Duration of dual antiplatelet therapy and stability of coronary heart disease: a 60 000-patient meta-analysis of randomised controlled trials.

BACKGROUND: Dual antiplatelet therapy (DAPT) has important implications for clinical outcomes in coronary disease. However, the optimal DAPT duration remains uncertain. METHODS AND RESULTS: We searched four major databases for randomised controlled trials comparing long-term (≥12 months) with short-term (≤6 months) or shorter (≤3 months) DAPT in patients with coronary syndromes. The primary outcome was all-cause mortality. Secondary outcomes were any bleeding and major bleeding (safety), cardiac death, myocardial infarction, stent thrombosis, revascularisation and stroke (efficacy). Nineteen randomised controlled trials (n=60 111) satisfied inclusion criteria, 8 assessed ≤3 months DAPT. Compared with long-term (≥12 months), short-term DAPT (≤6 months) was associated with a trend towards reduced all-cause mortality (RR: 0.90, 95% CI: 0.80 to 1.01) and significant bleeding reduction (RR: 0.68, 95% CI: 0.55 to 0.83 and RR: 0.66, 95% CI: 0.56 to 0.77 for major and any bleeding, respectively). There were no significant differences in efficacy outcomes. These associations persisted in sensitivity analysis comparing shorter duration DAPT (≤3 months) to long-term DAPT (≥12 months) for all-cause mortality (RR: 0.91, 95% CI: 0.79 to 1.05). In subgroup analysis, short-term DAPT was associated with lower risk of bleeding in patients with acute or chronic coronary syndromes (RR: 0.66, 95% CI: 0.54 to 0.81 and RR: 0.53, 95% CI: 0.33 to 0.65, respectively), but higher risk of stent thrombosis in acute coronary syndrome (RR: 1.49, 95% CI: 1.02 to 2.17 vs RR: 1.25, 95% CI 0.44 to 3.58). CONCLUSION: Our meta-analysis suggests that short (≤6 months) and shorter (≤3 months) durations DAPT are associated with lower risk of bleeding, equivalent efficacy and a trend towards lower all-cause mortality irrespective of coronary artery disease stability

Machine-learning with 18F-sodium fluoride PET and quantitative plaque analysis on CT angiography for the future risk of myocardial infarction

Coronary (18)F-sodium fluoride ((18)F-NaF) PET and CT angiography–based quantitative plaque analysis have shown promise in refining risk stratification in patients with coronary artery disease. We combined both of these novel imaging approaches to develop an optimal machine-learning model for the future risk of myocardial infarction in patients with stable coronary disease. Methods: Patients with known coronary artery disease underwent coronary (18)F-NaF PET and CT angiography on a hybrid PET/CT scanner. Machine-learning by extreme gradient boosting was trained using clinical data, CT quantitative plaque analysis, measures and (18)F-NaF PET, and it was tested using repeated 10-fold hold-out testing. Results: Among 293 study participants (65 ± 9 y; 84% male), 22 subjects experienced a myocardial infarction over the 53 (40–59) months of follow-up. On univariable receiver-operator-curve analysis, only (18)F-NaF coronary uptake emerged as a predictor of myocardial infarction (c-statistic 0.76, 95% CI 0.68–0.83). When incorporated into machine-learning models, clinical characteristics showed limited predictive performance (c-statistic 0.64, 95% CI 0.53–0.76) and were outperformed by a quantitative plaque analysis-based machine-learning model (c-statistic 0.72, 95% CI 0.60–0.84). After inclusion of all available data (clinical, quantitative plaque and (18)F-NaF PET), we achieved a substantial improvement (P = 0.008 versus (18)F-NaF PET alone) in the model performance (c-statistic 0.85, 95% CI 0.79–0.91). Conclusion: Both (18)F-NaF uptake and quantitative plaque analysis measures are additive and strong predictors of outcome in patients with established coronary artery disease. Optimal risk stratification can be achieved by combining clinical data with these approaches in a machine-learning model

