Safety and incremental prognostic value of stress cardiovascular magnetic resonance in patients with known chronic kidney disease.

BACKGROUND: Cardiovascular disease (CVD) is the main cause of mortality in patients with chronic kidney disease (CKD). Although several studies have demonstrated the consistently high prognostic value of stress cardiovascular magnetic resonance (CMR), its prognostic value in patients with CKD is not well established. We aimed to assess the safety and the incremental prognostic value of vasodilator stress perfusion CMR in consecutive symptomatic patients with known CKD. METHODS: Between 2008 and 2021, we conducted a retrospective dual center study with all consecutive symptomatic patients with known stage 3 CKD, defined by estimated glomerular filtration rate (eGFR) between 30 and 60 ml/min/1.73 m2, referred for vasodilator stress CMR. All patients with eGFR < 30 ml/min/1.73 m2 (n = 62) were excluded due the risk of nephrogenic systemic fibrosis. All patients were followed for the occurrence of major adverse cardiovascular events (MACE) defined as cardiac death or recurrent nonfatal myocardial infarction (MI). Cox regression analysis was used to determine the prognostic value of stress CMR parameters. RESULTS: Of 825 patients with known CKD (71.4 ± 8.8 years, 70% men), 769 (93%) completed the CMR protocol. Follow-up was available in 702 (91%) (median follow-up 6.4 (4.0-8.2) years). Stress CMR was well tolerated without occurrence of death or severe adverse event related to the injection of gadolinium or cases of nephrogenic systemic fibrosis. The presence of inducible ischemia was associated with the occurrence of MACE (hazard ratio [HR] 12.50; 95% confidence interval [CI] 7.50-20.8; p < 0.001). In multivariable analysis, ischemia and late gadolinium enhancement were independent predictors of MACE (HR 15.5; 95% CI 7.72 to 30.9; and HR 4.67 [95% CI 2.83-7.68]; respectively, both p < 0.001). After adjustment, stress CMR findings showed the best improvement in model discrimination and reclassification above traditional risk factors (C-statistic improvement: 0.13; NRI = 0.477; IDI = 0.049). CONCLUSIONS: In patients with known stage 3 CKD, stress CMR is safe and its findings have an incremental prognostic value to predict MACE over traditional risk factors.

Left atrioventricular coupling index assessed using cardiac CT as a prognostic marker of cardiovascular death.

PURPOSE: The purpose of this study was to investigate the prognostic value of left atrioventricular coupling index (LACI) assessed by cardiac computed tomography (CT), to predict cardiovascular death in consecutive patients referred for cardiac CT with coronary analysis. MATERIALS AND METHODS: Between 2010 and 2020, we conducted a single-centre study with all consecutive patients without known cardiovascular disease referred for cardiac CT. LACI was defined as the ratio of left atrial to left ventricle end-diastolic volumes. The primary outcome was cardiovascular death. Cox regressions were used to evaluate the association between LACI and primary outcome after adjustment for traditional risk factors and cardiac CT angiography findings. RESULTS: In 1,444 patients (mean age, 70 ± 12 [standard deviation] years; 43% men), 67 (4.3%) patients experienced cardiovascular death after a median follow-up of 6.8 (Q1, Q3: 5.9, 9.1) years. After adjustment, LACI was positively associated with the occurrence of cardiovascular death (adjusted hazard ratio [HR], 1.07 [95% CI: 1.05-1.09] per 1% increment; P < 0.001), and all-cause death (adjusted HR, 1.05 [95% CI: 1.03-1.07] per 1% increment; P <0.001). After adjustment, a LACI ≥ 25% showed the best improvement in model discrimination and reclassification for predicting cardiovascular death above traditional risk factors and cardiac CT findings (C-statistic improvement: 0.27; Nnet reclassification improvement = 0.826; Integrative discrimination index =0.209, all P < 0.001; likelihood-ratio-test, P < 0.001). CONCLUSION: LACI measured by cardiac CT is independently associated with cardiovascular death and all-cause death in patients without known cardiovascular disease referred for cardiac CT, with an incremental prognostic value over traditional risk factors and cardiac CT findings.

