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). Regression and machine learning analyses in addition to model optimization were conducted using ML-PSr (Machine Learning-augmented Propensity Score adjusted multivariable regression) and BAyesian Machine learning-augmented Propensity Score (BAM-PS) multivariable regression. RESULTS: Of all adult hospitalizations, there were 5790 (0.004%) TMVRs and 1705 (0.001%) TEERs. Of the total TMVRs, 160 (2.76%) were done in active cancer. Of the total TEERs, 30 (1.76%) were done in active cancer. After the comparable rates of TEER/TMVR in active cancer in 2016, the prevalence of TEER/TMVR was significantly less in active cancer from 2017 to 2020 (2.61% versus 7.28% p < 0.001). From 2017 to 2020, active cancer significantly decreased the odds of receiving TEER or TMVR (OR 0.28, 95%CI 0.13-0.68, p = 0.008). In patients with active cancer who underwent TMVR/TEER, there were no significant differences in socio-economic disparities, mortality or total hospitalization costs. CONCLUSION: The presence of malignancy does not contribute to increased mortality, length of stay or procedural costs in TMVR or TEER. Whereas the prevalence of TMVR has increased in patients with active cancer, the utilization of TEER in the context of active cancer is declining despite a growing patient population.

Percutaneous Coronary Intervention Mortality, Cost, Complications, and Disparities after Radiation Therapy: Artificial Intelligence-Augmented, Cost Effectiveness, and Computational Ethical Analysis.

The optimal cardio-oncology management of radiation therapy and its complications are unknown despite the high patient and societal costs. This study is the first known nationally representative, multi-year, artificial intelligence and propensity score-augmented causal clinical inference and computational ethical and policy analysis of percutaneous coronary intervention (PCI) mortality, cost, and disparities including by primary malignancy following radiation therapy. Bayesian Machine learning-augmented Propensity Score translational (BAM-PS) statistics were conducted in the 2016-2020 National Inpatient Sample. Of the 148,755,036 adult hospitalizations, 2,229,285 (1.50%) had a history of radiation therapy, of whom, 67,450 (3.00%) had an inpatient AMI, and of whom, 18,400 (28.69%) underwent PCI. Post-AMI mortality, costs, and complications were comparable with and without radiation across cancers in general and across the 30 primary malignancies tested, except for breast cancer, in which PCI significantly increased mortality (OR 3.70, 95%CI 1.10-12.43, p = 0.035). In addition to significant sex, race, and insurance disparities, significant regional disparities were associated with nearly 50 extra inpatient deaths and over USD 500 million lost. This large clinical, cost, and pluralistic ethical analysis suggests PCI when clinically indicated should be provided to patients regardless of sex, race, insurance, or region to generate significant improvements in population health, cost savings, and social equity.

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. Recent stent technologies may safely allow for shorter duration (< 6 months) of dual antiplatelet therapy post-percutaneous coronary interventions. Intracoronary imaging may be useful in the decision making process in terms of stent positioning and healing. Summary: Large registry studies have partially filled a gap left by the lack of randomized controlled trials in the treatment of CAD in cancer patients. Cardio-oncology is gaining traction as a major sub-specialty in the cardiology field given the release of the first European Society of Cardiology - Cardio-oncology guidelines in 2022.

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. The Cardiac Arrest Cardio-Oncology Score (CACOS) was then created for the above population and validated. The results informed the computational ethical analysis to determine ethical and related policy recommendations. Results: Of the 101,521,656 hospitalizations, 6,656,883 (6.56%) suffered cardiac arrest of whom 61,300 (0.92%) had active cancer. Patients with versus without active cancer were significantly less likely to receive an inpatient LHC (7.42% versus 20.79%, p < 0.001). In ML-PS regression in active cancer, post-arrest LHC significantly reduced mortality (OR 0.18, 95%CI 0.14−0.24, p < 0.001) which PS matching confirmed by up to 42.87% (95%CI 35.56−50.18, p < 0.001). The CACOS model included the predictors of no inpatient LHC, PEA initial rhythm, metastatic malignancy, and high-risk malignancy (leukemia, pancreas, liver, biliary, and lung). Cost-benefit analysis indicated 292 racial minorities and $2.16 billion could be saved annually by reducing racial disparities in LHC. Ethical analysis indicated the convergent consensus across diverse belief systems that such disparities should be eliminated to optimize just and equitable outcomes. Conclusions: This AI-guided empirical and ethical analysis provides a novel demonstration of LHC mortality reductions in cardio-oncology cardiac arrest and related disparities, along with an innovative predictive model that can be integrated within the digital ecosystem of modern healthcare systems to improve equitable clinical and public health outcomes.

