Enhancing pre-transplant cardiac assessment: Validation and utility of the CAD-LT score with CCTA in liver transplant candidates.

BACKGROUND: Coronary computed tomography angiography (CCTA) is increasingly being used in the preoperative workup for liver transplantation (LT). We sought to assess the utility of integrating CCTA with the novel CAD-LT (Coronary Artery Disease in Liver Transplantation) score and its impact on reducing the need for invasive coronary angiography prior to LT. METHODS: We conducted a retrospective cohort study of consecutive patients (age ≥ 18 years) who underwent CCTA for LT workup between 2011 and 2018 at the Victorian Liver Transplant Unit, Melbourne, Australia. CAD-LT scores, a traditional risk factor-based criteria, were calculated, and patients stratified as low-, intermediate- or high-risk. RESULTS: Overall, 229 patients underwent CCTA. The mean age was 66 ± 5 years (82% male) with a modest-to-high risk factor burden (diabetes, 53%; hypertension, 46%; current or former smoker, 62%). The mean CAD-LT score of our cohort was 12.4 ± 4.0. No patients were classified as low-risk, 49 patients (21.4%) were deemed intermediate-risk and 180 patients (78.6%) were deemed high-risk. A high CAD-LT score (≥ 9) showed high sensitivity (95.3% [95% CI 86-98%]) and modest specificity (27.8% [95% CI 21-35%]) for the detection of obstructive coronary artery disease on CCTA, with a negative predictive value of 94%. Following multidisciplinary discussions, only 41 patients (18%) of patients proceeded to ICA of which 27% received percutaneous coronary intervention. CONCLUSIONS: The use of CCTA in patients deemed intermediate- to high-risk by the CAD-LT score has the potential to reduce the need for invasive coronary angiography in patients undergoing LT workup.

Cardiac Risk Stratification in Liver Transplantation: Results of a Tiered Assessment Protocol Based on Traditional Cardiovascular Risk Factors.

Coronary artery disease (CAD) confers increased perioperative risk in patients undergoing liver transplantation (LT). Although routine screening for CAD is recommended, there are limited data on the effectiveness of screening strategies. We evaluated the safety and efficacy of a 3-tiered cardiac risk-assessment protocol that stratifies patients based on age and traditional cardiac risk factors. We peformed a single-center, prospective, observational study of consecutive adult patients undergoing LT assessment (2010-2017). Patients were stratified into low-risk (LR), intermediate-risk (IR), or high-risk (HR) cardiac groups and received standardized investigations with selective use of transthoracic echocardiography (TTE), dobutamine stress echocardiography (DSE), computed tomography coronary angiography (CTCA), and coronary angiography (CA). Primary outcomes were cardiac events (CEs) and cardiovascular death up to 30 days after LT. Overall, 569 patients were included, with 76 patients identified as LR, 256 as IR, and 237 as HR. Cardiac risk factors included diabetes mellitus (26.0%), smoking history (47.3%), hypertension (17.8%), hypercholesterolemia (7.2%), family (17.0%) or prior history of heart disease (6.0%), and obesity (27.6%). Of the patients, 42.0% had ≥2 risk factors. Overall compliance with the protocol was 90.3%. Abnormal findings on TTE, DSE, and CTCA were documented in 3, 23, and 44 patients, respectively, and 12 patients were not listed for transplantation following cardiac assessment (1 LR, 2 IR, and 9 HR). Moderate or severe CAD was identified in 25.4% of HR patients on CTCA following a normal DSE. CEs were recorded in 7 patients (1.2%), with 2 cardiovascular deaths (0.4%). Cardiac risk stratification based on traditional cardiac risk factors with the selective use of DSE, CTCA, and CA is a safe and feasible approach that results in a low perioperative cardiac event rate.

A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre.

Retinal blood vessels provide information on the risk of cardiovascular disease (CVD). Here, we report the development and validation of deep-learning models for the automated measurement of retinal-vessel calibre in retinal photographs, using diverse multiethnic multicountry datasets that comprise more than 70,000 images. Retinal-vessel calibre measured by the models and by expert human graders showed high agreement, with overall intraclass correlation coefficients of between 0.82 and 0.95. The models performed comparably to or better than expert graders in associations between measurements of retinal-vessel calibre and CVD risk factors, including blood pressure, body-mass index, total cholesterol and glycated-haemoglobin levels. In retrospectively measured prospective datasets from a population-based study, baseline measurements performed by the deep-learning system were associated with incident CVD. Our findings motivate the development of clinically applicable explainable end-to-end deep-learning systems for the prediction of CVD on the basis of the features of retinal vessels in retinal photographs.

Accuracy of wrist-worn heart rate monitors for rate control assessment in atrial fibrillation.

BACKGROUND: Wrist-worn heart rate (HR) monitors are increasingly popular. A paucity of data exists on their accuracy in atrial fibrillation (AF) in ambulatory patients. We sought to assess the HR accuracy of two commercially available smart watches [SW] (Fitbit Charge HR [FB] and Apple Watch Series 3 [AW]) compared with Holter monitoring in an ambulant patient cohort. METHODS: Thirty-two participants ≥18 years referred for 24-hour Holter monitoring were prospectively recruited. Each participant was randomly allocated to wear either a FB or AW along with their Holter monitor. RESULTS: Across all devices, 53,288 heart rate values were analysed from 32 participants. Twenty wore the AW (17 had persistent AF and 3 had sinus rhythm [SR]) while 12 participants wore the FB (9 in persistent AF and 3 in SR). Participants in SR demonstrated strong agreement compared to Holter monitoring (bias <1 beat, limits of agreement [LoA] -11 to 11 beats). In AF, both devices underestimated HR measurements (bias -9 beats, LoA -41 to 23). The degree of underestimation was more pronounced when HR > 100 bpm (bias of -28 beats for HR range 100-120 bpm, -48 for 120-140 bpm, and -69 for >140 bpm) compared to a slower HR (bias of -6 for HR range 80-100 bpm, <1 for 60-80 bpm, and -1 for <60 bpm). CONCLUSION: In ambulatory patients, smartwatches underestimated HR in AF particularly at HR ranges >100 bpm. Further improvements in device technology are needed before integrating them into the clinical management of rate control in AF.