Safety, feasibility, and prognostic value of stress perfusion CMR in patients with MR-conditional pacemaker.

AIMS: To assess the safety, feasibility, and prognostic value of stress cardiovascular magnetic resonance (CMR) in patients with pacemaker (PM). METHODS AND RESULTS: Between 2008 and 2021, we conducted a bi-centre longitudinal study with all consecutive patients with MR-conditional PM referred for vasodilator stress CMR at 1.5 T in the Institut Cardiovasculaire Paris Sud and Lariboisiere University Hospital. They were followed for the occurrence of major adverse cardiovascular events (MACE) defined as cardiac death or non-fatal myocardial infarction. Cox regression analyses were performed to determine the prognostic value of CMR parameters. The quality of CMR was rated by two observers blinded to clinical details. Of 304 patients who completed the CMR protocol, 273 patients (70% male, mean age 71 ± 9 years) completed the follow-up (median [interquartile range], 7.1 [5.4-7.5] years). Among those, 32 experienced a MACE (11.7%). Stress CMR was well tolerated with no significant change in lead thresholds or pacing parameters. Overall, the image quality was rated good or excellent in 84.9% of segments. Ischaemia and late gadolinium enhancement (LGE) were significantly associated with the occurrence of MACE (hazard ratio, HR: 11.71 [95% CI: 4.60-28.2]; and HR: 5.62 [95% CI: 2.02-16.21], both P < 0.001). After adjustment for traditional risk factors, ischaemia and LGE were independent predictors of MACE (HR: 5.08 [95% CI: 2.58-14.0]; and HR: 2.28 [95% CI: 2.05-3.76]; both P < 0.001). CONCLUSION: Stress CMR is safe, feasible and has a good discriminative prognostic value in consecutive patients with PM.

Machine-Learning Score Using Stress CMR for Death Prediction in Patients With Suspected or Known CAD.

BACKGROUND: In patients with suspected or known coronary artery disease, traditional prognostic risk assessment is based on a limited selection of clinical and imaging findings. Machine learning (ML) methods can take into account a greater number and complexity of variables. OBJECTIVES: This study sought to investigate the feasibility and accuracy of ML using stress cardiac magnetic resonance (CMR) and clinical data to predict 10-year all-cause mortality in patients with suspected or known coronary artery disease, and compared its performance with existing clinical or CMR scores. METHODS: Between 2008 and 2018, a retrospective cohort study with a median follow-up of 6.0 (IQR: 5.0-8.0) years included all consecutive patients referred for stress CMR. Twenty-three clinical and 11 stress CMR parameters were evaluated. ML involved automated feature selection by random survival forest, model building with a multiple fractional polynomial algorithm, and 5 repetitions of 10-fold stratified cross-validation. The primary outcome was all-cause death based on the electronic National Death Registry. The external validation cohort of the ML score was performed in another center. RESULTS: Of 31,752 consecutive patients (mean age: 63.7 ± 12.1 years, and 65.7% male), 2,679 (8.4%) died with 206,453 patient-years of follow-up. The ML score (ranging from 0 to 10 points) exhibited a higher area under the curve compared with Clinical and Stress Cardiac Magnetic Resonance score, European Systematic Coronary Risk Estimation score, QRISK3 score, Framingham Risk Score, and stress CMR data alone for prediction of 10-year all-cause mortality (ML score: 0.76 vs Clinical and Stress Cardiac Magnetic Resonance score: 0.68, European Systematic Coronary Risk Estimation score: 0.66, QRISK3 score: 0.64, Framingham Risk Score: 0.63, extent of inducible ischemia: 0.66, extent of late gadolinium enhancement: 0.65; all P < 0.001). The ML score also exhibited a good area under the curve in the external cohort (0.75). CONCLUSIONS: The ML score including clinical and stress CMR data exhibited a higher prognostic value to predict 10-year death compared with all traditional clinical or CMR scores.