Prostate Cancer Therapy Cardiotoxicity Map (PROXMAP) for Advanced Disease States: A Systematic Review and Network Meta-analysis with Bayesian Modeling of Treatment Histories.

Background And Objective: Recommendations of first-line therapies for metastatic hormone-sensitive (mHSPC), nonmetastatic castrate-resistant (M0CRPC), and metastatic castrate-resistant (mCRPC) prostate cancer do not account for cardiotoxicity due to a lack of clear prior evidence. This manuscript assesses cardiotoxicity of these therapies.

Methods: We searched Ovid Medline, Elsevier Embase, and the Cochrane Library for randomized clinical trials (RCTs) from database inception to January 14, 2024.

Artificial Intelligence and Health Inequities in Dietary Interventions on Atherosclerosis: A Narrative Review.

Poor diet is the top modifiable mortality risk factor globally, accounting for 11 million deaths annually with half being from diet-linked atherosclerotic cardiovascular disease (ASCVD). Yet, most of the world cannot afford a healthy diet-as the hidden costs of the inadequate global food system total over USD 13 trillion annually-let alone the much more clinically, financially, and ecologically costly and resource-intensive medical interventions required to address the disease progression and acute complications of ASCVD. Yet, AI is increasingly understood as a force multiplying revolutionary technology which may catalyze multi-sector efforts in medicine and public health to better address these significant health challenges.

Prevalence, mortality, cost, and disparities in transcatheter mitral valve repair and replacement in cancer patients: Artificial intelligence and propensity score national 5-year analysis of 7495 procedures.

Introduction: We conducted the first comprehensive evaluation of the therapeutic value and safety profile of transcatheter mitral edge-to-edge repair (TEER) and transcatheter mitral valve replacement (TMVR) in individuals concurrently afflicted with cancer.

Methods: Utilizing the National Inpatient Sample (NIS) dataset, we analyzed all adult hospitalizations between 2016 and 2020 (n = 148,755,036). The inclusion criteria for this retrospectively analyzed prospective cohort study were all adult hospitalizations (age 18 years and older).

Coronary Revascularization in Patients With Cancer.

Purpose Of Review: The treatment of coronary artery disease (CAD) in cancer patients is an evolving landscape. Recent data emphasizes the importance of aggressive management of cardiovascular risk factors and diseases in improving cardiovascular health in this unique group of patients regardless of cancer type or stage.

Recent Findings: Novel cancer therapeutics such as immune therapies and proteasome inhibitors have been associated with CAD.

Artificial intelligence-augmented analysis of contemporary procedural, mortality, and cost trends in carcinoid heart disease in a large national cohort with a focus on the "forgotten pulmonic valve".

Background: Carcinoid heart disease is increasingly recognized and challenging to manage due to limited outcomes data. This is the largest known cohort study of valvular pathology, treatment (including pulmonary and tricuspid valve replacements [PVR and TVR]), dispairties, mortality, and cost in patients with malignant carcinoid tumor (MCT).

Methods: Machine learning-augmented propensity score-adjusted multivariable regression was conducted for clincal outcomes in the 2016-2018 U.

Bioprosthetic valve monitoring in patients with carcinoid heart disease.

Background: Carcinoid heart disease (CnHD) is a frequent cause of morbidity and mortality in patients with neuroendocrine tumors and carcinoid syndrome. Although valve replacement surgery appears to decrease all-cause mortality in patients with advanced CnHD, few studies have investigated the outcomes of patients after valve replacement.

Methods: We conducted a multi-institution retrospective registry of patients who received both tricuspid and pulmonic bioprosthetic valve (TV/PV) replacements for advanced CnHD from November 2005 to March 2021.

Artificial Intelligence-Augmented Propensity Score, Cost Effectiveness and Computational Ethical Analysis of Cardiac Arrest and Active Cancer with Novel Mortality Predictive Score.

Background and objectives: Little is known about outcome improvements and disparities in cardiac arrest and active cancer. We performed the first known AI and propensity score (PS)-augmented clinical, cost-effectiveness, and computational ethical analysis of cardio-oncology cardiac arrests including left heart catheterization (LHC)-related mortality reduction and related disparities. Materials and methods: A nationally representative cohort analysis was performed for mortality and cost by active cancer using the largest United States all-payer inpatient dataset, the National Inpatient Sample, from 2016 to 2018, using deep learning and machine learning augmented propensity score-adjusted (ML-PS) multivariable regression which informed cost-effectiveness and ethical analyses.

