ラットにおける新しい肺動脈絞扼右心不全モデル

Inmueble de planta arquitectónica compacta en dos pisos, con patio posterior; fachada y muros en bahareque; entrepisos en madera; y techo en fibrocemento. En 2015, se encontraba en buen estado de conservación y estaba destinado a uso comercial

Deep learning to predict elevated pulmonary artery pressure in patients with suspected pulmonary hypertension using standard chest X ray

Accurate diagnosis of pulmonary hypertension (PH) is crucial to ensure that patients receive timely treatment. We hypothesized that application of artificial intelligence (AI) to the chest X-ray (CXR) could identify elevated pulmonary artery pressure (PAP) and stratify the risk of heart failure hospitalization with PH. We retrospectively enrolled a total of 900 consecutive patients with suspected PH. We trained a convolutional neural network to identify patients with elevated PAP (> 20 mmHg) as the actual value of PAP. The endpoints in this study were admission or occurrence of heart failure with elevated PAP. In an independent evaluation set for detection of elevated PAP, the area under curve (AUC) by the AI algorithm was significantly higher than the AUC by measurements of CXR images and human observers (0.71 vs. 0.60 and vs. 0.63, all p < 0.05). In patients with AI predicted PH had 2-times the risk of heart failure with PH compared with those without AI predicted PH. This preliminary work suggests that applying AI to the CXR in high risk groups has limited performance when used alone in identifying elevated PAP. We believe that this report can serve as an impetus for a future large study

AI for Exercise-Induced Pulmonary Hypertension

Background: Stress echocardiography is an emerging tool used to detect exercise-induced pulmonary hypertension (EIPH). However, facilities that can perform stress echocardiography are limited by issues such as cost and equipment. Objective: We evaluated the usefulness of a deep learning (DL) approach based on a chest X-ray (CXR) to predict EIPH in 6-min walk stress echocardiography. Methods: The study enrolled 142 patients with scleroderma or mixed connective tissue disease with scleroderma features who performed a 6-min walk stress echocardiographic test. EIPH was defined by abnormal cardiac output (CO) responses that involved an increase in mean pulmonary artery pressure (mPAP). We used the previously developed AI model to predict PH and calculated PH probability in this cohort. Results: EIPH defined as ΔmPAP/ΔCO >3.3 and exercise mPAP >25 mmHg was observed in 52 patients, while non-EIPH was observed in 90 patients. The patients with EIPH had a higher mPAP at rest than those without EIPH. The probability of PH based on the DL model was significantly higher in patients with EIPH than in those without EIPH. Multivariate analysis showed that gender, mean PAP at rest, and the probability of PH based on the DL model were independent predictors of EIPH. A model based on baseline parameters (age, gender, and mPAP at rest) was improved by adding the probability of PH predicted by the DL model (AUC: from 0.65 to 0.74; p = 0.046). Conclusion: Applying the DL model based on a CXR may have a potential for detection of EIPH in the clinical setting

Deep learning approach for analyzing chest x-rays to predict cardiac events in heart failure

Background: A deep learning (DL) model based on a chest x-ray was reported to predict elevated pulmonary artery wedge pressure (PAWP) as heart failure (HF). Objectives: The aim of this study was to (1) investigate the role of probability of elevated PAWP for the prediction of clinical outcomes in association with other parameters, and (2) to evaluate whether probability of elevated PAWP based on DL added prognostic information to other conventional clinical prognostic factors in HF. Methods: We evaluated 192 patients hospitalized with HF. We used a previously developed AI model to predict HF and calculated probability of elevated PAWP. Readmission following HF and cardiac mortality were the primary endpoints. Results: Probability of elevated PAWP was associated with diastolic function by echocardiography. During a median follow-up period of 58 months, 57 individuals either died or were readmitted. Probability of elevated PAWP appeared to be associated with worse clinical outcomes. After adjustment for readmission score and laboratory data in a Cox proportional-hazards model, probability of elevated PAWP at pre-discharge was associated with event free survival, independent of elevated left atrial pressure (LAP) based on echocardiographic guidelines (p < 0.001). In sequential Cox models, a model based on clinical data was improved by elevated LAP (p = 0.005), and increased further by probability of elevated PAWP (p < 0.001). In contrast, the addition of pulmonary congestion interpreted by a doctor did not statistically improve the ability of a model containing clinical variables (compared p = 0.086). Conclusions: This study showed the potential of using a DL model on a chest x-ray to predict PAWP and its ability to add prognostic information to other conventional clinical prognostic factors in HF. The results may help to enhance the accuracy of prediction models used to evaluate the risk of clinical outcomes in HF, potentially resulting in more informed clinical decision-making and better care for patients

