Visit-to-visit variability of systolic blood pressure predicts all-cause mortality in patients received percutaneous coronary intervention with drug-eluting stents.

Blood pressure (BP) and its variability are associated with atherosclerotic disease and cardiovascular events. The prognostic implications of outpatient clinic visit-to-visit blood pressure variability (BPV) are unknown in patients undergoing percutaneous coronary intervention (PCI) with drug-eluting stents (DES). A total of 1,463 patients undergoing PCI with DES were consecutively enrolled from January 2009 to December 2013. We analyzed the 1,234 patients, who measured clinic BP more than three times during the first year after PCI. The BPV is determined by standard deviation of systolic and diastolic BP, and coefficient of variation. Median follow-up duration was 905 days (interquartile range 529-1,310 days). All patients were divided into two groups according to the coefficient of variation of systolic BP (CVSBP); high CVSBP group (> 8.78, n = 617) and low CVSBP group (≤ 8.78, n = 617). High CVSBP group had significantly higher all-cause mortality (7.9% versus 3.1%, p < 0.001) and composite of all-cause mortality, myocardial infarction, and stroke (13.1% versus 6.2%, p < 0.001). In multivariate logistic regression analysis for prediction of all-cause mortality, and composite of all-cause mortality, myocardial infarction, and stroke after PCI with DES, hazard ratios of high CVSBP group were 2.441 (95% of confidence interval 1.042-5.718, p = 0.040), and 1.980 (95% of confidence interval 1.125-3.485, p = 0.018). The higher visit-to-visit BPV is associated higher mortality in patients undergoing PCI with DES. The clinic measured visit-to-visit BPV may serve as a predictor of all-cause mortality after PCI with DES.

Lifestyle risk behavior and atherosclerotic cardiovascular risk: An analysis using the Korea National Health and Nutrition Examination Survey.

BACKGROUND: Clustering lifestyle risk behaviors is important for predicting cardiovascular disease risk. However, it is unclear which behavior mediates other ones to influence cardiovascular disease risk. We aimed to assess the causal inference of each lifestyle risk behavior for the atherosclerotic cardiovascular disease (ASCVD) risk of the general population. METHODS: We performed a Bayesian network mediation analysis using data from the Korea National Health and Nutrition Examination Survey from 2014 to 2019. The main exposure was a combination of lifestyle risk behaviors including unhealthy weight, heavy alcohol consumption, inadequate sleep, physical inactivity, excessive sodium intake, and current smoking among subjects 40 to 79 years of age. The high risk of ASCVD (≥7.5% for the 10-year risk) was assessed using logistic regression, Bayesian networks, and structural equational models to examine the causal relationships between these six lifestyle risk behaviors. RESULTS: Among all participants, the most prevalent lifestyle risk behavior for those at high risk for ASCVD was excessive sodium intake (95.6%), followed by inadequate sleep (49.9%) and physical inactivity (43.8%). Older age (65-79 years) and male sex were directly associated with a high risk for ASCVD. Physical inactivity, current smoking, excessive sodium intake, and unhealthy weight indirectly mediated the effects of older age (8.2% of the older age) and male sex (39.9% of males) to high ASCVD risk. Physical inactivity, current smoking, excessive sodium intake, and unhealthy weight particularly mediated the high ASCVD risk sequentially. Heavy alcohol consumption and inadequate sleep were not directly associated with high ASCVD risk and did not indirectly mediate the effects of older age and males on the high ASCVD risk. CONCLUSION: Lifestyle risk behaviors mediated the atherosclerotic cardiovascular disease risk in a different manner. Especially, physical inactivity preceded current smoking, excessive sodium intake, and unhealthy weight in relation to high ASCVD risk, and this causal relationship was different according to age and sex. Therefore, tailored strategies according to specific target populations may be needed to effectively reduce the high ASCVD risk.

Indirect Volume Estimation for Acute Ischemic Stroke from Diffusion Weighted Image Using Slice Image Segmentation.

