Cardiac Valve Replacement Research Articles

Music therapy for pain and anxiety in patients after cardiac valve replacement: a randomized controlled clinical trial

ObjectiveThis study aimed to assess how listening to music after cardiac valve replacements affected patients' pain, anxiety, and vital signs.MethodIn Fuzhou, China's Fujian Medical University Union Hospital, the cardiac surgery division conducted a randomized controlled clinical experiment. 86 patients were enrolled, and 43 were assigned randomly to each group (control and experimental group). The standard treatment was given to the control group, while the experimental group was given standard treatment + a 15-min music intervention 3 times. Indicators include pain, anxiety and vital signs (respiratory rate, heart rate, and blood pressure).ResultsIn comparison to the control group, the experimental group, over time, demonstrated a statistically substantial decrease in pain, anxiety, systolic blood pressure, heart rate and respiratory rate (all P < 0.001), yet, there were no discernible variations (P > 0.05) in diastolic blood pressure.ConclusionsIn conclusion, these results provide additional proof for using music therapy to minimize cardiac postoperative pain and anxiety, as well as systolic blood pressure, heart rate and respiratory rate. Moreover, it should be regarded as a supplementary treatment for pain and anxiety after cardiac valve replacement and other medical procedures with comparable postoperative pain.

A Novel Low-Profile Self-Expanding Biodegradable Percutaneous Heart Valve Frame That Grows with a Child

According to rough estimates, one in every 125 newborns born in the United States has a congenital cardiac abnormality that must be repaired. With the recent development of new biomaterials and innovative treatment methods, percutaneous cardiac valve replacement has been considered as an alternative to surgical procedures. While percutaneous heart valve replacement is a relatively new procedure with a few commercially available devices, the devices are not sufficiently low-profile, and do not grow with the child. To address this issue, a novel low-profile growing percutaneous pediatric heart valve frame made of two types of unique metallic biomaterials (supere lastic nitinol and biodegradable iron) has been developed through this study. The developed pediatric heart valve frame has an innovative mechanism that will expand its diameter by disconnecting biodegradable metals, enabling the growth of the device with the surrounding tissue in the cardiac space. The thermally treated iron wires show stable and gradual degradation characteristics, showing approximately 7.66% for both wires treated under 350 and 450 °C. Polymer-coated wires show a degradation range of 4.96 to 5.55% depending on the type of coating. Degradation test results show the predicted 9–23 months of degradation depending on the type of surface treatment (e.g., thermal treatment, polymer coating), which is a suitable range when compared with the theoretical arterial vessel remodeling process period in the human vascular system. Radial forces calculated by finite element analysis and measured by mechanical testing matched well, showing 5–6 N with a 20% diameter reduction considering the deployed valve frame in the heart. Biocompatibility study results demonstrated superior cell viability in thermally treated iron wires after 3 days of cell culture and showed rarely found platelets on the surface after 3-h blood exposure tests. Prototype devices were successfully fabricated using optimized advanced joining processes for dissimilar metallic materials such as nitinol and iron. This study represents the first demonstration of self-expanding and biodegradable percutaneous heart valve frames for pediatric patients that grow with a child.

Predictors of Intraoperative Echocardiography: Analysis of The Society of Thoracic Surgeons Database

BackgroundIntraoperative transesophageal echocardiography (TEE) is associated with improved outcomes after cardiac surgery, but unexplained practice pattern variation exists. This study aimed to identify and quantify the predictors of intraoperative TEE use among patients undergoing isolated coronary artery bypass graft surgery (CABG) or cardiac valve surgery. MethodsThis observational cohort study used The Society of Thoracic Surgeon (STS) Adult Cardiac Surgery Database data to identify and quantify the predictors of intraoperative TEE use among adult patients aged 18 years or more undergoing either isolated CABG or open cardiac valve repair or replacement surgery between January 1, 2011, and December 31, 2019. Generalized linear mixed models were used to measure the relationship between intraoperative TEE and patient characteristics, surgical volume, and geographic location, while accounting for clustering within hospitals (primary analysis) or surgeons (secondary analysis). ResultsOf 1,973,655 patients, 1,365,708 underwent isolated CABG and 607,947 underwent cardiac valve surgery. Overall, intraoperative TEE was used in 62% of surgeries. The primary hospital-level generalized linear mixed models analysis demonstrated that the strongest predictor of intraoperative TEE use was the hospital where the surgery occurred—with a median odds ratio for TEE of 10.13 in isolated CABG and 5.30 in cardiac valve surgery. The secondary surgeon-level generalized linear mixed models analysis demonstrated similar findings. ConclusionsIntraoperative TEE use (vs lack of use) during surgery was more strongly associated with hospital and surgeon practice patterns than with any patient-level factor, surgical volume, or geographic location.