Post-cardiac arrest PCI is underutilized among cancer patients: Machine learning augmented nationally representative case-control study of 30 million hospitalizations.

Background: Cancer patients are less likely to undergo percutaneous coronary intervention (PCI) after cardiac arrest, although they demonstrate improved mortality benefit from the procedure. We produced the largest nationally representative analysis of mortality of cardiac arrest and PCI for patients with cancer versus non-cancer.

Methods: Propensity score adjusted multivariable regression for mortality was performed in this case-control study of the United States' largest all-payer hospitalized dataset, the 2016 National Inpatient Sample.

Reclassification of Treatment Strategy with Fractional Flow Reserve in Cancer Patients with Coronary Artery Disease.

Background and Objectives: Cancer and coronary artery disease (CAD) often coexist. Compared to quantitative coronary angiography (QCA), fractional flow reserve (FFR) has emerged as a more reliable method of identifying significant coronary stenoses. We aimed to assess the specific management, safety and outcomes of FFR-guided percutaneous coronary intervention (PCI) in cancer patients with stable CAD.

Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations.

Background and Objectives: There are no nationally representative studies of mortality and cost effectiveness for fractional flow reserve (FFR) guided percutaneous coronary interventions (PCI) in patients with cancer. Our study aims to show how this patient population may benefit from FFR-guided PCI. Materials and Methods: Propensity score matched analysis and backward propagation neural network machine learning supported multivariable regression was performed for inpatient mortality in this case-control study of the 2016 National Inpatient Sample (NIS).

Percutaneous Coronary Intervention in Patients With Gynecological Cancer: Machine Learning-Augmented Propensity Score Mortality and Cost Analysis for 383,760 Patients.

Background: Despite the growing number of patients with both coronary artery disease and gynecological cancer, there are no nationally representative studies of mortality and cost effectiveness for percutaneous coronary interventions (PCI) and this cancer type.

Methods: Backward propagation neural network machine learning supported and propensity score adjusted multivariable regression was conducted for the above outcomes in this case-control study of the 2016 National Inpatient Sample (NIS), the United States' largest all-payer hospitalized dataset. Regression models were fully adjusted for age, race, income, geographic region, cancer metastases, mortality risk, and the likelihood of undergoing PCI (and also with length of stay [LOS] for cost).

Racial and Socioeconomic Disparities in Out-Of-Hospital Cardiac Arrest Outcomes: Artificial Intelligence-Augmented Propensity Score and Geospatial Cohort Analysis of 3,952 Patients.

Introduction: Social disparities in out-of-hospital cardiac arrest (OHCA) outcomes are preventable, costly, and unjust. We sought to perform the first large artificial intelligence- (AI-) guided statistical and geographic information system (GIS) analysis of a multiyear and multisite cohort for OHCA outcomes (incidence and poor neurological disposition).

Method: We conducted a retrospective cohort analysis of a prospectively collected multicenter dataset of adult patients who sequentially presented to Houston metro area hospitals from 01/01/07-01/01/16.

Stress cardiomyopathy in hospitalized patients with cancer: machine learning analysis by primary malignancy type.

Aims: Previous studies have shown that patients with stress (Takotsubo) cardiomyopathy (SC) and cancer have higher in-hospital mortality than patients with SC alone. No studies have examined outcomes in patients with active cancer and SC compared to patients with active cancer without SC. We aimed to assess the potential association between primary malignancy type and SC and their shared interaction with inpatient mortality.

TAVR in Cancer Patients: Comprehensive Review, Meta-Analysis, and Meta-Regression.

This study sought to systematically analyze the available clinical evidence on TAVR therapy in cancer patients with symptomatic severe AS. Aortic stenosis is the most common valvular heart disease in the world. TAVR has expanded the treatment options for this lethal disease process.

TAVR and cancer: machine learning-augmented propensity score mortality and cost analysis in over 30 million patients.