The accurate estimation of acute ischemic stroke (AIS) using diffusion-weighted imaging (DWI) is crucial for assessing patients and guiding treatment options. This study aimed to propose a method that estimates AIS volume in DWI objectively, quickly, and accurately. We used a dataset of DWI with AIS, including 2159 participants (1179 for internal validation and 980 for external validation) with various types of AIS. We constructed algorithms using 3D segmentation (direct estimation) and 2D segmentation (indirect estimation) and compared their performances with those annotated by neurologists. The proposed pretrained indirect model demonstrated higher segmentation performance than the direct model, with a sensitivity, specificity, F1-score, and Jaccard index of 75.0%, 77.9%, 76.0, and 62.1%, respectively, for internal validation, and 72.8%, 84.3%, 77.2, and 63.8%, respectively, for external validation. Volume estimation was more reliable for the indirect model, with 93.3% volume similarity (VS), 0.797 mean absolute error (MAE) for internal validation, VS of 89.2% and a MAE of 2.5% for external validation. These results suggest that the indirect model using 2D segmentation developed in this study can provide an accurate estimation of volume from DWI of AIS and may serve as a supporting tool to help physicians make crucial clinical decisions.

Another Look at Obesity Paradox in Acute Ischemic Stroke: Association Rule Mining.

Though obesity is generally associated with the development of cardiovascular disease (CVD) risk factors, previous reports have also reported that obesity has a beneficial effect on CVD outcomes. We aimed to verify the existing obesity paradox through binary logistic regression (BLR) and clarify the paradox via association rule mining (ARM). Patients with acute ischemic stroke (AIS) were assessed for their 3-month functional outcome using the modified Rankin Scale (mRS) score. Predictors for poor outcome (mRS 3-6) were analyzed through BLR, and ARM was performed to find out which combination of risk factors was concurrently associated with good outcomes using maximal support, confidence, and lift values. Among 2580 patients with AIS, being obese (OR [odds ratio], 0.78; 95% CI, 0.62-0.99) had beneficial effects on the outcome at 3 months in BLR analysis. In addition, the ARM algorithm showed obese patients with good outcomes were also associated with an age less than 55 years and mild stroke severity. While BLR analysis showed a beneficial effect of obesity on stroke outcome, in ARM analysis, obese patients had a relatively good combination of risk factor profiles compared to normal BMI patients. These results may partially explain the obesity paradox phenomenon in AIS patients.

Prediction of Hemorrhagic Transformation after Ischemic Stroke Using Machine Learning.

Hemorrhagic transformation (HT) is one of the leading causes of a poor prognostic marker after acute ischemic stroke (AIS). We compared the performances of the several machine learning (ML) algorithms to predict HT after AIS using only structured data. A total of 2028 patients with AIS, who were admitted within seven days of symptoms onset, were included in this analysis. HT was defined based on the criteria of the European Co-operative Acute Stroke Study-II trial. The whole dataset was randomly divided into a training and a test dataset with a 7:3 ratio. Binary logistic regression, support vector machine, extreme gradient boosting, and artificial neural network (ANN) algorithms were used to assess the performance of predicting the HT occurrence after AIS. Five-fold cross validation and a grid search technique were used to optimize the hyperparameters of each ML model, which had its performance measured by the area under the receiver operating characteristic (AUROC) curve. Among the included AIS patients, the mean age and number of male subjects were 69.6 years and 1183 (58.3%), respectively. HT was observed in 318 subjects (15.7%). There were no significant differences in corresponding variables between the training and test dataset. Among all the ML algorithms, the ANN algorithm showed the best performance in terms of predicting the occurrence of HT in our dataset (0.844). Feature scaling including standardization and normalization, and the resampling strategy showed no additional improvement of the ANN's performance. The ANN-based prediction of HT after AIS showed better performance than the conventional ML algorithms. Deep learning may be used to predict important outcomes for structured data-based prediction.

Off-pump open pulmonary embolectomy for patients with major pulmonary embolism.