Efficacy of Hemoperfusion Cartridge Procedure on Patients Undergoing Cardiac Valve Replacement Surgery with Cardiopulmonary Bypass

Cardiopulmonary bypass (CPB) induces inflammatory homeostasis dysregulation, closely related to many postoperative adverse effects. Minimizing the systemic inflammatory response to CPB is imperative to improving cardiac surgery safety. This study aimed to retrospectively evaluate the efficacy of the hemoperfusion cartridge, a device recently designed for extracorporeal blood purification to remove cytokines from the blood for patients undergoing cardiac valve replacement surgery using CPB. The hemoperfusion (HP) group consisted of 138 patients, who underwent a hemoperfusion cartridge procedure during CPB. The control group included 149 patients, who received standard CPB management. The evaluated indices included inflammatory cytokines, blood biochemical indices, and postoperative outcome indices. Patients in the HP group had relatively lower interleukin (IL)-6 levels (days one and two post-CPB) and IL-8 (day one post-CPB) compared with the control group. Some relatively decreased biochemical blood indices also were observed in the HP group, including a significantly lower lactic acid level (days one, two, and three post-CPB), platelet counts (days one, two, and three post-CPB), and aspartate aminotransferase (days one and three post-CPB). Regarding the postoperative outcomes, no severe complications occurred in the patients; however, the HP group required less ventilation time than the control group. The hemoperfusion cartridge seems promising in limiting the inflammatory reactions during CPB, with noteworthy potential for application in cardiac surgery.

Retracted: Effects of Different Anesthetics on Perioperative Organ Protection and Postoperative Cognitive Function in Patients Undergoing Cardiac Valve Replacement with Cardiopulmonary Bypass.

[This retracts the article DOI: 10.1155/2022/8994946.].

Retracted: Effects of Ulinastatin on Myocardial Ischemia-Reperfusion Injury, Cardiac Function, and Serum TNF-α and IL-10 Levels in Patients Undergoing Cardiac Valve Replacement under Cardiopulmonary Bypass.

[This retracts the article DOI: 10.1155/2022/1823398.].

Serum procalcitonin levels in open heart surgery patients and its relationship with mortality and morbidity

Aim: The release of procalcitonin (PCT) has been suggested to be related to the type of surgery and cardiopulmonary bypass (CPB). We aimed to investigate the associations of PCT with hemodynamic stability, type of cardiac surgery, and complications.Methods: Our study was conducted in 2015 on 76 adult patients divided into three groups according to types of surgery: group I consisted of coronary artery bypass grafting with CPB, group II consisted of cardiac valve replacement, and group III included left ventricle assist device implantation. The patients’ serum PCT values were measured preoperatively before induction, 24 and 48 hours postoperatively, and when a complication occurred.Results: Preoperative PCT levels of the groups were similar. The PCT level in group I was lowest preoperatively, highest in postoperative 24 hours, and showed a decline postoperatively from 24 hours to 48 hours. In group II, the PCT level was increased in postoperative 24 and 48 hours compared to the preoperative level, and there was no difference between postoperative 24- and 48-hour values. In group III, the PCT level was lowest preoperatively and highest in postoperative 24 hours, while the postoperative 48-hour value was lower than the 24-hour value. Intensive care unit (ICU) stay with a higher P1PCTlevel correlated with longer ICU stay. There were no differences between patients with PCT levels ≥ 0.5 and

Analgesic efficacy of butorphanol combined with sufentanil after heart valve surgery: A propensity score-matching analysis

