Cardiovascular diagnosis and therapy最新文献

Background: We aimed to examine whether intra-individual variability in traditional risk factors affects the progression of atherosclerosis on subsequent coronary computed tomography angiography (CCTA).

Methods: We conducted a retrospective cohort study using asymptomatic health examination cohort data from Haeundae Paik Hospital in Korea collected between 2010-2020. A total of 387 adults met the inclusion criteria of having at least two CCTAs without specific symptoms with an interval of more than one year and having completed three or more health examinations. Visit-to-visit variability was evaluated using the average real variability (ARV) of body mass index, waist circumference, systolic and diastolic blood pressure, and plasma glucose, total cholesterol, triglyceride, high-density lipoprotein (HDL)-cholesterol, and low-density lipoprotein (LDL)-cholesterol. Progression of coronary artery atherosclerosis was defined as worsening of coronary artery stenosis from baseline to final CCTA. ARV values for various metabolic parameters were stratified into quartiles, and hazard ratios (HRs) and 95% confidence intervals (CIs) for coronary atherosclerosis progression were analyzed using multiple Cox proportional hazards models.

Results: There were 126 cases of coronary artery stenosis progression (32.56%) assessed using the Coronary Artery Disease Reporting and Data System during a mean follow up of 3.91 (range, 1-9) years. In the multivariate analysis comparing ARV quartiles for LDL-cholesterol after adjusting for covariates, individuals with higher variability showed an increased risk of stenosis progression: HR 2.23 (95% CI: 1.33-3.73) for the third quartile, HR 1.56 (95% CI: 0.91-2.66) for the fourth quartile (P for trend =0.005). Triglycerides also showed a significant linear trend (P for trend =0.04), and Q4 had a greater risk of stenosis progression (HR, 2.09; 95% CI: 1.24-3.52). Meanwhile, the risk of stenosis progression was significantly reduced as the ARV of HDL-cholesterol increased: HR 0.56 (95% CI: 0.35-0.89) for the third quartile, HR 0.47 (95% CI: 0.27-0.81) for the fourth quartile (P for trend =0.01).

Conclusions: High variability in LDL-cholesterol and triglyceride was an independent predictor of coronary artery stenosis progression on subsequent CCTA in our cohort. This finding highlights the importance of maintaining stable state to effectively prevent the progression of coronary artery stenosis in clinical settings.

Background: During the COVID-19 pandemic, guideline documents on the management of anticoagulation were rapidly published. However, these documents did not follow a structured methodology, and significant differences existed between the guidelines. The aim of this expert consensus was to provide recommendations on the clinical management of oral anticoagulation in patients in the context of the COVID-19 pandemic.

Methods: A two-round Delphi study was conducted using an online survey. In the first round, panellists expressed their level of agreement with the items on a 9-point Likert scale. Items were selected if they received approval from ≥66.6% of panellists and if they were agreed by the scientific committee. In the second round, panellists revaluated those items that did not meet consensus in the first round.

Results: A total of 147 panellists completed the first round, and 144 of them completed the second round. Consensus was reached on 161 items included in five dimensions. These dimensions addressed: (I) management of anticoagulation in patients with atrial fibrillation (AF) without mechanical valves or moderate/severe mitral stenosis during COVID-19 infection; (II) thromboprophylaxis in patients hospitalised for COVID-19; (III) management of anticoagulation at hospital discharge/after COVID-19; (IV) anticoagulation monitoring in the COVID-19 pandemic setting; and (V) role of telemedicine in the management and follow-up of patients with AF in the COVID-19 pandemic setting.

Conclusions: These areas of collective agreement could specially guide clinicians in making decisions regarding anticoagulation in patients with COVID-19 during hospitalisation and at discharge, where results from clinical trials are still limited and, in some cases, conflicting.

Background: Atherosclerotic plaques can cause carotid artery stenosis, and "vulnerable plaques" can even lead to ischemic stroke. The objective of this study was to assess the accuracy of superb microvascular imaging (SMI) for the detection of carotid intraplaque neovascularization (IPN) in patients with atherosclerotic plaques.