Acute major pulmonary artery embolism (AMPE) requires rapid diagnosis and early intensive treatment to optimize patient outcomes. Most patients with AMPE and hemodynamic instability need open pulmonary embolectomy (OPE). We modified the technique of OPE to include a minimally invasive procedure without the use of cardiopulmonary bypass (CPB). From March 1988 to April 2006, we performed OPE on a total of 12 patients (21 sides) with AMPE. Seven patients (13 sides) underwent conventional OPE with CPB and 5 patients underwent off-pump OPE (OPPE), 4 (8 sides) with AMPE and 1 with catheter embolus with thrombosis. In patients who underwent conventional OPE, there was 1 hospital death in a patient with severe right ventricle dysfunction and 2 significant cases of airway bleeding. In patients who underwent OPPE, there was 1 case of minimal airway bleeding. Mean systolic pulmonary artery pressure in conventional OPE and OPPE patients, respectively, decreased from 50.3 +/- 14 mmHg and 35.4 +/- 6.6 mmHg pre-operatively to 41.7 +/- 20 and 28 +/- 3 mmHg postoperatively. During the long-term follow-up, there were 2 cancer-related deaths but no recurrence of PE. All surviving patients maintained functional class I (n = 10) or II (n = 1). Compared with conventional OPE, OPPE was effective for treating AMPE in our selected cases. Modification of conventional CPB and systemic full heparinization to minimal use of systemic heparinization without CPB may be helpful in treating selected patients with AMPE.

Relationship between plasma adiponectin, retinol-binding protein 4 and uric Acid in hypertensive patients with metabolic syndrome.

BACKGROUND AND OBJECTIVES: Adipokines have been suggested for their potential use in tracking the clinical progress in the subjects with metabolic syndrome (MS). To investigate the relationship between the serum levels of adipokines {adiponectin and retinol-binding protein 4 (RBP4)} and the serum level of uric acid in hypertensive (HTN) patients with MS. SUBJECTS AND METHODS: In this study, 38 totally untreated HTN patients were enrolled. Anthropometric measurements, blood pressure (BP) were taken in the 12 HTN patients without MS and the 26 HTN patients with MS. Fasting blood samples were collected for measurement of adiponectin, RBP4, nitric oxide (NO), glucose, creatinine, uric acid, lipid profile and insulin. RESULTS: The HTN with MS group had significant higher values of body mass index, waist length, serum uric acid and triglyceride levels than the HTN without MS group. Compared to the HTN without MS group, the HTN with MS group showed significantly lower adiponectin (p=0.030), NO (p=0.003) and high density lipoprotein levels (p<0.001). Serum adiponectin levels negatively correlated with insulin level (R=-0.453, p=0.026) and uric acid level (R=-0.413, p=0.036), and serum RBP4 levels positively correlated with uric acid level (R=0.527, p=0.006) in the HTN with MS group. Multiple linear regression analysis using RBP4 and adiponectin levels as the dependent variables showed that uric acid level correlated with serum RBP4 level (p=0.046) and adiponectin level (p=0.044). CONCLUSION: The HTN with MS group showed a correlation with two types of adipokines (adiponectin, RBP4) and uric acid. Adiponectin, RBP4 and uric acid may be important components associated with MS, especially when associated with hypertension.

Clinical, electrocardiographic, and procedural characteristics of patients with coronary chronic total occlusions.

BACKGROUND AND OBJECTIVES: Percutaneous coronary intervention for chronic total occlusion lesions is technically difficult despite equipment advances. Changes in electrocardiographic patterns, such as Q and T waves, during chronic total occlusion can provide information about procedural success and myocardial viability. In this study, we investigated clinical, electrocardiographic, and procedural characteristics of chronic total occlusions. SUBJECTS AND METHODS: Patients (2,635) who underwent coronary angiography between January 2006 and July 2007 at six Catholic University Hospitals were identified using a dedicated Internet database. RESULTS: A total of 195 patients had total occlusion lesions (7.4%). Percutaneous coronary interventions were attempted in 136 total occlusion lesions (66.0%) in 134 patients. Successful recanalization with stent implantation was accomplished in 89 lesions, with a procedural success rate of 66.4%. One procedure-related death occurred because of no-reflow phenomenon. After excluding 8 patients with bundle branch block, Q and T wave inversions were observed in 60 (32.1%) and 78 patients (41.7%), respectively. The presence of Q waves was associated with severe angina, decreased left ventricular ejection fraction, regional wall motion abnormality, and T wave inversion, but was not related to procedural success. CONCLUSION: Percutaneous coronary intervention is a safe and useful procedure for the revascularization of coronary chronic total occlusion lesions. The procedural success rate was not related to the presence of pathologic Q waves, which were associated with severe angina and decreased left ventricular function.