Pain is common after heart valve surgery and can stimulate the sympathetic nervous system, causing hemodynamic instability and respiratory complications. Current treatments for postoperative pain are insufficient, and postoperative pain is difficult to control effectively with a single analgesic. Therefore, we investigated the analgesic efficacy of butorphanol with sufentanil after heart valve surgery and its hemodynamic effects. The records of 221 patients admitted to the intensive care unit after cardiac valve replacement between January 1, 2018, and May 31, 2021, were retrospectively analyzed. Patients were allocated to 2 groups based on the postoperative pain treatment they received: treatment group (administered butorphanol combined with sufentanil), and control group (administered conventional sufentanil analgesia). After propensity score matching for sex, age, Acute Physiology and Chronic Health Evaluation II score, type of valve surgery, and operation duration, 76 patients were included in the study, and analgesic efficacy, hemodynamic changes, and adverse drug reactions were compared between the 2 groups. After propensity score matching, the baseline characteristics were not significantly different between the groups. The histogram and jitter plot of the propensity score distribution indicated good matching. No significant differences were observed in the duration of mechanical ventilation, duration of stay in the intensive care unit, duration of total hospital stay, and hospitalization expenditure between the groups (P > .05). The treatment group had notably higher minimum systolic blood pressure (P = .024) and lower heart rate variability (P = .049) than those in the control group. Moreover, the treatment group exhibited better analgesic efficacy and had lower critical-care pain observation tool scores and consumption of sufentanil 24 hours after surgery than the control group (P < .05). The incidence of vomiting was notably lower in the treatment than in the control group (P = .028). Butorphanol combined with sufentanil can be used in patients after heart valve replacement. This combined treatment has good analgesic efficacy and is associated with reduced adverse drug reactions and, potentially, steady hemodynamics.

A Digital Health Intervention for Stress and Anxiety Relief in Perioperative Care: Protocol for a Feasibility Randomized Controlled Trial.

Stress and anxiety are psychophysiological responses commonly experienced by patients during the perioperative process that can increase presurgical and postsurgical complications to a comprehensive and positive recovery. Preventing and intervening in stress and anxiety can help patients achieve positive health and well-being outcomes. Similarly, the provision of education about surgery can be a crucial component and is inversely correlated with preoperative anxiety levels. However, few patients receive stress and anxiety relief support before surgery, and resource constraints make face-to-face education sessions untenable. Digital health interventions can be helpful in empowering patients and enhancing a more positive experience. Digital health interventions have been shown to help patients feel informed about the possible benefits and risks of available treatment options. However, they currently focus only on providing informative content, neglecting the importance of personalization and patient empowerment. This study aimed to explore the feasibility of a digital health intervention called the Adhera CARINAE Digital Health Program, designed to provide evidence-based, personalized stress- and anxiety-management methods enabled by a comprehensive digital ecosystem that incorporates wearable, mobile, and virtual reality technologies. The intervention program includes the use of advanced data-driven techniques for tailored patient education and lifestyle support. The trial will include 5 hospitals across 3 European countries and will use a randomized controlled design including 30 intervention participants and 30 control group participants. The involved surgeries are cardiopulmonary and coronary artery bypass surgeries, cardiac valve replacement, prostate or bladder cancer surgeries, hip and knee replacement, maxillofacial surgery, or scoliosis. The control group will receive standard care, and the intervention group will additionally be exposed to the digital health intervention program. The recruitment process started in January 2022 and has been completed. The primary impact analysis is currently ongoing. The expected results will be published in early 2023. This manuscript details a comprehensive protocol for a study that will provide valuable information about the intervention program, such as the measurement of comparative intervention effects on stress; anxiety and pain management; and usability by patients, caregivers, and health care professionals. This will contribute to the evidence planning process for the future adoption of diverse digital health solutions in the field of surgery. ClinicalTrials.gov NCT05184725; https://www.clinicaltrials.gov/ct2/show/NCT05184725. DERR1-10.2196/38536.

Primrose Journey

About 8 weeks after Clare died, now 10 years ago, her husband, Keith, e-mailed to ask if he could come see me. I agreed to his request immediately and looked forward to seeing him. For 24 years, I had had the privilege of caring for Clare and helping her and her family navigate the myriad health challenges caused by her Takayasu arteritis, including 5 cardiac valve replacement surgeries and 25-plus medical hospitalizations. In the more than 100 times that I had seen Clare in the office or in the hospital, I had almost never seen her without Keith.

