoulos, Alexios S
AU - Patel, Parijat
AU - Lyasheva, Maria
AU - Kingham, Lucy
AU - West, Henry
AU - Oikonomou, Evangelos K
AU - Volpe, Lucrezia
AU - Mavrogiannis, Michail C
AU - Nicol, Edward
AU - Mittal, Tarun K
AU - Halborg, Thomas
AU - Kotronias, Rafail A
AU - Adlam, David
AU - Modi, Bhavik
AU - Rodrigues, Jonathan
AU - Screaton, Nicholas
AU - Kardos, Attila
AU - Greenwood, John P
AU - Sabharwal, Nikant
AU - De Maria, Giovanni Luigi
AU - Munir, Shahzad
AU - McAlindon, Elisa
AU - Sohan, Yogesh
AU - Tomlins, Pete
AU - Siddique, Muhammad
AU - Kelion, Andrew
AU - Shirodaria, Cheerag
AU - Pugliese, Francesca
AU - Petersen, Steffen E
AU - Blankstein, Ron
AU - Desai, Milind
AU - Gersh, Bernard J
AU - Achenbach, Stephan
AU - Libby, Peter
AU - Neubauer, Stefan
AU - Channon, Keith M
AU - Deanfield, John
AU - Antoniades, Charalambos
AU - ORFAN Consortium
AU - Thomas, Sheena
AU - Denton, Jon
AU - Farral, Robyn
AU - Taylor, Carolyn
AU - Qin, Wendy
AU - Kasongo, Mary
AU - Anthony, Susan
AU - Banning, Adrian
AU - Xie, Cheng
AU - Kharbanda, Rajesh K
AU - Pritchard, Amy
AU - Syed, Nigar
AU - Fry, Sam
AU - Mathers, Chris
AU - Rose, Anne
AU - Hudson, George
AU - Bajaj, Amrita
AU - Das, Intrajeet
AU - Deshpande, Aparna
AU - Rao, Praveen
AU - Lawday, Dan
AU - Mirsadraee, Saeed
AU - Hudson, Benjamin
AU - Berry, Colin
AU - Marwan, Mohamed
AU - Maurovich-Horvat, Pál
AU - He, Guo-Wei
AU - Lin, Wen-Hua
AU - Fan, Li-Juan
AU - Takahashi, Naohiko
AU - Kondo, Hidekazu
AU - Dai, Neng
AU - Ge, Junbo
AU - Koo, Bon-Kwon
AU - Guglielmo, Marco
AU - Pontone, Gianluca
AU - Huck, Daniel
AU - Benedek, Theodora
AU - Rajani, Ronak
AU - Vilic, Dijana
AU - Aljazzaf, Haleema
AU - Mun, Mak S
AU - Benedetti, Giulia
AU - Preston, Rebecca L
AU - Raisi-Estabragh, Zahra
AU - Connolly, Derek L
AU - Sharma, Vinoda
AU - Grenfell, Rebecca
AU - Bradlow, William
AU - Schmitt, Matthias
AU - Serfaty, Fabiano
AU - Gottlieb, Ilan
AU - Neves, Mario F T
AU - Newby, David E
AU - Dweck, Marc R
AU - Hatem, Stéphane
AU - Redheuil, Alban
AU - Benetos, Georgios
AU - Beer, Meinrad
AU - Granillo, Gastón A R
AU - Selvanayagam, Joseph
AU - Lopez-Jimenez, Francisco
AU - De Bosscher, Ruben
AU - Tavildari, Alain
AU - Figtree, Gemma
AU - Danad, Ibrahim
AU - Shantouf, Ronney
AU - Kietselaer, Bas
AU - Tousoulis, Dimitris
AU - Dangas, George
AU - Mehta, Nehal N
AU - Kontanidis, Christos
AU - Kunadian, Vijay
AU - Fairbairn, Timothy A
PY - 2024/6/15
Y1 - 2024/6/15
N2 - Background: Coronary computed tomography angiography (CCTA) is the first line investigation for chest pain, and it is used to guide revascularisation. However, the widespread adoption of CCTA has revealed a large group of individuals without obstructive coronary artery disease (CAD), with unclear prognosis and management. Measurement of coronary inflammation from CCTA using the perivascular fat attenuation index (FAI) Score could enable cardiovascular risk prediction and guide the management of individuals without obstructive CAD. The Oxford Risk Factors And Non-invasive imaging (ORFAN) study aimed to evaluate the risk profile and event rates among patients undergoing CCTA as part of routine clinical care in the UK National Health Service (NHS); to test the hypothesis that coronary arterial inflammation drives cardiac mortality or major adverse cardiac events (MACE) in patients with or without CAD; and to externally validate the performance of the previously trained artificial intelligence (AI)-Risk prognostic algorithm and the related AI-Risk classification system in a UK population. Methods: This multicentre, longitudinal cohort study included 40 091 consecutive patients undergoing clinically indicated CCTA in eight UK hospitals, who were followed up for MACE (ie, myocardial infarction, new onset heart failure, or cardiac death) for a median of 2·7 years (IQR 1·4–5·3). The prognostic value of FAI Score in the presence and absence of obstructive CAD was evaluated in 3393 consecutive patients from the two hospitals with the longest follow-up (7·7 years [6·4–9·1]). An AI-enhanced cardiac risk prediction algorithm, which integrates FAI Score, coronary plaque metrics, and clinical risk factors, was then evaluated in this population. Findings: In the 2·7 year median follow-up period, patients without obstructive CAD (32 533 [81·1%] of 40 091) accounted for 2857 (66·3%) of the 4307 total MACE and 1118 (63·7%) of the 1754 total cardiac deaths in the whole of Cohort A. Increased FAI Score in all the three coronary arteries had an additive impact on the risk for cardiac mortality (hazard ratio [HR] 29·8 [95% CI 13·9–63·9], p<0·001) or MACE (12·6 [8·5–18·6], p<0·001) comparing