Cardiovascular diagnosis and therapy最新文献

Indigenous Australians are known to have a higher prevalence of coronary artery disease (CAD) than non-Indigenous counterparts. Atherogenic lipid profiles, characterised by low serum levels of high-density lipoprotein (HDL) and higher serum triglycerides, have been shown to be more prevalent in Indigenous Australians. The use of computed tomography coronary angiography (CTCA) for risk stratification and diagnosis of CAD has been validated in moderate risk populations, but limited data exists in specific high-risk populations such as Indigenous Australians. Through a retrospective study of patient records, we aimed to confirm if an atherogenic lipid profile occurred in Indigenous Australians undergoing CTCA in the Northern Territory of Australia and if so, whether this correlated with the prevalence or burden of CAD. We demonstrate that Indigenous Australians have similar prevalence (52.6% vs. 50.3%, P=0.80) and burden of CAD (Leaman score 6.03±4.66 vs. 6.96±4.82, P=0.44) on CTCA as non-Indigenous patients, but were 8 years younger (41.9±8.9 vs. 50.0±11.9 years, P<0.001) at the time of examination. We confirmed the presence of an atherogenic lipid profile in Indigenous patients and showed low serum-HDL was associated with very premature (patients aged 18-35 years) CAD in comparison to premature (patients aged 36-55 years) and mature-onset (patients aged 56 years and older) CAD (0.71±0.25 vs. 1.09±0.35 vs. 1.18±0.36 mmol/L, P=0.009). Future clinical guidelines should consider the role of CTCA in Indigenous Australians and whether younger patients may benefit. The causes of premature CAD, including atherogenic lipid profiles, require an ongoing focus in order to achieve equitable cardiovascular outcomes for Indigenous and non-Indigenous Australians.

Background: Coronary chronic total occlusion (CTO) increases the risk of developing major adverse cardiovascular events (MACE) and cardiogenic shock. Coronary computed tomography angiography (CCTA) is a safe, noninvasive method to diagnose CTO lesions. With the development of artificial intelligence (AI), AI has been broadly applied in cardiovascular images, but AI-based detection of CTO lesions from CCTA images is difficult. We aim to evaluate the performance of AI in detecting the CTO lesions of coronary arteries based on CCTA images.

Methods: We retrospectively and consecutively enrolled patients with 50% stenosis, 50-99% stenosis, and CTO lesions who received CCTA scans between June 2021 and June 2022 in Beijing Anzhen Hospital. Four-fifths of them were randomly assigned to the training dataset, while the rest (1/5) were randomly assigned to the testing dataset. Performance of the AI-assisted CCTA (CCTA-AI) in detecting the CTO lesions was evaluated through sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and receiver operating characteristic analysis. With invasive coronary angiography as the reference, the diagnostic performance of AI method and manual method was compared.

Results: A total of 537 patients with 1,569 stenotic lesions (including 672 lesions with <50% stenosis, 493 lesions with 50-99% stenosis, and 404 CTO lesions) were enrolled in our study. CCTA-AI saved 75% of the time in post-processing and interpreting the CCTA images when compared to the manual method (116±15 vs. 472±45 seconds). In the testing dataset, the accuracy of CCTA-AI in detecting CTO lesions was 86.2% (79.0%, 90.3%), with the area under the curve of 0.874. No significant difference was found in detecting CTO lesions between AI and manual methods (P=0.53).

Conclusions: AI can automatically detect CTO lesions based on CCTA images, with high diagnostic accuracy and efficiency.

Background: The preoperative predictors of residual or recurrent tricuspid regurgitation (TR) after cone reconstruction (CR) remains unclear in patients with Ebstein anomaly (EA). We aimed to determine the predictive value of right ventricular longitudinal strain, assessed using cardiac magnetic resonance (CMR) imaging, for residual or recurrent TR after CR in patients with EA.

Methods: This single-centre, retrospective study analysed data from 48 patients with EA [mean ± standard deviation (SD), age, 35.0±13.6 years; 13 males] who underwent CMR before CR between January 2017 and February 2023. Two-dimensional colour Doppler echocardiography was performed before CR and mid-term (>6 months) after CR to evaluate the degree of TR in patients with EA. Thirty healthy volunteers served as controls. Univariate and multivariate logistic regression analyses were performed to identify CMR predictors of moderate or severe TR >6 months after CR.