Abstract 9422: Tandem Deep Learning and Logistic Regression Models to Optimize Hypertrophic Cardiomyopathy Detection in Routine Clinical Practice

Background: An electrocardiogram (ECG)-based artificial intelligence (AI) algorithm has shown good performance in detecting hypertrophic cardiomyopathy (HCM AI-score). However, its clinical application may be challenging due to the low disease prevalence and potentially high false-positive rate when screening unenriched cohorts. Aims: To identify clinical characteristics associated with false-positive HCM AI-score results to improve screening tool application. Methods: From a cohort of 20,677 patients with a digital 12-lead ECG in routine clinical practice in 2021, we performed a detailed chart review of the 200 patients with highest HCM AI-score to determine their HCM status and collect clinical data. Stepwise forward logistic regression was used to create a clinical variable-based “candidacy for HCM screening” score (CHS score), differentiating true- and likely true-positive from likely false-positive HCM AI-score results. We then validated the CHS score in 200 patients with the highest HCM AI-scores from an independent cohort of 15,147 patients with an ECG in 2022. Results: Among the 200 patients in 2021 (median age 71 years, 48% female), 96 (48%) were likely false-positive HCM AI-score results, 71 (36%) definite or likely true-positive results, and 33 (16%) indeterminate. The CHS score included a history of surgical septal myectomy, coronary artery bypass graft surgery, cardiac valve replacement, and pacemaker, and had an AUC of 0.88 (95% CI 0.83-0.92) for the differentiation of true- versus false-positive AI results. In the 2022 cohort, the CHS score had an AUC of 0.82 (95% CI 0.76 - 0.88). After limiting the cohort to HCM candidates identified by the CHS score, the false-positive results rate was reduced to 27/114 (24%). Conclusions: By applying the CHS score to patients with positive HCM AI-screening results, the false-positive rate decreased from 49% to 24%. Utilizing a clinical model used in tandem with an AI model improved diagnostic yield.

Development and internal validation of a prediction model for acute kidney injury following cardiac valve replacement surgery

BackgroundAcute kidney injury (AKI) is a common complication after cardiac surgery. This study aims to develop and validate a risk model for predicting AKI after cardiac valve replacement surgery. MethodsData from patients undergoing surgical valve replacement between January 2015 and December 2018 in our hospital were retrospectively analyzed. The subjects were randomly divided into a derivation cohort and a validation cohort at a ratio of 7:3. The primary outcome was defined as AKI within 7 days after surgery. Logistic regression analysis was conducted to select risk predictors for developing the prediction model. Receiver operator characteristic curve (ROC), calibration plot and clinical decision curve analysis (DCA) will be used to evaluate the discrimination, precision and clinical benefit of the prediction model. ResultsA total of 1159 patients were involved in this study. The prevalence of AKI following surgery was 37.0% (429/1159). Logistic regression analysis showed that age, hemoglobin, fibrinogen, serum uric acid, cystatin C, bicarbonate, and cardiopulmonary bypass time were independent risk factors associated with AKI after surgical valve replacement (all P < 0.05). The areas under the ROC curves (AUCs) in the derivation cohort and the validation cohort were 0.777 (95% CI 0.744–0.810) and 0.760 (95% CI 0.706–0.813), respectively. The calibration plots indicated excellent consistency between the prediction probability and actual probability. DCA demonstrated great clinical benefit of the prediction model. ConclusionsWe developed a prediction model for predicting AKI after cardiac valve replacement surgery that was internally validated to have good discrimination, calibration, and clinical practicability.

Risk Factors and Outcomes of Protein-Calorie Malnutrition in Chronic Heart Failure Patients Undergoing Elective Cardiac Surgery.