Methods: We searched the Cochrane Library, Embase, Medline, and Wanfang databases until January 17, 2023. We included original studies with information on diagnostic accuracy of SMI for the evaluation of carotid IPN. The primary outcome was the accuracy of SMI for detecting carotid IPN. A meta-analysis was performed to estimate the accuracy of each parameter. We used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) to assess the risk of bias for each included article. Meta-regression was performed to determine items that may have contributed to heterogeneity in the sensitivity or specificity of the test.

Results: This meta-analysis included 20 studies with 1,589 carotid plaques in 1,225 patients. The analysis showed a sensitivity and specificity of SMI for detecting IPN of 93% [95% confidence interval (CI): 87-96%] and 80% (95% CI: 71-87%), respectively. The risk of bias across the QUADAS-2 domains was low. Only the proportion of dyslipidemia influenced the estimates of sensitivity and specificity.

Conclusions: This review suggests that SMI has a good diagnostic performance for detecting carotid IPN. The very high sensitivity with excellent post-test probability indicated that SMI can be recommended to screen for carotid IPN among patients with carotid plaques.

Background: Non-contrast T1-weighted imaging (T1WI) with cardiac magnetic resonance enables to evaluate the intensity of coronary plaque. Plaque-to-myocardial signal intensity ratio (PMR) has been shown to associate with an elevated risk of future coronary events. Of note, PMR >1.4 is a best cut-off value to identify high-risk plaque causing future coronary events. One recent study has reported intraluminal thrombus as a contributor to PMR. However, whether plaque material itself is associated with PMR has not been fully characterized yet. We present three cases with coronary artery stenosis evaluated by non-contrast T1WI-magnetic resonance imaging, optical coherence tomography (OCT) and near-infrared spectroscopy (NIRS)-intravascular ultrasound (IVUS) imaging.

Case description: Case 1 exhibited one lesion with high PMR (2.79) at the proximal segment of left anterior descending (LAD) artery. OCT imaging did not identify any obvious intra-luminal thrombus but the presence of lipid-rich plaque harboring cholesterol crystal at the corresponding lesion. In addition, an elevated maximum 4-mm lipid-core burden index (maxLCBI_4mm) (=873) was observed at this lesion by NIRS/IVUS imaging. In case 2, PMR of coronary stenosis at the middle segment of LAD artery was 1.88. This lesion harboured lipidic materials without any thrombus on OCT imaging. NIRS-derived maxLCBI_4mm was 725. Case 3 had a severe stenosis at the middle segment of LAD artery. This lesion exhibited a low PMR (0.90). On OCT and NIRS/IVUS imaging, this lesion was characterized as the presence of small lipid arc with a low maxLCBI_4mm (=386).

Conclusions: These cases showed the possible relationship of T1WI-derived PMR with the degree of lipidic plaque components.

Background: Timely reperfusion therapy is recommended for patients with ST-segment elevation myocardial infarction (STEMI), and system delay <90 minutes and door-to-device (D2D) time <60 minutes are recommended by the 2017 ESC Guidelines for the management of STEMI patients and have been proposed as a performance measure for triaging patients for primary percutaneous coronary intervention (PCI). However, previous research produced contradictory results regarding the association between D2D time and mortality. Therefore, this study aimed to examine the associations between D2D time and mortality in Thailand.

Methods: This cohort study included STEMI patients treated with primary PCI in 39 PCI centres in Thailand from February 27, 2018, to August 1, 2019. Patients were eligible if they met the following criteria: primary STEMI diagnosis, symptom onset within 12 hours, and ST-segment elevation of at least 0.1 mV in 2 or more contiguous leads (at least 0.2 mV in V1-V3) or a new left bundle branch block.