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). Regression results were adjusted for age, race, income, geographic region, metastases, mortality risk, and the likelihood of undergoing FFR versus non-FFR PCI. All analyses were adjusted for the complex survey design to produce nationally representative estimates. Results: Of the 30,195,722 hospitalized patients meeting criteria, 3.37% of the PCIs performed included FFR. In propensity score adjusted multivariable regression, FFR versus non-FFR PCI significantly reduced inpatient mortality (OR 0.47, 95%CI 0.35−0.63; p < 0.001) and length of stay (LOS) (in days; beta −0.23, 95%CI −0.37−−0.09; p = 0.001) while increasing cost (in USD; beta $5708.63, 95%CI, 3042.70−8374.57; p < 0.001), without significantly increasing complications overall. FFR versus non-FFR PCI did not specifically change cancer patients' inpatient mortality, LOS, or cost. However, FFR versus non-FFR PCI significantly increased inpatient mortality for Hodgkin's lymphoma (OR 52.48, 95%CI 7.16−384.53; p < 0.001) and rectal cancer (OR 24.38, 95%CI 2.24−265.73; p = 0.009). Conclusions: FFR-guided PCI may be safely utilized in patients with cancer as it does not significantly increase inpatient mortality, complications, and LOS. These findings support the need for an increased utilization of FFR-guided PCI and further studies to evaluate its long-term impact.

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. Materials and Methods: FFR was used to assess cancer patients that underwent coronary angiography for stable CAD between September 2008 and May 2016, and were found to have ≥50% stenosis by QCA. Patients with lesions with an FFR > 0.75 received medical therapy alone, while those with FFR ≤ 0.75 were revascularized. Procedure-related complications, all-cause mortality, nonfatal myocardial infarction, or urgent revascularizations were analyzed. Results: Fifty-seven patients with stable CAD underwent FFR on 57 lesions. Out of 31 patients with ≥70% stenosis as measured by QCA, 14 (45.1%) had an FFR ≥ 0.75 and lesions were reclassified as moderate and did not receive PCI nor DAPT. Out of 26 patients with <70% stenosis as measured by QCA, 6 (23%) had an FFR < 0.75 and were reclassified as severe and were treated with PCI and associated DAPT. No periprocedural complications, urgent revascularization, acute coronary syndromes, or cardiovascular deaths were noted. There was a 22.8% mortality at 1 year, all cancer related. Patients who received a stent by FFR assessment showed a significant association with decreased risk of all-cause death (HR: 0.37, 95% CI 0.15−0.90, p = 0.03). Conclusions: Further studies are needed to define the optimal therapeutic approach for cancer patients with CAD. Using an FFR cut-off point of 0.75 to guide PCI translates into fewer interventions and can facilitate cancer care. There was an overall reduction in mortality in patients that received a stent, suggesting increased resilience to cancer therapy and progression.

Multisite Medical Student-Led Community Culinary Medicine Classes Improve Patients' Diets: Machine Learning-Augmented Propensity Score-Adjusted Fixed Effects Cohort Analysis of 1381 Subjects.

Background. Healthy diet represents one of the largest single modifiable risk factors proven to decrease rates of obesity and associated chronic disease, but practical approaches to improving dietary habits through nutritional intervention are limited. Objective. To evaluate the effectiveness of a medical student-led, 6-week culinary course on participants' dietary knowledge and behaviors, particularly focusing on the tenets of the Mediterranean diet (MedDiet). Design. This study is a prospective multisite cohort study evaluating the effects of a 6-week, hands-on community culinary education course offered at 3 sites. Participants' knowledge of cooking skills, eating habits, and adherence to the MedDiet were evaluated using a survey prior to beginning and 6 weeks after the completion of the course. Analysis was conducted using multivariable regression to assess subjects' diets, associated behaviors, and nutrition beliefs according to the number of classes to which they were exposed (0 to >6). Statistical results were then compared with the machine learning results to check statistical validity after selection of the top-performing algorithm from 43 supervised algorithms using 10-fold cross-validation with performance assessed according to accuracy, root relative square error, and root mean square error. Results. Among the 1381 participants, cooking classes significantly improved patients' overall 9-point MedDiet adherence (ß = 0.62, 95% CI 0.23-1.00, P = .002). Participants were more likely to meet MedDiet point requirements for fruit intake (odds ratio [OR] 2.77, 95% CI 1.46-5.23, P = .002), vegetable intake (OR 4.61, 95% CI 1.85-11.53, P = .001), legume intake (OR 2.48, 95% CI 1.45-4.26, P = .001), and olive oil use (OR 2.87, 95% CI 1.44-5.74, P = .003), and were less likely to believe that cooking takes excessive time (OR 0.31, 95% CI 0.16-0.59, P < .001). Conclusion. Hands-on culinary education courses were associated with increased MedDiet adherence and improved knowledge of healthful eating. Such interventions thus represent a cost-effective option for addressing rates of obesity and obesity-related chronic illness.