Chronic heart failure (CHF) patients are often malnourished. Our aim was to determine the effect of protein-calorie malnutrition (PCM) on in-hospital outcomes in CHF patients following elective cardiac surgery and to identify risk factors for PCM in this patient population. A retrospective analysis of the National Inpatient Sample (NIS) database was conducted from2016 to 2018. In-hospital outcomes in adult patients with CHF undergoing elective coronary artery bypass graft (CABG) with cardiopulmonary bypass-assist or cardiac valve replacement surgeries were analyzed. Propensity-score matching was used to match CHF patients with and without PCM and followed by logistic regression analysis. A multivariate logistic regression model was used to identify the risk factors associated with PCM in this population. In total 25,940 CHF patients were identified, of which 6,271 underwent elective CABG and 19,669 underwent valve replacement surgeries. The prevalence of PCM in CHF patients undergoing CABG and valve replacement was 3.9% and 2.9%, respectively. CHF patients with PCM had significantly higher risk of in-hospital mortality, post-operative cardiac and gastrointestinal complications compared to CHF patients without PCM. The mean hospital length of stay was twice as high in the PCM group (mean days: 18.6 vs 9.9). Female gender, Black race (vsWhite race), a high Charlson Comorbidity Index, Medicare/Medicaid insurance status (vsprivate insurance), and CHF (systolic and combined systolic and diastolic) were independently associated with significantly higher risk of PCM diagnosis. CHF patients with PCM who undergo elective CABG or valve replacement surgeries are at a significantly higher risk of mortality, post-operative cardiac and gastrointestinal complications, and increased duration of hospital stay compared to those without PCM. Future prospective studies should assess the CHF patients who are at a higher risk of PCM and whether correcting pre-operative nutrition in this surgical population can improve outcomes following cardiac surgery.

Does Exercise-Based Cardiac Rehabilitation Reduce Mortality and Hospitalization Rates After Heart Valve Surgery?: A Cochrane Review Summary With Commentary.

Does Exercise-Based Cardiac Rehabilitation Reduce Mortality and Hospitalization Rates After Heart Valve Surgery?: A Cochrane Review Summary With Commentary.

Gynaecological Laparoscopic Surgeries in the Omicron Era: Improvising the Management Skills After Lessons Learnt From the Delta Wave.

Background During the peak of the Omicron wave, elective laparoscopic surgeries were restricted; however, semi-emergency and emergency cases were managed despite the limited resources and manpower. We conducted this study to assess the types of gynaecological laparoscopic surgeries performed, the difficulties faced during the Omicron wave, and how we could implement the lessons learnt from the previous Delta wave for better management of gynaecological cases in the Omicron wave. Methodology We conducted a prospective cohort study over a period of three months involving 105 patients who underwent laparoscopic surgeries. Based on the decision regarding surgical incision time, the surgeries were sub-classified into immediate, urgent, and expedited. The surgical outcome and satisfaction rates among the patients were assessed through various parameters. Results Most of the women (81.9%) were pre-menopausal. Diabetes and chronic hypertension were the predominant medical co-morbidities. Three patients had a history of cardiac valve replacement which required switching warfarin to unfractionated heparin in the pre-operative period. Nearly three-fourthsof the study patients were doubly vaccinated against coronavirus disease 2019 (COVID-19) (77; 73.4%). A total of 14 (13.3%) patients had a history of COVID-19 infection in the past two weeks prior to the current admission. Immediate, urgent, and expedited surgeries comprised 11.4%, 22.8%, and 65.8% of total surgeries, respectively. On assessing the ease of pre-operative preparation according to the five-point Likert scale, immediate, urgent, and expedited surgeries were rated with a mean score of two, four, and five, respectively. The mean duration of surgery in the immediate and urgent groups was 37.6 and 44.2 minutes, respectively. The expedited group comprising mostly laparoscopic myomectomies and hysterectomies required an average duration of 92.6 minutes. The mean rating of patient satisfaction measured by the Likert scale was four, five, and five, respectively, in the three subgroups. Pre-operative patient preparation during the Omicron wave was faster, thereby decreasing the decision to incision interval compared to the Delta wave. Conclusions Thelessons learnt from the previous Delta wave were used to modify the existing hospital policies in the Omicron wave. More number of vaccinated ground staff, less stringent intubation and extubation protocols during surgery, and lesser duration of post-operative stay helped modify our existing hospital policies for better patient care and satisfaction.

