Parvimonas micra-induced prosthetic valve endocarditis: a challenging case report and literature review.

Parvimonas micra, a gram-positive anaerobic bacterium, has garnered increased attention due to its role in infective endocarditis. We present a challenging prosthetic valve endocarditis caused by Parvimonas micra in a patient with a complex cardiac history involving multiple surgeries. The case highlights the difficulties in diagnosis and treatment, emphasizing the importance of advanced diagnostic techniques, including metagenomics next-generation sequencing (mNGS). Additionally, it underscores the need for heightened vigilance regarding oral symptoms and the potential risk of bacteremia in post-valvular surgery patients. This report contributes to a better understanding of Parvimonas micra-associated endocarditis and its unique characteristics.

Severe tricuspid regurgitation with chordae tendinae rupture in CABG surgery.

A 58-year-old male patient was admitted with chest pain and was diagnosed with coronary heart disease. He was scheduled for coronary artery bypass grafting (CABG) under cardiopulmonary bypass (CPB). Intraoperative real-time transesophageal echocardiography (TEE) showed that the tricuspid valves were well-aligned and subtle regurgitation. Real-time TEE after separation from CPB showed severe tricuspid regurgitation and prolapsed chordae tendineae. The tricuspid chordae tendineae rupture due to a right atrial venous return cannula. The use of negative pressure to improve venous drainage during CPB may result in the tricuspid valve being adsorbed to the cannula, increasing the likelihood of injury to the tricuspid valve.

Atrial septal hematogenous cyst with calcification mimicking myxoma: A rare case.

A 61-year-old female presented with right atrial mass during physical examination. Contrast-enhanced left heart echocardiography revealed a mass with the size of 32*23 mm in the right atrium, attached to the atrial septum; there was a certain degree of activity and deformation. MRI showed a mass of about 35*22 mm in the right atrium adjacent to the atrial septum, which was diagnosed with right atrial myxoma. Intraoperative TEE showed that the mass was located in the atrial septum close to the inferior vena cava and spontaneous echo contrast with hyperechoic images within the mass. The lesion was resected under cardiopulmonary bypass. Pathological examination revealed that the filling defect was an atrial septal hematogenous cyst with calcification.

Autologous bone marrow stem cell transplantation for patients undergoing coronary artery bypass grafting: a meta-analysis of 22 randomized controlled trials.

BACKGROUND: Although the safety and feasibility of coronary artery bypass grafting (CABG) and bone marrow stem cell (BMSC) transplantation have been established, the effectiveness of this approach compared with CABG alone remains controversial. The aim of this updated meta-analysis of randomized controlled trials was to evaluate the efficacy of this procedure. METHODS: A random-effects meta-analysis was conducted using studies sourced from the PubMed, Embase, and Cochrane literature databases to compare patients who received isolated CABG (CABG group) and BMSC transplantation with CABG (BMSC group). 22 studies were included. RESULTS: A total of 22 relevant publications with 820 patients were included. 432 patients received BMSC transplantation with CABG and 388 patients received isolated CABG. Compared with the CABG group, the BMSC transplantation group exhibited an improvement in the left ventricular (LV) ejection fraction (mean difference (MD) = 3.87%; 95% confidence interval (CI): 1.93-5.80%; P < 0.001). CONCLUSION: The present evidence suggests that autologous BMSC transplantation for patients undergoing CABG appears to be associated with an improvement in LV function compared with CABG alone. However, heterogeneity in the data suggests that patients respond differently to this therapy. Further research is needed to understand these differences.

An Improved Monkey Model of Myocardial Ischemic Infarction for Cardiovascular Drug Development.