Peri-Renal Fat and Adiponectin

Background: The interactions of adipose tissue with the kidney are hypothesized to affect kidney function. Also, excessive peri-renal fat may increase the risk of cardiometabolic risk. However, the role(s) of peri-renal fat adipocytokine has never been evaluated. Objectives: To elucidate levels of adiponectin expression in peri-renal and subcutaneous adipose tissue and its determinants in human biopsied samples. Methods: A pair of subcutaneous and perirenal fat tissue samples were collected from 80 patients (men: 54; women: 26) who underwent urological operations. Subcutaneous adipose tissue (SAT) area, visceral adipose tissue (VAT) area and peri-renal adipose tissue (RAT) volume were quantified on abdominal computed tomography. Cytokine/adipocytokine expression was evaluated by real-time semi-quantitative polymerase chain reaction (qPCR). Probability was considered significant if P < 0.05. Results: Current study evaluated determinants of plasma adiponectin levels and expression levels of adiponectin in SAT and RAT in human samples. We found that: first, plasma adiponectin levels were correlated with VAT area but not with BMI, waist circumference, SAT area, and RAT volume; second, expression levels of adiponectin in SAT were correlated with BMI, waist circumference, and SAT area but not with VAT area and RAT volume; and third, expression levels of adiponectin in RAT were correlated with all adiposity indices including BMI, waist circumference, SAT area, VAT area, and RAT volume. Conclusion: This study evaluated levels of adiponectin expression in RAT and SAT and its determinants in patients who underwent urological operation. Levels of adiponectin mRNA in RAT were negatively correlated with remote fat mass in SAT and VAT and also with local fat mass in RAT, while level of adiponectin in SAT was not correlated with RAT volume. Further studies are warranted to evaluate roles of peri-renal fat mass accumulation and its pathophysiological machineries

Inhibition of activated factor X by rivaroxaban attenuates neointima formation after wire-mediated vascular injury

Accumulating evidence suggests that activated factor X (FXa), a key coagulation factor, plays an important role in the development of vascular inflammation through activation of many cell types. Here, we investigated whether pharmacological blockade of FXa attenuates neointima formation after wire-mediated vascular injury. Transluminal femoral artery injury was induced in C57BL/6 mice by inserting a straight wire. Rivaroxaban (5 mg/kg/day), a direct FXa inhibitor, was administered from one week before surgery until killed. At four weeks after surgery, rivaroxaban significantly attenuated neointima formation in the injured arteries compared with control (P<0.01). Plasma lipid levels and blood pressure were similar between the rivaroxaban-treated group and non-treated group. Quantitative RT-PCR analyses demonstrated that rivaroxaban reduced the expression of inflammatory molecules (e.g., IL-1β and TNF-α) in injured arteries at seven days after surgery (P<0.05, respectively). In vitro experiments using mouse peritoneal macrophages demonstrated that FXa increased the expression of inflammatory molecules (e.g., IL-1β and TNF-α), which was blocked in the presence of rivaroxaban (P<0.05). Also, in vitro experiments using rat vascular smooth muscle cells (VSMC) demonstrated that FXa promoted both proliferation and migration of this cell type (P<0.05), which were blocked in the presence of rivaroxaban. Inhibition of FXa by rivaroxaban attenuates neointima formation after wire-mediated vascular injury through inhibition of inflammatory activation of macrophages and VSMC

Progression of Renal Dysfunction in Patients with Cardiovascular Disease

It has been established that patients with chronic kidney disease (CKD) suffer from frequent cardiovascular events. On the other hand, recent studies suggest that renal damage tends to worsen in patients with cardiovascular diseases (CVD). Although the mechanisms for the cardiorenal association are unclear, the presence of arteriosclerotic risk factors common to both CVD and CKD is important. In arteriosclerosis, vascular derangement progresses not only in the heart but also in the kidney. In addition, heart failure, cardiac catheterization and hesitation of medical treatments due to renal dysfunction may explain the progression of renal damage. Therefore, the goal of treatments is a total control of arteriosclerotic risk factors. Medication should be selected among agents with protective effects on both heart and kidney. It is important to always consider the presence of CKD for the treatment of the cardiovascular disease and strictly control the risk factors