Prediction of depression among patients with cardiovascular disease scheduled cardiac surgery using an AI-empowered pipeline

Abstract Introduction Several studies have demonstrated, that one in three patients with cardiovascular disease (CVD) suffers from depression, and depression increases the likelihood for cardiac morbidity and mortality in the CVD population by 2–3-fold, independently of traditional risk factors or gender. Purpose The aim of this work is to predict depression in patients with CVD. Methods The clinical study was conducted in the cardiac surgical intensive care unit of The Central Clinical Hospital, the Medical University of Lodz in Poland, among patients scheduled for elective coronary artery bypass graft surgery (CABG). 224 patients signed an informed consent form, met the inclusion criteria and were enrolled in the study. All the patients had chronic coronary syndromes. The inclusion criteria were: consecutive adult patients scheduled for CABG surgery or CABG surgery with cardiac valve repair or replacement (CVR). The study population was examined by a psychiatrist the day prior to the scheduled operation, a diagnosis of major depressive disorder (MDD) was established on the basis of DSM-5 criteria. A data curation pipeline was applied to automatically remove outliers and duplicated fields in the input dataset. An AI-empowered pipeline was developed to classify patients at higher risk for depression. Random downsampling with replacement was applied to deal with the increased class imbalance by taking into consideration two confound factors, namely the Mini Mental State Examination and Hemoglobin concentration &amp;lt;10mg/dl. The downsampling process was repeated K times. In each iteration, three bagging and boosting ML schemas were utilized for the classification task including the AdaBoost (adaptive boosting), Random Forests and Extreme Gradient boosting trees (XGBoost). To this end, a nested cross-validation process was applied for hyperparameter optimization and model validation, where: (i) a 3-fold cross-validation process was first applied to seek for the optimal set of hyperparameters based on the grid search approach by tuning core parameters, including the learning rate, number of estimators, and max depth, among others, and (ii) a stratified 5-fold cross-validation process was subsequently used to evaluate the performance of the best model from the previous stage by computing the classification accuracy, sensitivity, specificity, and area under the ROC curve (AUC). The performance evaluation results were averaged across the 5 folds and across the downsampling iterations. Shappley additive explanation analysis was finally applied to provide explainable risk factors for depression. Results sRAGE was significantly correlated with depression (r=0.32, p=0.038). The Random forests classifier presented the highest performance to predict depression (Accuracy: 0.71, Sensitivity: 0.71, Specificity: 0.75 and AUC: 0.74). Conclusions Depression can be predicted with 71% accuracy at patients with CVD and elevated sRAGE values. Funding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): HORIZON2020

Risk predictors and outcomes of infective endocarditis among adult patients with congenital heart disease

Abstract Background Infective endocarditis (IE) is a serious disease associated with increased morbidity and mortality. Patients with adult congenital heart disease (ACHD) have been reported to be at a particularly increased risk of infective endocarditis (IE). Purpose To investigate the risk predictors of IE, and the long-term risk of IE among ACHD patients aged 18–65 years, compared with matched controls without ACHD, in a nationwide setting. Methods All patients with ACHD in Sweden born in years 1952–1999 and who survived until 18 years of age were followed in the National Patient Register and Cause of Death Register until year 2017. For each case of ACHD, approximately ten controls without ACHD were randomly selected from the Total Population Register and matched by birth year and sex. The study population was followed from 18 years of age and until a first time diagnosis of IE, death or end of study. Both comorbidities and occurrence of ACHD related surgery were collected from 1970 and onwards. Cox proportional hazard models were used to predict the risk of IE. Results Altogether, 36,189 ACHD patients and 403,962 controls without ACHD were included. A total of 706 (1.95%) ACHD patients and 147 (0.04%) controls developed IE during a median follow-up of 15.5 (interquartile range (IQR) 6.9–28.5) years (ACHD) and 15.5 (IQR 7.5–28.5) years (controls). ACHD patients were somewhat younger at age of IE diagnosis compared with controls, median age 33.9 (IQR 25.4–44.1) years in ACHD vs 39.8 (IQR 30.6–52.0) years in controls. The overall risk of IE was markedly higher among ACHD patients compared with controls, with a hazard ratio (HR) of 54.8 (95% confidence interval (CI), 45.9–65.5). More than one third of the ACHD patients with IE (n=272, 38.5%) had undergone any kind of previous congenital heart surgery whereof 122 (44.9%) had undergone valve replacement (mechanical/biological) prior to IE. In ACHD patients, the most important risk predictors for IE were ACHD related cardiac surgery and valve replacement surgery, HR 117 (95% CI 93.0–148) and HR 74.8 (95% CI 56.4–99.2), respectively. Diabetes mellitus, previous ischemic stroke and presence of an intracardiac electronic device also predicted the risk of IE, however, they were less important predictors (diabetes: HR 1.69, 95% CI 1.01–2.82, ischemic stroke: HR 1.75, 95% CI 1.21–2.52, electronic device: HR 1.59, 95% CI 1.05–2.39). Conclusion The risk of developing IE was found to be almost 55 times higher in patients with ACHD aged 18–65 years compared with matched controls. Previous ACHD related surgery and valve replacement were the most significant risk predictors. These results underscore the need of continuous clinical follow-up as well as the need of further research to prevent this serious complication of ACHD. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): The work was supported by grants from the Swedish state under an agreement between the Swedish government and country councils, the ALF-agreement (grant numbers 236611 and 917361); and the Swedish Heart-Lung Foundation (grant number: 20180644 and 20200521).