Non-human primate monkey model of myocardial ischemic infarction is precious for translational medicine research. Ligation of the left anterior descending (LAD) artery is a common procedure to induce myocardial ischemic infarction. However, the consistency of the myocardial infarction thus generated remains problematic. The present study was undertaken to critically evaluate the monkey model of myocardial ischemic infarction to develop a procedure for a consistent cross-study comparison. Forty male Rhesus monkeys were divided into 4 groups and subjected to LAD artery ligation at different levels along the artery. In addition, the major diagonal branch was selectively ligated parallel to the ligation site of the LAD artery according to the diagonal branch distribution. Analyses of MRI, echocardiography, cardiac hemodynamics, electrocardiography, histopathology, and cardiac injury biomarkers were undertaken to characterize the monkeys with myocardial infarction. Ligation at 40% of the total length of the artery, measured from the apex end, produced variable infarct areas with inconsistent functional alterations. Ligation at 60% or above coupled with selective ligation of diagonal branches produced a consistent myocardial infarction with uniform dysfunction. However, ligation at 70% caused a lethal threat. After a thorough analysis, it is concluded that ligation at 60% of the total length coupled with selective ligation of diagonal branches, enables standardization of the location of occlusion and the subsequent ischemic area, as well as avoids the influence of the diagonal branches, are ideal to produce a consistent monkey model of myocardial ischemic infarction.

Warfarin maintenance dose prediction for Chinese after heart valve replacement by a feedforward neural network with equal stratified sampling.

Patients requiring low-dose warfarin are more likely to suffer bleeding due to overdose. The goal of this work is to improve the feedforward neural network model's precision in predicting the low maintenance dose for Chinese in the aspect of training data construction. We built the model from a resampled dataset created by equal stratified sampling (maintaining the same sample number in three dose-groups with a total of 3639) and performed internal and external validations. Comparing to the model trained from the raw dataset of 19,060 eligible cases, we improved the low-dose group's ideal prediction percentage from 0.7 to 9.6% and maintained the overall performance (76.4% vs. 75.6%) in external validation. We further built neural network models on single-dose subsets to invest whether the subsets samples were sufficient and whether the selected factors were appropriate. The training set sizes were 1340 and 1478 for the low and high dose subsets; the corresponding ideal prediction percentages were 70.2% and 75.1%. The training set size for the intermediate dose varied and was 1553, 6214, and 12,429; the corresponding ideal prediction percentages were 95.6, 95.1%, and 95.3%. Our conclusion is that equal stratified sampling can be a considerable alternative approach in training data construction to build drug dosing models in the clinic.

In-situ recurrence of the primary cardiac dedifferentiated liposarcoma: To resect or not?

Dedifferentiated liposarcoma (DDLPS) is a rare type of neoplasm which can originally rise in cardiac chamber. Owing to the recurrence and distant metastasis, the prognosis of the primary malignant cardiac tumor is extremely poor and remains a challenge for cardiac surgeons. Here, we report a patient with an intracavitary mass which was diagnosed as DDLPS by postoperative pathological examinations, experienced repeated in-situ recurrence of the malignant cardiac tumor.

The Prediction Model of Warfarin Individual Maintenance Dose for Patients Undergoing Heart Valve Replacement, Based on the Back Propagation Neural Network.