Results: Within 12 hours of symptom onset, 3,874 patients underwent primary PCI. The median D2D time was 54 minutes [interquartile range (IQR) 29-90], and there was a significant difference between patients transferred from other hospitals (44 minutes, IQR 25-77, n=2,871) and patients presented directly to PCI centres (81 minutes, IQR 56-129, n=1,003) (P<0.001). Overall, in-hospital mortality was 7.8%. In a multivariable analysis, adjusting for other predictors of mortality and stratifying according to intervals of D2D time, cumulative in-hospital mortality was significantly higher in patients with a D2D time greater than 90 minutes [hazard ratio (HR) 1.5, 95% confidence interval (CI): 1.0-2.1, P=0.046] but not associated with D2D time shorter than 60 minutes (HR 1.2, 95% CI: 0.8-1.8, P=0.319).

Conclusions: A D2D time greater than 90 minutes was related to in-hospital mortality in patients with STEMI treated with primary PCI, but a D2D time less than 60 minutes was not consistently associated with D2D time-improved survival in real-world, contemporary practice in Thailand.

Background: There are few reports on the postoperative left ventricular mass (LVM), aortic valve area (AVA), and pressure gradient (PG) after surgical aortic valve replacement (SAVR) and transcatheter aortic valve replacement (TAVR) in Japan. We aimed to compare the postoperative LVM, AVA, stroke volume (SV), PG, and long-term outcomes between patients undergoing SAVR and TAVR procedures from single center in Japan.

Methods: This was a retrospective cohort study. We included 107 patients who underwent simple SAVR between January 2012 and May 2022 (SAVR group, n=107) and 274 who underwent TAVR between January 2016 and May 2022 (TAVR group, n=274). The overall mean follow-up periods was 28.8±25.9 months (median: 24 months; range, 0.03-117 months).

Results: The aortic valve mean PG (mmHg) was significantly smaller in the TAVR group than in the SAVR group (P<0.001). The AVA index (cm²/m²) was significantly larger in the TAVR group than in the SAVR group (P<0.001). The SV index (mL/m²) was significantly smaller in the SAVR group than in the TAVR group (P=0.02). The LVM index (LVMI) (g/m²) was significantly smaller in the SAVR group than in the TAVR group (P<0.001). The incidence of mild or higher postoperative paravalvular leak (PVL) and pacemaker implantation were significantly higher in the TAVR group. The 5-year postoperative mortality, re-hospitalization, and major adverse cerebral and cardiovascular events (MACCEs) were significantly better in the SAVR group.

Conclusions: The postoperative aortic valve PG, AVA, and SV were better in the TAVR group; however, LVM regression and postoperative outcomes were better in the SAVR group.

Background: Digital subtraction angiography (DSA) is an important technique for diagnosis of moyamoya disease (MMD) or moyamoya syndrome (MMS), and computed tomography perfusion (CTP) is essential for assessing intracranial blood supply. The aim of this study was to assess whether radiomics features based on images of DSA could predict the mean transit time (MTT; outcome of CTP) using machine learning models.

Methods: The DSA images and MTT values of adult patients with MMD or MMS, according to the diagnostic guidelines for MMD, as well as control cases, were retrospectively collected in the Guangdong Provincial People's Hospital between January 2018 and December 2020. A total of 93 features were extracted from the images of each case through 3-dimensional (3D) slicer. After features preprocessing and filtering, 3-4 features were selected by the least absolute shrinkage and selection operator (LASSO) regression algorithm. Prediction models were established using random forest (RF) and support vector machine (SVM) for MTT values. Single-factor receiver operating characteristic (ROC) curve analysis and partial-dependence (PD) profiles were conducted to investigate selected features and prediction models.

Results: Our results showed that prediction models based on RF models had the best performance in frontal lobe {area under the curve (AUC) [95% confidence interval (CI)] =1.000 (1.000-1.000)], parietal lobe [AUC (95% CI) =1.000 (1.000-1.000)], and basal ganglia/thalamus [AUC (95% CI) =0.922 (0.797-1.000)] in the test set, whereas the SVM model performed the best in the temporal lobe [AUC (95% CI) =0.962 (0.876-1.000)] in the test set. The AUC values in the test set were greater than 0.9. The PD profiles showed good robustness and consistency.

Conclusions: Prediction models based on radiomics features extracted from DSA images demonstrate excellent performance in predicting MTT in patients with MMD or MMS, which may provide guidance for future clinical practice.