Effects of Dexmedetomidine Pretreatment, Posttreatment, and Whole-Course Pumping on Myocardial Damage during Cardiac Valve Replacement.

To compare the effects of dexmedetomidine (DEX) pretreatment, posttreatment, and whole-course pumping on myocardial protection during cardiac valve replacement.One hundred and twenty patients undergoing cardiac valve replacement were randomly divided into the follow groups: DEX pretreatment (D1 group), DEX posttreatment (D2 group), DEX whole-course pumping (D3 group), and Control (C group). The concentrations of cardiac troponin I (cTnI), malondialdehyde (MDA), tumor necrosis factor alpha (TNF-α), rate of spontaneous heart rebound after aortic opening, time to heart rebound, incidence of arrhythmia, and use of sufentanil and vasoactive drugs were recorded.Compared with group C, the concentrations of cTnI, MDA, and TNF-α in the D1, D2, and D3 groups were lower, especially in the latter. The time to heart rebound was prolonged in all three groups (P < 0.05). The rate of automatic rebound was increased (P < 0.05) while the incidence of arrhythmia was decreased (P < 0.05) in all groups compared with group C. Group D3 had the highest rate of automatic rebound and the lowest incidence of arrhythmia. Compared with groups C and D2, the use of sufentanil and dopamine was lower in groups D1 and D3 (P < 0.05), especially in the latter.During cardiac valve replacement, DEX pretreatment, posttreatment, and whole-course pumping could have myocardial protective effects. The latter showed better effects.

Massive Thrombosis of Mitral Bioprosthesis Due to SARS-CoV-2 Infection

Thromboembolic events have been reported as frequent and fearsome complications in patients affected by SARS-CoV-2 infection. Patients undergoing cardiac valve replacement exhibit an increased risk of valve thrombosis, even with prosthetic biological valves, and especially in the first period after surgery. The management of these patients is challenging and requires prompt interventions. We report the case of a young woman infected by SARS-CoV-2 three months after double cardiac valve replacement that developed a massive prosthetic biological valve thrombosis despite optimal anticoagulant therapy.

Deep learning-based reconstruction on cardiac CT yields distinct radiomic features compared to iterative and filtered back projection reconstructions

We aimed to determine the effects of deep learning-based reconstruction (DLR) on radiomic features obtained from cardiac computed tomography (CT) by comparing with iterative reconstruction (IR), and filtered back projection (FBP). A total of 284 consecutive patients with 285 cardiac CT scans that were reconstructed with DLR, IR, and FBP, were retrospectively enrolled. Radiomic features were extracted from the left ventricular (LV) myocardium, and from the periprosthetic mass if patients had cardiac valve replacement. Radiomic features of LV myocardium from each reconstruction were compared using a fitting linear mixed model. Radiomics models were developed to diagnose periprosthetic abnormality, and the performance was evaluated using the area under the receiver characteristics curve (AUC). Most radiomic features of LV myocardium (73 of 88) were significantly different in pairwise comparisons between all three reconstruction methods (P < 0.05). The radiomics model on IR exhibited the best diagnostic performance (AUC 0.948, 95% CI 0.880–1), relative to DLR (AUC 0.873, 95% CI 0.735–1) and FBP (AUC 0.875, 95% CI 0.731–1), but these differences did not reach significance (P > 0.05). In conclusion, applying DLR to cardiac CT scans yields radiomic features distinct from those obtained with IR and FBP, implying that feature robustness is not guaranteed when applying DLR.