Surgical versus medical management of infective endocarditis after TAVR.

We assessed the incidence of aortic valve surgery intervention in the treatment of infective endocarditis (IE) after transcatheter aortic valve replacement (TAVR) and compared the characteristics and outcomes of surgical intervention versus medical management alone in this cohort using a nationwide data set. We identified all the hospitalizations in patients undergoing TAVR who developed IE within 1-year (i.e., early IE) of the procedure from 2014 to 2017 using the Nationwide Readmission Database (NRD). The primary outcomes of the study were in-hospital mortality. A total of 906 hospitalizations were identified for IE amongst the TAVR patients from 2014 to 2017 of which 20 (2.21%) underwent aortic valve surgery during the hospitalization. Patients undergoing surgery were younger, more likely to have Staphylococcus aureus endocarditis, cardiogenic shock, and acute kidney injury (AKI) during the hospitalization. There were no significant differences in in-hospital mortality (9.9% vs. 12.4%, p = 0.824; adjusted odds ratio (aOR): 0.26 (0.01-1.58), p = 0.223) and 30-day readmissions. However, the length of stay and hospitalization costs were higher in surgical intervention group. The important predictors of in-hospital mortality in TAVR-related IE patients were dialysis during IE hospitalization, AKI, cardiogenic shock, Staphylococcus aureus endocarditis, stroke, and female sex. The utilization of surgical management for IE post-TAVR during the index hospitalization is low, and there is no significant mortality benefit with surgical intervention as compared with the medical management.

Google trends in "anatomy": pre-pandemic versus during COVID-19 pandemic.

PURPOSE: The purpose of the present study was to assess the online search behavior for the keyword "anatomy" worldwide and to compare the pre-pandemic and during COVID-19 pandemic scenario for the same. METHODS: Google trends tool was used for the assessment of the search behavior for the term "anatomy". The data, i.e. relative search volume (RSV) were downloaded for this term using the all categories, web search and only YouTube settings during a period from 1.1.2019 to 3.31.2021 from www.trends.google.com . The geographic trends for this search query were plotted across the world. RESULTS: Seasonal peaks were observed for the search term "anatomy" during the first 3 months of the year and in months of September, October and November in 2019. Similar seasonal peaks were observed for the year 2020 except that there was sudden decrease in RSV for term "anatomy" in the month of March. Though trend for the rest of the year was same, but there was general lower RSV in 2020. The country with highest search hit was United States followed by Canada, Ireland, Australia and Philippines. CONCLUSION: The search trend for pre-pandemic and pandemic period was similar with overall lower RSV during 2020, where it noticeably decreased during the initial phase of lockdown, i.e. in the month of March. As the whole world is still in the COVID-19 pandemic era, the future studies may report the google trends once the pandemic is over and may compare the post-pandemic trend for the same.

Applications of artificial intelligence and machine learning approaches in echocardiography.

Artificial intelligence and machine learning approaches have become increasingly applied in the field of echocardiography to streamline diagnostic and prognostic assessments, and to support treatment decisions. Artificial intelligence and machine learning have been applied to aid image acquisition and automation. They have also been applied to the integration of clinical and imaging data. Applications of artificial intelligence and machine learning approaches in echocardiography in conjunction with health information databases may be promising in improving the classification and treatment of many cardiac conditions. This review article provides an overview of the applications of artificial intelligence and machine learning approaches in echocardiography.

Machine Learning Models to Predict Major Adverse Cardiovascular Events After Orthotopic Liver Transplantation: A Cohort Study.