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. (B) Teaching kitchens. PARTICIPANTS: (A) Medical trainees. (B) Trainees, providers and patients. RESULTS: (A) Of the 212 citations identified (n 1698 trainees), eleven studies met inclusion criteria. The overall effect size was 9·80 (95 % CI (7·15, 12·45) and 95 % CI (6·87, 13·85); P < 0·001), comparable with the machine learning (ML)-augmented results. The number needed to treat for the top performing high-quality study was 12. (B) The hands-on cooking and nutrition education curriculum from the top performing study were applied for medical trainees and providers who subsequently taught patients in the same curriculum (n 5847). The intervention compared with standard medical care and education alone significantly increased the odds of superior diets (high/medium v. low Mediterranean diet adherence) for residents/fellows most (OR 10·79, 95 % CI (4·94, 23·58); P < 0·001) followed by students (OR 9·62, 95 % CI (5·92, 15·63); P < 0·001), providers (OR 5·19, 95 % CI (3·23, 8·32), P < 0·001) and patients (OR 2·48, 95 % CI (1·38, 4·45); P = 0·002), results consistent with those from ML. CONCLUSIONS: The current study suggests that medical trainees and providers can improve patients' diets with nutrition counseling in a manner that is clinically and cost effective and may simultaneously advance societal equity.

Are the current colonoscopy recommendations for interval surveillance in patients with polyps enough? Machine learning-augmented propensity score cohort analysis of 1840 patients.

BACKGROUND: Colonoscopy remains the gold standard for screening and surveillance of colorectal neoplasms, and is associated with a lower risk of colorectal cancer (CRC)-related mortality. The current interval surveillance recommendations in patients with previous adenomas lack sufficient evidence. The prevalence of subsequent adenomas, and especially high-risk adenomas, during surveillance is not well known. METHODS: The primary outcome of this study was to determine the prevalence of polyps upon surveillance colonoscopy in patients who have a history of adenomas on initial average-risk-screening colonoscopy, but then have a normal initial surveillance (second) colonoscopy between 2003 and 2017. This is the first known retrospective cohort study of adenoma detection rate (ADR) with sub-group analysis of patients with serial surveillance colonoscopies by abnormal and high-risk surveillance findings separately by prior abnormal colonoscopies and correct surveillance strategies based on the recent March 2020 updated guidelines. After ADR calculation, machine learning-augmented propensity score adjusted multivariable regression with augmented inverse-probability weighting propensity (AIPW) score analysis was used to assess the relationship between guideline adherence, as well as abnormal and high-risk surveillance findings. RESULTS: A total of 1840 patients with pathologically confirmed adenomas or cancer on an initial average-risk-screening (first) colonoscopy met study criteria. 837 (45.5%) had confirmed adenomas on second colonoscopy, and 1003 (54.5%) had normal findings. Of 837 patients with polyps on both first and second colonoscopy, 423 (50.5%) had adenomas on third colonoscopy. Of the 1003 patients without polyps on second colonoscopy, 406 (40.5%) had confirmed adenomas on third colonoscopy. Guideline adherence was low at 9.18%, though was associated in propensity score adjusted multivariable regression with increased odds of an abnormal third (but not high-risk) colonoscopy, with comparable AIPW results. CONCLUSION: This 14-year study demonstrates the ADR to be > 40% on the third colonoscopy for patients with adenomas on initial screening colonoscopy, who then have a normal second colonoscopy. Through advanced machine learning and propensity score analysis, we showed that correct adherence is associated with higher odds of abnormal, but not high-risk abnormal 3rd colonoscopy, with evidence that high-risk surveillance findings are reduced by providers shortening the time between surveillance colonoscopies in contrast to the guidelines for those for whom there is presumed greater clinical suspicion of eventual cancer. Larger prospective trials are needed to guide optimal surveillance for these patients.