Introduction: Cardiovascular disease (CVD) and cancer are the top mortality causes globally, yet little is known about how the diagnosis of cancer affects treatment options in patients with hemodynamically compromising aortic stenosis (AS). Patients with cancer often are excluded from aortic valve replacement (AVR) trials including trials with transcatheter AVR (TAVR) and surgical AVR (SAVR). This study looks at how cancer may influence treatment options and assesses the outcome of patients with cancer who undergo SAVR or TAVR intervention.

Meta-analysis and machine learning-augmented mixed effects cohort analysis of improved diets among 5847 medical trainees, providers and patients.

Objective: We sought to produce the first meta-analysis (of medical trainee competency improvement in nutrition counseling) informing the first cohort study of patient diet improvement through medical trainees and providers counseling patients on nutrition.

Design: (Part A) A systematic review and meta-analysis informing (Part B) the intervention analysed in the world's largest prospective multi-centre cohort study on hands-on cooking and nutrition education for medical trainees, providers and patients.

Settings: (A) Medical educational institutions.

Race and Gender Disparity in the Surgical Management of Hepatocellular Cancer: Analysis of the Surveillance, Epidemiology, and End Results (SEER) Program Registry.

Background: The existence of race and gender disparity has been described in numerous areas of medicine. The management of hepatocellular cancer is no different, but in no other area of medicine, is the treatment algorithm more complicated by local, regional, and national health care distribution policy.

Methods: Multivariate logistic regression and Cox-regression were utilized to analyze the treatment of patients with hepatocellular cancer registered in SEER between 1999 and 2013 to determine the incidence and effects of racial and gender disparity.

Machine Learning-Augmented Propensity Score Analysis of Percutaneous Coronary Intervention in Over 30 Million Cancer and Non-cancer Patients.

It is unknown to what extent the clinical benefits of PCI outweigh the risks and costs in patients with vs. without cancer and within each cancer type. We performed the first known nationally representative propensity score analysis of PCI mortality and cost among all eligible adult inpatients by cancer and its types.

Antiepileptic Drug Management in Acute Ischemic Stroke: Are Vascular Neurologists Utilizing Electroencephalograms? An Observational Cohort Study.

Introduction: This study examines the utility of electroencephalography (EEG) in clinical decision making in acute ischemic stroke (AIS) patients in regards to the prescription of antiseizure medications.

Methods: Patients were grouped as having positive EEG (+) for epileptiform activity or negative EEG (-). These studies were no more than 30 minutes in length.

Anastomotic Leak is Increased With Infection After Colectomy: Machine Learning-Augmented Propensity Score Modified Analysis of 46 735 Patients.

Background: infection (CDI) is now the most common cause of healthcare-associated infections, with increasing prevalence, severity, and mortality of nosocomial and community-acquired CDI which makes up approximately one third of all CDI. There are also increased rates of asymptomatic colonization particularly in high-risk patients. is a known collagenase-producing bacteria which may contribute to anastomotic leak (AL).

Does Distance to Treatment Affect Mortality Rate for Surgical Oncology Patients?

Introduction: Using the National Cancer Database (NCDB), we seek to analyze the relationship of patient distance to hospital of treatment on mortality trends after surgery, since patients often travel large distances to referral centers.

Methods: A retrospective cohort study of the NCDB from 2004 to 2013 was performed, and patients with gastrointestinal, melanoma, and head and neck primary site tumors who underwent surgery were included. We excluded cases with no recorded mortality status or distance from the hospital.

The role of cardio-protective agents in cardio-preservation in breast cancer patients receiving Anthracyclines ± Trastuzumab: a Meta-analysis of clinical studies.

Background: Breast cancer patients often receive cardiotoxic drugs such as anthracyclines (ANT) and Trastuzumab. Numerous trials have tested angiotensin converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARB), and beta-blockers (BB) as monotherapy or in combination to reprogram cardiac function dynamics in these patients, but no clear conclusions have been reached thus far, due to evident heterogeneity in the design of clinical studies.

Methods: This PRISMA-guided systematic review and meta-analysis assessed a pooled effect estimate of the potential benefit/harm of ACEi/ARB/BB in breast cancer patients treated with ANT ± Trastuzumab.