OBJECTIVE: To develop machine learning models that can predict post-transplantation major adverse cardiovascular events (MACE), all-cause mortality, and cardiovascular mortality in patients undergoing liver transplantation (LT). DESIGN: Retrospective cohort study. SETTING: High-volume tertiary care center. PARTICIPANTS: The study comprised 1,459 consecutive patients undergoing LT between January 2008 and December 2019. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: MACE, all-cause mortality, and cardiovascular mortality were modeled using logistic regression, least absolute shrinkage and selection surgery regression, random forests, support vector machine, and gradient-boosted modeling (GBM). All models were built by splitting data into training and testing cohorts, and performance was assessed using five-fold cross-validation based on the area under the receiver operating characteristic curve and Harrell's C statistic. A total of 1,459 patients were included in the final cohort; 1,425 (97.7%) underwent index transplantation, 963 (66.0%) were female, the median age at transplantation was 57 (11-70) years, and the median Model for End-Stage Liver Disease score was 20 (6-40). Across all outcomes, the GBM model XGBoost achieved the highest performance, with an area under the receiver operating curve of 0.71 (95% confidence interval [CI] 0.63-0.79) for MACE, a Harrell's C statistic of 0.64 (95% CI 0.57-0.73) for overall survival, and 0.72 (95% CI 0.59-0.85) for cardiovascular mortality over a mean follow-up of 4.4 years. Examination of Shapley values for the GBM model revealed that on the cohort-wide level, the top influential factors for postoperative MACE were age at transplantation, diabetes, serum creatinine, cirrhosis caused by nonalcoholic steatohepatitis, right ventricular systolic pressure, and left ventricular ejection fraction. CONCLUSION: Machine learning models developed using data from a tertiary care transplantation center achieved good discriminant function in predicting post-LT MACE, all-cause mortality, and cardiovascular mortality. These models can support clinicians in recipient selection and help screen individuals who may be at elevated risk for post-transplantation MACE.

Anatomy education of medical and dental students during COVID-19 pandemic: a reality check.

PURPOSE: During this forced down-time of COVID-19 pandemic, shift to virtual anatomy education is the solitary solution to support the learning of students. The purpose of this study was to understand the visible and invisible potential challenges being faced by the 1st year medical and dental students while attending digital anatomy classes. METHODS: The present study was conducted on 81st year medical and dental students who were admitted to their respective college in August 2019 and were willing to participate in the study. A multiple choice close-ended questionnaire regarding their opinion on virtual classes was designed and feedback was taken from the students. RESULTS: Majority (65%) of the students agreed that they missed their traditional anatomy learning i.e., dissection courses, face to face lectures and interaction with mentors. The students strongly felt the lack of confidence and difficulty in the topics completed without dissections, models, microscopic slides and other modalities. 83% felt lack of proper gadgets, high-band width and strong internet connections, a potential barrier in their digital learning. Lack of self-motivation was felt by 69% students. CONCLUSIONS: The current situation of anatomy education is not intentional, and is not the long term silver bullet solution for a visual subject like anatomy. Though learners face a lot of challenges, however, a shift to online must be supported at this time of health crisis. As the digital learning may go for indefinite period, the feedback of students may be helpful for relevant and timely modifications in digital anatomy education.

Utility of Artificial Intelligence Amidst the COVID 19 Pandemic: A Review.

The term machine learning refers to a collection of tools used for identifying patterns in data. As opposed to traditional methods of pattern identification, machine learning tools relies on artificial intelligence to map out patters from large amounts of data, can self-improve as and when new data becomes available and is quicker in accomplishing these tasks. This review describes various techniques of machine learning that have been used in the past in the prediction, detection and management of infectious diseases, and how these tools are being brought into the battle against COVID-19. In addition, we also discuss their applications in various stages of the pandemic, the advantages, disadvantages and possible pit falls.

Comparison of Contemporary Treatment Strategies in Patients With Cardiogenic Shock Due to Severe Aortic Stenosis.

BACKGROUND: The aims of this study were to understand the incidence and outcomes of patients with cardiogenic shock (CS) due to severe aortic stenosis (AS), and the impact of conventional treatment strategies in this population. METHODS AND RESULTS: All patients admitted to the Cleveland Clinic cardiac intensive care unit between January 1, 2010 and December 31, 2021 with CS were retrospectively identified and categorized into those with CS in the setting of severe AS versus CS without AS. The impact of various treatment strategies on mortality was further assessed. We identified 2754 patients with CS during the study period, of whom 216 patients (8%) had CS in the setting of severe AS. Medical management was associated with the highest 30-day mortality when compared with either balloon aortic valve replacement or aortic valve replacement (surgical or transcatheter aortic valve replacement) (hazard ratio, 3.69 [95% CI, 2.04-6.66]; P<0.0001). Among patients who received transcatheter therapy, 30-day mortality was significantly higher in patients who received balloon aortic valvuloplasty versus transcatheter aortic valve replacement (26% versus 4%, P=0.02). Both surgical and transcatheter aortic valve replacement had considerably lower mortality than medical management and balloon aortic valvuloplasty at 30 days and 1 year (P<0.05 for both comparisons). CONCLUSIONS: CS due to severe AS is associated with high in-hospital and 30-day mortality, worse compared with those with CS without AS. In suitable patients, urgent surgical aortic valvuloplasty or transcatheter aortic valve replacement is associated with favorable short- and long-term outcomes. Although balloon aortic valvuloplasty may be used to temporize patients with CS in the setting of severe AS, mortality is ≈50% if not followed by definitive aortic valve replacement within 90 days.