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

BACKGROUND: Clostridium difficile 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. C difficile is a known collagenase-producing bacteria which may contribute to anastomotic leak (AL). METHODS: Machine learning-augmented multivariable regression and propensity score (PS)-modified analysis was performed in this nationally representative case-control study of CDI and anastomotic leak, mortality, and length of stay for colectomy patients using the ACS-NSQIP database. RESULTS: Among 46 735 colectomy patients meeting study criteria, mean age was 61.7 years (SD 14.38), 52.2% were woman, 72.5% were Caucasian, 1.5% developed CDI, 3.1% developed anastomotic leak, and 1.6% died. In machine learning (backward propagation neural network)-augmented multivariable regression, CDI significantly increases anastomotic leak (OR 2.39, 95% CI 1.70-3.36; P < .001), which is similar to the neural network results. Having CDI increased the independent likelihood of anastomotic leak by 3.8% to 6.8% overall, and in dose-dependent fashion with increasing ASA class to 4.3%, 5.7%, 7.6%, and 10.0%, respectively, for ASA class I to IV. In doubly robust augmented inverse probability weighted PS analysis, CDI significantly increases the likelihood of AL by 4.58% (95% CI 2.10-7.06; P < .001). CONCLUSIONS: This is the first known nationally representative study on CDI and AL, mortality, and length of stay among colectomy patients. Using advanced machine learning and PS analysis, we provide evidence that suggests CDI increases AL in a dose-dependent manner with increasing ASA Class.

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.S. National Inpatient Sample (NIS). Regression models were weighted by the complex survey design and adjusted for known confounders and the likelihood of undergoing valvular procedures. Results: Among 101,521,656 hospitalizations, 55,910 (0.06%) had MCT. Patients with MCT vs. those without had significantly higher inpatient mortality (2.93 vs. 2.04%, p = 0.002), longer mean length of stay (12.20 vs. 4.62, p < 0.001), and increased mean total cost of stay ($70,252.18 vs. 51,092.01, p < 0.001). There was a step-wise increased rate of TVR and PVR with each subsequent year, with significantly more TV (0.16% vs. 0.01, p < 0.001) and PV (0.03 vs. 0.00, p = 0.040) diagnosed with vs. without MCT for 2016, with comparable trends in 2017 and 2018. There were no significant procedural disparities among patients with MCT for sex, race, income, urban density, or geographic region, except in 2017, when the highest prevalence of PV procedures were performed in the Western North at 50.00% (p = 0.034). In machine learning and propensity score augmented multivariable regression, MCT did not significantly increase the likelihood of TVR or PVR. In sub-group analysis restricted to MCT, neither TVR nor PVR significantly increased mortality, though it did increase cost (respectively, $141,082.30, p = 0.015; $355,356.40, p = 0.012). Conclusion: This analysis reflects a favorable trend in recognizing the need for TVR and PVR in patients with MCT, with associated increased cost but not mortality. Our study also suggests that pulmonic valve pathology is increasingly recognized in MCT as reflected by the upward trend in PVRs. Further research and updated societal guidelines may need to focus on the "forgotten pulmonic valve" to improve outcomes and disparities in this understudied patient population.

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. Then AI-based machine learning (backward propagation neural network) augmented multivariable regression and GIS heat mapping were performed. RESULTS: Of 3,952 OHCA patients across 38 hospitals, African Americans were the most likely to suffer OHCA despite representing a significantly lower percentage of the population (42.6 versus 22.8%; p < 0.001). Compared to Caucasians, they were significantly more likely to have poor neurological disposition (OR 2.21, 95%CI 1.25-3.92; p=0.006) and be discharged to a facility instead of home (OR 1.39, 95%CI 1.05-1.85; p=0.023). Compared to the safety net hospital system primarily serving poorer African Americans, the university hospital serving primarily higher income commercially and Medicare insured patients had the lowest odds of death (OR 0.45, p < 0.001). Each additional $10,000 above median household income was associated with a decrease in the total number of cardiac arrests per zip code by 2.86 (95%CI -4.26- -1.46; p < 0.001); zip codes with a median income above $54,600 versus the federal poverty level had 14.62 fewer arrests (p < 0.001). GIS maps showed convergence of the greater density of poor neurologic outcome cases and greater density of poorer African American residences. CONCLUSION: This large, longitudinal AI-guided analysis statistically and geographically identifies racial and socioeconomic disparities in OHCA outcomes in a way that may allow targeted medical and public health coordinated efforts to improve clinical, cost, and social equity outcomes.