three vessels with an FAI Score in the top versus bottom quartile for each artery. FAI Score in any coronary artery predicted cardiac mortality and MACE independently from cardiovascular risk factors and the presence or extent of CAD. The AI-Risk classification was positively associated with cardiac mortality (6·75 [5·17–8·82], p<0·001, for very high risk vs low or medium risk) and MACE (4·68 [3·93–5·57], p<0·001 for very high risk vs low or medium risk). Finally, the AI-Risk model was well calibrated against true events. Interpretation: The FAI Score captures inflammatory risk beyond the current clinical risk stratification and CCTA interpretation, particularly among patients without obstructive CAD. The AI-Risk integrates this information in a prognostic algorithm, which could be used as an alternative to traditional risk factor-based risk calculators. Funding: British Heart Foundation, NHS-AI award, Innovate UK, National Institute for Health and Care Research, and the Oxford Biomedical Research Centre.
AB - Background: Coronary computed tomography angiography (CCTA) is the first line investigation for chest pain, and it is used to guide revascularisation. However, the widespread adoption of CCTA has revealed a large group of individuals without obstructive coronary artery disease (CAD), with unclear prognosis and management. Measurement of coronary inflammation from CCTA using the perivascular fat attenuation index (FAI) Score could enable cardiovascular risk prediction and guide the management of individuals without obstructive CAD. The Oxford Risk Factors And Non-invasive imaging (ORFAN) study aimed to evaluate the risk profile and event rates among patients undergoing CCTA as part of routine clinical care in the UK National Health Service (NHS); to test the hypothesis that coronary arterial inflammation drives cardiac mortality or major adverse cardiac events (MACE) in patients with or without CAD; and to externally validate the performance of the previously trained artificial intelligence (AI)-Risk prognostic algorithm and the related AI-Risk classification system in a UK population. Methods: This multicentre, longitudinal cohort study included 40 091 consecutive patients undergoing clinically indicated CCTA in eight UK hospitals, who were followed up for MACE (ie, myocardial infarction, new onset heart failure, or cardiac death) for a median of 2·7 years (IQR 1·4–5·3). The prognostic value of FAI Score in the presence and absence of obstructive CAD was evaluated in 3393 consecutive patients from the two hospitals with the longest follow-up (7·7 years [6·4–9·1]). An AI-enhanced cardiac risk prediction algorithm, which integrates FAI Score, coronary plaque metrics, and clinical risk factors, was then evaluated in this population. Findings: In the 2·7 year median follow-up period, patients without obstructive CAD (32 533 [81·1%] of 40 091) accounted for 2857 (66·3%) of the 4307 total MACE and 1118 (63·7%) of the 1754 total cardiac deaths in the whole of Cohort A. Increased FAI Score in all the three coronary arteries had an additive impact on the risk for cardiac mortality (hazard ratio [HR] 29·8 [95% CI 13·9–63·9], p<0·001) or MACE (12·6 [8·5–18·6], p<0·001) comparing three vessels with an FAI Score in the top versus bottom quartile for each artery. FAI Score in any coronary artery predicted cardiac mortality and MACE independently from cardiovascular risk factors and the presence or extent of CAD. The AI-Risk classification was positively associated with cardiac mortality (6·75 [5·17–8·82], p<0·001, for very high risk vs low or medium risk) and MACE (4·68 [3·93–5·57], p<0·001 for very high risk vs low or medium risk). Finally, the AI-Risk model was well calibrated against true events. Interpretation: The FAI Score captures inflammatory risk beyond the current clinical risk stratification and CCTA interpretation, particularly among patients without obstructive CAD. The AI-Risk integrates this information in a prognostic algorithm, which could be used as an alternative to traditional risk factor-based risk calculators. Funding: British Heart Foundation, NHS-AI award, Innovate UK, National Institute for Health and Care Research, and the Oxford Biomedical Research Centre.
KW - Inflammation
KW - Chest pain
KW - Obstructive coronary artery disease
UR - http://www.scopus.com/inward/record.url?scp=85195645345&partnerID=8YFLogxK
U2 - 10.1016/S0140-6736(24)00596-8
DO - 10.1016/S0140-6736(24)00596-8
M3 - Article
C2 - 38823406
AN - SCOPUS:85195645345
SN - 0140-6736
VL - 403
SP - 2606
EP - 2618
JO - The Lancet
JF - The Lancet
IS - 10444
ER -