Outcomes of patients with cardiac amyloidosis undergoing percutaneous left atrial appendage occlusion.

BACKGROUND: There is limited data on the safety and efficacy of left atrial appendage occlusion (LAAO) devices in patients with cardiac amyloidosis. We examined the outcomes of patients with cardiac amyloidosis undergoing LAAO device implantation in a nationally representative cohort of patients. METHODS: The National Readmissions Database (NRD) was analyzed from 2016 to 2019 to identify patients ≥ 18 years old with atrial fibrillation (AF) undergoing LAAO. Patients were divided into those with cardiac amyloidosis and those without cardiac amyloidosis. A multivariable logistic regression model was utilized to assess the independent association of cardiac amyloidosis with in-hospital, 30-day/90-day/180-day outcomes after adjusting for confounders. RESULTS: Our cohort included 54,900 LAAO implantation procedures, of which 220 (0.4%) had cardiac amyloidosis. Patients with cardiac amyloidosis had a lower proportion of women and a lower prevalence of comorbidities including anemia, obesity, diabetes, and peripheral vascular disorders but a higher prevalence of stroke, as compared to those without cardiac amyloidosis. On multivariable analysis, cardiac amyloidosis was associated with significantly higher odds of peri-procedural major adverse events (adjusted odds ratio [aOR]: 2.69; 95% confidence interval [CI]: 1.41-5.14; p<0.01) and neurological complications (aOR: 5.48; 95% CI: 2.47-12.8; p<0.01). There was no difference in the odds of other peri-procedural complications, in-hospital mortality, hospital resource utilization, and 30/90/180-day all-cause/bleeding/stroke-related readmissions between both groups. CONCLUSION: Patients with cardiac amyloidosis undergoing LAAO device implantation have an increased risk of peri-procedural complications without any difference in bleeding/stroke-related readmissions. These hypothesis-generating findings need validation in future prospective studies.

Sex Differences in the Progression and Long-Term Outcomes of Native Mild to Moderate Aortic Stenosis.

BACKGROUND: There are limited data on the sex differences in the hemodynamic progression and outcomes of early-stage aortic stenosis (AS). OBJECTIVES: The authors sought to determine sex differences in hemodynamic progression and outcomes of mild to moderate native AS. METHODS: This was a retrospective observational cohort study including patients with mild to moderate native tricuspid AS from the Cleveland Clinic echocardiographic database between 2008 and 2016 and followed until 2018. All-cause mortality, aortic valve replacement (AVR), and disease progression assessed by annualized changes in echocardiographic parameters were analyzed based on sex. RESULTS: The authors included 2,549 patients (mean age, 74 ± 7 years and 42.5% women) followed over a median duration of 5.7 years. There was no difference in all-cause mortality between sexes irrespective of age, baseline disease severity, progression to severe AS, and receipt of AVR. Relative to men, women had similar all-cause mortality but lower risk of AVR (adjusted HR: 0.81 [95% CI: 0.67-0.91]; P = 0.009) at 10 years. On 1:1 propensity-matched analysis, men had a significantly faster disease progression represented by greater increases in the median of annualized change in mean gradient (2.10 vs 1.15 mm Hg/y, respectively, P < 0.001), maximum transvalvular velocity (0.42 vs 0.28 m/s/y), left ventricular end-diastolic diameters (0.15 vs 0.048 mm/m2.7/y) (P = 0.014). Women have significantly higher left ventricular ejection fraction, filling pressures, and left ventricular septum thickness over time on follow-up echocardiograms compared with men. CONCLUSIONS: Women with mild to moderate AS had slower hemodynamic progression of AS, were more likely to have preserved left ventricular ejection fraction and concentric left ventricular hypertrophy in addition to lower incidence of AVR compared with men despite similar mortality. These findings provide further evidence that there are distinct sex-specific longitudinal echocardiographic and clinical profiles in patients with AS.

Role of Serum Soluble Interleukin-2 Receptor Level in the Diagnosis of Sarcoidosis: A Systematic Review and Meta-Analysis.