BACKGROUND AND OBJECTIVE: Because of the narrow therapeutic window and huge inter-individual variation, the individual precision on anticoagulant therapy of warfarin is challenging. In our study, we aimed to construct a Back Propagation Neural Network (BPNN) model to predict the individual warfarin maintenance dose among Chinese patients who have undergone heart valve replacement, and validate its prediction accuracy. METHODS: In this study, we analyzed 13,639 eligible patients extracted from the Chinese Low Intensity Anticoagulant Therapy after Heart Valve Replacement database, which collected data on patients using warfarin after heart valve replacement from 15 centers all over China. Ten percent of patients who were finally enrolled in the database were used as the external validation, while the remaining were randomly divided into the training and internal validation groups at a ratio of 3:1. Input variables were selected by univariate analysis of the general linear model; 2.0, the mean value of the international normalized ratio (INR) range 1.5-2.5, was used as the mandatory variable. The BPNN model and the multiple linear regression (MLR) model were constructed by the training group and validated through comparisons of the mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and ideal predicted percentage. RESULTS: Finally, 10 input variables were selected and a three-layer BPNN model was constructed. In the BPNN model, the value of MAE (0.688 mg/day and 0.740 mg/day in internal and external validation, respectively), MSE (0.580 mg/day and 0.599 mg/day in internal and external validation, respectively), and RMSE (0.761 mg/day and 0.774 mg/day in internal and external validation, respectively) were achieved. Ideal predicted percentages were high in both internal (63.0%) and external validation (59.7%), respectively. Compared with the MLR model, the BPNN model showed a higher ideal prediction percentage in the external validation group (59.7% vs. 56.6%), and showed the best prediction accuracy in the intermediate-dose subgroup (internal validation group: 85.2%; external validation group: 84.7%) and a high predicted percentage in the high-dose subgroup (internal validation group: 36.2%; external validation group: 39.8%), but poor performance in the low-dose subgroup (internal validation group: 0%; external validation group: 0.3%). Meanwhile, the BPNN model showed better ideal prediction percentage in the high-dose group than the MLR model (internal validation: 36.2% vs. 31.6%; external validation: 42.8% vs. 37.8%). CONCLUSION: The BPNN model shows promise for predicting the warfarin maintenance dose after heart valve replacement.

Successful recognition and percutaneous coronary intervention of delayed severe multiple coronary artery dissection caused by cardiac surgery: a case report.

BACKGROUND: Multiple coronary artery dissection is rare after cardiac surgery. It is difficult to recognize and is easily misdiagnosed as low output syndrome as a result of cardiopulmonary bypass (CPB). CASE PRESENTATION: A 43-year-old woman who had undergone cardiac surgery presented with unstable hemodynamics, and progressively increasing lactate, B-type natriuretic peptide, and cardiac enzyme levels, along with electrocardiogram (ECG) changes. Angiography indicated the presence of severe multiple coronary artery dissection, and 3 stents were implanted, which improved the patient's hemodynamic status and cardiac function. CONCLUSIONS: In the present report, we describe our experience with identifying and treating delayed severe multiple coronary artery dissection caused by cardiac surgery. Timely angiography is vital in patients suspected with coronary artery dissection, and percutaneous coronary intervention (PCI) should be considered as a treatment strategy for cases with severe multiple coronary artery dissection and unstable hemodynamics after cardiac surgery.

A prediction study of warfarin individual stable dose after mechanical heart valve replacement: adaptive neural-fuzzy inference system prediction.

BACKGROUND: It's difficult but urgent to achieve the individualized rational medication of the warfarin, we aim to predict the individualized warfarin stable dose though the artificial intelligent Adaptive neural-fuzzy inference system (ANFIS). METHODS: Our retrospective analysis based on a clinical database, involving 21,863 patients from 15 Chinese provinces who receive oral warfarin after the heart valve replacement. They were allocated into four groups: the external validation group (A group), the internal validation group (B group), training group (C group) and stratified training group (D group). We used a univariate analysis of general linear models(GLM-univariate) to select the input variables and construct two prediction models by the ANFIS with the training and stratified training group, and then verify models with two validation groups by the mean squared error(MSE), mean absolute error(MAE) and the ideal predicted percentage. RESULTS: A total of 13,639 eligible patients were selected, including 1639 in A group, 3000 in B group, 9000 in C group, and 3192 in D group. Nine input variables were selected out and two five-layered ANFIS models were built. ANFIS model achieved the highest total ideal predicted percentage 63.7%. In the dose subgroups, all the models performed best in the intermediate-dose group with the ideal predicted percentage 82.4~ 86.4%, and the use of the stratified training group slightly increased the prediction accuracy in low-dose group by 8.8 and 5.2%, respectively. CONCLUSION: As a preliminary attempt, ANFIS model predicted the warfarin stable dose properly after heart valve surgery among Chinese, and also proved that Chinese need lower anticoagulation intensity INR (1.5-2.5) to warfarin by reference to the recommended INR (2.5-3.5) in the developed countries.