Results: Mid-term postoperative results revealed severe, moderate, and mild TR in 8 (17%), 7 (15%), and 33 (69%) patients, respectively. For patients with EA and moderate or severe TR after CR, left ventricular global longitudinal strain (GLS), left ventricular ejection fraction, right ventricular global longitudinal strain (RVGLS), and right ventricular ejection fraction (RVEF) were significantly worse compared to patients with mild TR (all P<0.05). Multivariate logistic regression analyses revealed that RVGLS was independently associated with moderate or severe TR >6 months after CR [odds ratio (OR) 1.193, 95% confidence interval (CI): 1.025-1.388; P=0.02].

Conclusions: RVGLS was a significant predictor of moderate or severe TR >6 months after CR. This finding emphasizes that early and accurate measurement of RV function may help to identify patients at high risk for severe residual or recurrent TR.

Background and objective: The introduction of photon-counting computed tomography (PCCT) represents the most recent groundbreaking advancement in clinical computed tomography (CT). PCCT has the potential to overcome the limitations of traditional CT and to provide new quantitative imaging information. This narrative review aims to summarize the technical principles, benefits, and challenges of PCCT and to provide a concise yet comprehensive summary of the applications of PCCT in the domain of coronary imaging.

Methods: A review of PubMed, Scopus, and Google Scholar was performed until October 2023 by using relevant keywords. Articles in English were considered.

Key content and findings: The main advantages of PCCT over traditional CT are enhanced spatial resolution, improved signal and contrast characteristics, diminished electronic noise and image artifacts, lower radiation exposure, and multi-energy capability with enhanced material discrimination. These key characteristics have made room for improved assessment of plaque volume and severity of stenosis, more precise assessment of coronary artery calcifications, also preserved in the case of a reduced radiation dose, improved assessment of plaque composition, possibility to provide details regarding the biological processes occurring within the plaque, enhanced quality and accuracy of coronary stent imaging, and improved radiomic analyses.

Conclusions: PCCT can significantly impact diagnostic and clinical pathways and improve the management of patients with coronary artery diseases (CADs).

Background: Wall shear stress (WSS) is related to the pathogenesis of atherosclerosis. WSS is affected by a variety of hemodynamic factors, and there is still a lack of accurate and objective methods for measuring it. This study sought to evaluate hemodynamic changes in WSS_{maximum (max)}, WSS_mean, WSS_{minimum (min)} in the common carotid artery of healthy adults of different ages using vascular vector flow mapping (VFM).

Methods: A retrospective analysis was conducted on 70 healthy volunteers aged 20-89 years who were recruited from our Ultrasound Department between February 2021 and June 2021. An ultrasound system with a 3-15 MHz probe was used to determine regions of interest (ROIs) of the common carotid artery. VFM-based WSS measurements were obtained by selecting ROIs with optimal image quality from three full cardiac cycles. The participants were divided into the following seven age groups: the 20s group, the 30s group, the 40s group, the 50s group, the 60s group, the 70s group, and the 80s group. The WSS parameters were compared among the age groups. An analysis of variance or a Kruskal-Wallis test was used to evaluate the difference among the groups, and a Pearson analysis and linear regression were used for the correlation and trend analysis.

Results: The WSS parameters were quantified using vascular VFM software. The WSS_max, WSS_mean, WSS_min differed among the age groups and gradually decreased with age, the elderly were significantly lower than the young. The Pearson correlation coefficient of the WSS_max and age was -0.556 (P<0.001), that of the WSS_mean and age was -0.461 (P<0.001), and that of the WSS_min and age was -0.308 (P<0.001). The WSS parameters with age are negatively correlated the carotid intima-media thickness differed between the groups.

Conclusions: The carotid WSS_max, WSS_mean, WSS_min can be quantitatively and visually analyzed using the vascular VFM technique. In healthy adults of different ages, the carotid WSS_max, WSS_mean, WSS_min decreased with age. Our findings about the normal values of carotid WSS maybe have clinical reference value for future studies.