BACKGROUND AND AIM: Serum Soluble Interleukin-2 Receptor (sIL-2R) levels are used clinically as a disease activity marker for systemic sarcoidosis. Studies have investigated the diagnostic role of serum soluble interleukin-2 receptor (sIL-2R) level for sarcoidosis relative to biopsy. We performed a systematic review and meta-analysis of studies evaluating the diagnostic utility of sIL-2R. METHODS: We carried out an electronic search in Medline, Embase, Google Scholar, and Cochrane databases using keyword and Medical Subject Heading (MeSH) terms: sarcoidosis and sIL-2R. Studies evaluating the sIL-2R levels as a diagnostic tool in clinically diagnosed or biopsy-proven sarcoidosis patients compared to control groups with non-sarcoidosis patients were included. Forest plots were constructed using a random effect model depicting pooled sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy. RESULTS: We selected ten studies comprising 1477 patients, with 592 in the sarcoidosis group and 885 in the non- sarcoidosis group. Pooled sensitivity and specificity of sIL-2R levels were 0.88 (95% CI: 0.75-0.95) and 0.87 (95% CI 0.73-0.94) respectively. Pooled negative predictive value and positive predictive value were 0.91 (95% CI 0.77-0.97) and 0.85 (95% CI 0.59-0.96) respectively with diagnostic accuracy of 0.86 (95% CI 0.71- 0.93). CONCLUSION: In addition to its utility as a marker of sarcoidosis disease activity, sIL-2R has high diagnostic accuracy. Despite the limitations of the heterogenous sarcoidosis population and different sIL-2R cutoffs, our results suggest that sIL-2R is an important biomarker that can be used to confirm sarcoidosis diagnosis in unconfirmed or unclear cases.

Impact of Psychosocial Risk Factors on Outcomes of Atrial Fibrillation Patients undergoing Left Atrial Appendage Occlusion Device Implantation.

BACKGROUND: The impact of psychosocial risk factors (PSRFs) on outcomes in patients undergoing percutaneous left atrial appendage occlusion (LAAO) device implantation is unclear. We aimed to analyze the association of psychosocial risk factors with outcomes in patients undergoing LAAO. METHODS: Data were extracted from the Nationwide readmissions database for the calendar years 2016-2019. LAAO device implantations were identified using ICD-10-CM code 02L73DK. The outcomes of interest included procedural complications, inpatient mortality, resource utilization, and 30-day readmissions. Patients were divided into two cohorts based on the absence or presence of PSRFs. RESULTS: Our cohort included a total of 54,900 patients, of which, 19,984 (36.4%) had ≥ 1 PSRF as compared to 34,916 (63.6%) with no PSRFs. The prevalence of major complications (3.3% vs 2.8%, p=0.03) was significantly higher in patients with ≥ 1 PSRF as compared to no PSRFs. Furthermore, patients with ≥ 1 PSRF had a significantly higher 30-day readmission rate (6.9% vs 6.2%, p=0.02). In the multivariable model, the presence of ≥ 1 PSRF was associated with significantly higher odds of overall complications [adjusted odds ratio (aOR):1.11; 95% confidence interval (CI): 1.01-1.21; p=0.02]. Additionally, the presence of ≥ 1 PSRF was associated with higher odds of prolonged hospital stay for more than one day (aOR: 1.30; 95% CI: 1.21-1.40; p<0.01). CONCLUSION: The high prevalence of PSRFs may be associated with poorer outcomes in patients with AF patients undergoing LAAO device implantations. These data merit further study to help in the selection process of patients for LAAO for improved outcomes.

MitraCox Score Predicts In-Hospital Mortality in Patients Admitted for Transcatheter Edge-to-Edge Mitral Valve Repair.

As mitral valve transcatheter edge-to-edge repair (M-TEER) is evolving as an effective treatment for high-risk surgical patients with mitral regurgitation, there is a pressing need for cardiologists to optimize resources through risk stratification of in-hospital mortality for this patient population. Although current risk-prediction models have been shown to predict adverse outcomes with reasonable accuracy, models trained using the US nationwide population are lacking. This study aimed to identify clinical, demographic, and procedural features that predict in-hospital mortality, and to derive and validate an in-hospital mortality risk-prediction tool in patients who have undergone M-TEER. A total of 9,373 admissions from the Nationwide Readmissions Database of patients who underwent M-TEER between 2015 and 2018 were used to develop and validate the model. We first performed least absolute shrinkage and selection operator (LASSO) regularization of Cox regression (Coxnet) that is 10-fold cross-validated. The non-zero coefficients were multiplied with the respective values of each observation of the predictors to build the scoring formula. Out of 9,373 admissions, 196 patients (2%) died in-hospital during index admission. In descending order, the top variables that were most predictive of in-hospital mortality were higher age, presence of fluid and electrolyte disturbance, and large metropolitan location of the hospital. The validation C-statistic of the MitraCox score was 0.82. Using X-tile software (Yale School of Medicine, New Haven, Connecticut), 2 cutoffs of the score were determined on the basis of in-hospital mortality and length of stay, and the survival of the population was classified into 3 risk groups: low, intermediate, and high. The scoring system deployed online as a web-based calculator can be accessed at https://kathavs.shinyapps.io/Mitracox_Kapadia/. In conclusion, MitraCox score is easy to calculate and predicts in-hospital mortality depending on length of stay in a dynamic manner.