Association of Lipoprotein(a) With Atherosclerotic Plaque Progression

BACKGROUND: Lipoprotein(a) [Lp(a)] is associated with increased risk of myocardial infarction, although the mechanism for this observation remains uncertain. OBJECTIVES: This study aims to investigate whether Lp(a) is associated with adverse plaque progression. METHODS: Lp(a) was measured in patients with advanced stable coronary artery disease undergoing coronary computed tomography angiography at baseline and 12 months to assess progression of total, calcific, noncalcific, and low-attenuation plaque (necrotic core) in particular. High Lp(a) was defined as Lp(a) ≥ 70 mg/dL. The relationship of Lp(a) with plaque progression was assessed using linear regression analysis, adjusting for body mass index, segment involvement score, and ASSIGN score (a Scottish cardiovascular risk score comprised of age, sex, smoking, blood pressure, total and high-density lipoprotein [HDL]–cholesterol, diabetes, rheumatoid arthritis, and deprivation index). RESULTS: A total of 191 patients (65.9 ± 8.3 years of age; 152 [80%] male) were included in the analysis, with median Lp(a) values of 100 (range: 82 to 115) mg/dL and 10 (range: 5 to 24) mg/dL in the high and low Lp(a) groups, respectively. At baseline, there was no difference in coronary artery disease severity or plaque burden. Patients with high Lp(a) showed accelerated progression of low-attenuation plaque compared with low Lp(a) patients (26.2 ± 88.4 mm(3) vs −0.7 ± 50.1 mm(3); P = 0.020). Multivariable linear regression analysis confirmed the relation between Lp(a) and low-attenuation plaque volume progression (β = 10.5% increase for each 50 mg/dL Lp(a), 95% CI: 0.7%-20.3%). There was no difference in total, calcific, and noncalcific plaque volume progression. CONCLUSIONS: Among patients with advanced stable coronary artery disease, Lp(a) is associated with accelerated progression of coronary low-attenuation plaque (necrotic core). This may explain the association between Lp(a) and the high residual risk of myocardial infarction, providing support for Lp(a) as a treatment target in atherosclerosis

Coronary Atherosclerotic Plaque Activity and Future Coronary Events

This study was funded by a Wellcome Trust Senior Investigator Award (WT103782AIA). Image analysis was supported by National Institutes for Health (R34HL161195 and 1R01HL135557). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Wellcome Trust or the National Institutes of Health. The British Heart Foundation supports DEN (CH/09/002, RG/16/10/32375, RE/18/5/34216), MRD (FS/SCRF/21/32010), NLM (CH/F/21/90010, RG/20/10/34966, RE/18/5/34216) AJM (AA/18/3/34220) and MCW (FS/ICRF/20/26002) and DD (FS/RTF/20/30009, NH/19/1/34595, PG/18/35/33786, PG/15/88/31780, PG/17/64/33205). MRD is the recipient of the Sir Jules Thorn Award for Biomedical Research 2015 (15/JTA). PJS is supported by outstanding investigator award National Institutes for Health (R35HL161195). JK is supported by the National Science Centre 2021/41/B/NZ5/02630. EvB is supported by SINAPSE (www.sinapse.ac.uk). AB is supported by a Clinical Research Training Fellowships (MR/V007254/1). DD is supported by Chest Heart and Stroke Scotland (19/53), Tenovus Scotland (G.18.01), and Friends of Anchor and Grampian NHS-Endowments. The Edinburgh Clinical Research Facilities, Edinburgh Imaging facility and Edinburgh Clinical Trials Unit are supported by the National Health Service Research Scotland through National Health Service Lothian Health Board. The Leeds Clinical Research Facilities are supported by the UK National Institute for Health Research (NIHR) via its Clinical Research Facility programme. The work at Cedars-Sinai Medical Center (the Los Angeles site) was supported in part by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation. For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. The Chief Investigator and Edinburgh Clinical Trials Unit had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.Peer reviewedPostprin