Background: Pulmonary hypertension (PH) is a critical health issue marked by high blood pressure in the pulmonary arteries, with limited data on its clinical characteristics in the Tibetan population. The objective of this study was to examine the clinical characteristics of PH patients among Tibetan population residing in Chaya County, Changdu, Tibet.

Methods: This was a retrospective cross-sectional study. A total of 94 PH patients diagnosed via echocardiography at the Internal Medicine Department of Chaya County People's Hospital in Changdu (Tibet, China) between March 2019 and October 2020 were included. Additionally, 52 non-PH inpatients were selected as the control group. Patient medical records were reviewed for demographic and clinical data, lab results, and echocardiographic findings. Student's t-test/chi-squared test between PH and control group, one-way analysis of variance (ANOVA) among control and PH subgroups, Pearson's and Spearman's correlation coefficient were used to analysis the results.

Results: Out of 1,689 inpatients in the Internal Medicine Department, 94 were identified as PH patients for analysis. The average hemoglobin level among PH patients (150.64±21.67 g/L) was similar to that observed in the normal population (146.65±17.51 g/L) at high altitude (P=0.28). Abnormal liver function indexes were observed, with 51.06% of PH patients exhibiting hyperuricemia (P<0.001 compared to control's 15.38%). The PH group demonstrated significantly elevated red blood cell distribution width (RDW)-standard deviation (50.59±6.49 vs. 43.67±3.40 fL, P<0.001) and RDW-coefficient of variation of (16.18%±3.04% vs. 13.52%±1.32%, P<0.001), along with a decreased platelet level compared to the control group [(202.55±73.67) vs. (256.63±72.85) ×10⁹/L]. Furthermore, echocardiographic indicators related to right heart function showed correlations with red blood cell count, bilirubin, albumin, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol (multiple significant correlation coefficient r, magnitude from 0.22 to 0.54).

Conclusions: Chronic pulmonary disease and left heart disease were identified as common etiologies of PH among Tibetan patients residing in high-altitude regions. The Tibetan population residing in high-altitude regions and diagnosed with PH displayed abnormal changes in numerous liver functional and metabolic indices, which were correlated with the morphological indices observed via cardiac ultrasound.

Background: No-reflow (NRF) phenomenon is a significant challenge in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (pPCI). Accurate prediction of NRF may help improve clinical outcomes of patients. This retrospective study aimed at creating an optimal model based on machine learning (ML) to predict NRF in these patients, with the additional objective of guiding pre- and intra-operative decision-making to reduce NRF incidence.

Methods: Data were collected from 321 STEMI patients undergoing pPCI between January 2022 and May 2023, with the dataset being randomly divided into training and internal validation sets in a 7:3 ratio. Selected features included pre- and intra-operative demographic data, laboratory parameters, electrocardiogram, comorbidities, patients' clinical status, coronary angiographic data, and intraoperative interventions. Post comprehensive feature cleaning and engineering, three logistic regression (LR) models [LR-classic, LR-random forest (LR-RF), and LR-eXtreme Gradient Boosting (LR-XGB)], a RF model and an eXtreme Gradient Boosting (XGBoost) model were developed within the training set, followed by performance evaluation on the internal validation sets.

Results: Among the 261 patients who met the inclusion criteria, 212 were allocated to the normal flow group and 49 to the NRF group. The training group consisted of 183 patients, while the internal validation group included 78 patients. The LR-XGB model, with an area under the curve (AUC) of 0.829 [95% confidence interval (CI): 0.779-0.880], was selected as the representative model for logistic regression analyses. The LR model had an AUC slightly lower than XGBoost model (AUC 0.835, 95% CI: 0.781-0.889) but significantly higher than RF model (AUC 0.731, 95% CI: 0.660-0.802). Internal validation underscored the unique advantages of each model, with the LR model demonstrating the highest clinical net benefit at relevant thresholds, as determined by decision curve analysis. The LR model encompassed seven meaningful features, and notably, thrombolysis in myocardial infarction flow after initial balloon dilation (TFAID) was the most impactful predictor in all models. A web-based application based on the LR model, hosting these predictive models, is available at https://l7173o-wang-lyn.shinyapps.io/shiny-1/.

Conclusions: A LR model was successfully developed through ML to forecast NRF phenomena in STEMI patients undergoing pPCI. A web-based application derived from the LR model facilitates clinical implementation.