Advances in multi-modality imaging for constrictive pericarditis and pericardial inflammation: role of imaging-guided therapy.

INTRODUCTION: Constrictive pericarditis (CP) can result from uncontrolled inflammation of the pericardium. This can be due to various etiologies. CP can lead to both left- and right-sided heart failure with associated poor quality of life, so early recognition is key. The evolving role of multimodality cardiac imaging allows for earlier diagnosis and facilitates management to help mitigate this adverse outcome. AREAS COVERED: This review discusses the pathophysiology of constrictive pericarditis, chronic inflammation and autoimmune etiologies, clinical presentation of CP, and advances in multimodality cardiac imaging for diagnosis and management. Echocardiography and cardiac magnetic resonance (CMR) imaging remain cornerstone modalities to evaluate this condition, whereas additional imaging modalities such as computed tomography and FDG-positron emission tomography can provide complementary information. EXPERT OPINION: Advances in multimodality imaging allow for a more precision diagnosis of constrictive pericarditis. There has been a paradigm shift in pericardial disease management with advances in multimodality imaging, especially CMR, to detect subacute and chronic inflammation. This has enabled imaging-guided therapy (IGT) to both help prevent and potentially reverse established constrictive pericarditis.

A Systematic Review and Meta-Analysis of Prevalence, Characteristics, and Impact of Mitral Annular Calcification on Outcomes After Transcatheter Aortic Valve Implantation.

There is a paucity of data on the prognostic impact of mitral annular calcification (MAC) in patients who underwent transcatheter aortic valve implantation (TAVI) with conflicting results being reported by the studies that are published. Therefore, we performed a meta-analysis to assess the short-term and long-term outcomes of MAC in patients after TAVI. Of 25,407 studies identified after the initial database search, 4 observational studies comprising 2,620 patients (2,030 patients in the nonsevere MAC arm and 590 patients in the severe MAC arm) were included in the final analysis. Compared with patients with nonsevere MAC, the severe MAC group was associated with significantly higher incidences of overall bleeding (0.75 [0.57 to 0.98], p = 0.03, I2 = 0%) at 30 days. However, no significant difference was observed between the 2 groups for the rest of the 30-day outcomes: all-cause mortality (0.79 [0.42 to 1.48], p = 0.46, I2 = 9%), myocardial infarction (1.62 [0.37 to 7.04], p = 0.52, I2 = 0%), cerebrovascular accident or stroke (1.22 [0.53 to 2.83], p = 0.64, I2 = 0%), acute kidney injury (1.48 [0.64 to 3.42], p = 0.35, I2 = 0%), and pacemaker implantation (0.70 [0.39 to 1.25], p = 0.23, I2 = 68%). Similarly, follow-up outcomes also showed no significant difference between the 2 groups: all-cause mortality (0.69 [0.46 to 1.03], p = 0.07, I2 = 44%), cardiovascular mortality (0.52 [0.24 to 1.13], p = 0.10, I2 = 70%) and stroke (0.83 [0.41 to 1.69], p = 0.61, I2 = 22%). The sensitivity analysis, however, demonstrated significant results for all-cause mortality (0.57 [0.39 to 0.84], p = 0.005, I2 = 7%) by removing the study by Okuno et al5 and cardiovascular mortality (0.41 [0.21 to 0.82], p = 0.01, I2 = 66%) by removing the study by Lak et al.7 In conclusion, our meta-analysis corroborates the notion that isolated MAC is not an independent predictor of long-term mortality after TAVI and determines severe MAC to be a predictor of mortality at follow-up because of the higher incidence of mitral valve dysfunction associated with it.