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. METHODS AND RESULTS: We analysed SC by primary malignancy type with propensity score adjusted multivariable regression and machine learning analysis using the 2016 United States National Inpatient Sample. Of 30 195 722 adult hospitalized patients, 4 719 591 had active cancer, of whom 568 239 had SC. The mean age of patients with cancer and SC was 69.1, of which 74.7% were women. Among patients with cancer, those with SC were more likely to be female and have white race, Medicare insurance, hypertension, heart failure with reduced ejection fraction, obesity, cerebrovascular disease, anaemia, and chronic obstructive pulmonary disease (P < 0.003 for all). In machine learning-augmented, propensity score multivariable regression adjusted for age, race, and income, only lung cancer [OR 1.25; 95% CI: 1.08-1.46; P = 0.003] and breast cancer [OR 1.81; 95% CI: 1.62-2.02; P < 0.001] were associated with a significantly increased likelihood of SC. Neither SC alone nor having both SC and cancer was significantly associated with in-hospital mortality. The presence of concomitant SC and breast cancer was significantly associated with reduced mortality (OR 0.48; 95% CI: 0.25-0.94; P = 0.032). CONCLUSIONS: This analysis demonstrates that primary malignancy type influences the likelihood of developing SC. Further studies will be necessary to delineate characteristics in patients with lung cancer and breast cancer which contribute to development of SC. Additional investigation should confirm lower mortality in patients with SC and breast cancer and determine possible explanations and protective factors.

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

Objectives: This study sought to systematically analyze the available clinical evidence on TAVR therapy in cancer patients with symptomatic severe AS. Background: Aortic stenosis is the most common valvular heart disease in the world. TAVR has expanded the treatment options for this lethal disease process. The safety and efficacy of TAVR in cancer patients has not yet been reliably established. We thus conducted the largest known multi-center meta-analysis on TAVR and cancer status. Methods: We performed a literature search using PubMed, EMBASE, and Cochrane Central Register of Controlled Trials from January 2015 to 2020. Studies that compared the use of TAVR in patients with severe symptomatic aortic stenosis and cancer against patients without cancer were included. Meta-regression was also conducted to determine if common clinical factors modified the possible association between cancer status and TAVR mortality. Results: Five studies with 11,129 patients in the cancer group and 41,706 patients in the control group met inclusion criteria. The short-term mortality in the cancer group was 2.4% compared with 3.3% in the control group (odds ratio: 0.72, 95% confidence interval: 0.63-0.82; p < 0.0001). The frequency of stroke was 2.4% compared with 2.7% (odds ratio of 0.87, 95% confidence interval: 0.76-0.99; p < 0.04). The frequency of AKI was 14.2% in cancer patients vs. 16.4% (odds ratio of 0.81, 95% confidence interval: 0.76-0.85; p < 0.04). The rates of bleeding and need for new pacemaker implantation were not significantly different. Meta-regression demonstrated there was no significant association modifying. Conclusions: On the basis of the results of this meta-analysis TAVR may be a safe and effective therapeutic option for patients with cancer and symptomatic severe aortic stenosis. Larger, longer, and randomized trials are required to adequately test this above hypothesis.

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. Additionally, we sought to quantitate and compare both clinical and cost outcomes for patients with and without cancer. METHODS: This population-based case-control study uses the most recent year available National Inpatient Sample (NIS (2016) from the United States Department of Health and Human Services' Agency for Healthcare Research and Quality (AHRQ). Machine learning augmented propensity score adjusted multivariable regression was conducted based on the likelihood of undergoing TAVR versus medical management (MM) and TAVR versus SAVR with model optimization supported by backward propagation neural network machine learning. RESULTS: Of the 30,195,722 total hospital admissions, 39,254 (0.13%) TAVRs were performed, with significantly fewer performed in patients with versus without cancer even in those of comparable age and mortality risk (23.82% versus 76.18%, p < 0.001) despite having similar hospital and procedural mortality. Multivariable regression in patients with cancer demonstrated that mortality was similar for TAVR, MM, and SAVR, though LOS and cost was significantly lower for TAVR versus MM and comparable for TAVR versus SAVR. Patients with prostate cancer constituted the largest primary cancer among TAVR patients including those with metastatic disease. There were no significant race or geographic disparities for TAVR mortality. DISCUSSION: Comparison of aortic valve intervention in patients with and without cancer suggests that interventions are underutilized in the cancer population. This study suggests that patients with cancer including those with metastasis have similar inpatient outcomes to patients without cancer. Further, patients who have symptomatic AS and those with higher risk aortic valve disease should be offered the benefit of intervention. Modern techniques have reduced intervention-related adverse events, provided improved quality of life, and appear to be cost effective; these advantages should not necessarily be denied to patients with co-existing cancer.

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

Background: 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. Methods: This multicenter case-control study used machine learning-augmented propensity score-adjusted multivariable regression to assess the above outcomes and disparities using the 2016 nationally representative National Inpatient Sample. Results: Of the 30,195,722 hospitalized patients, 15.43% had a malignancy, 3.84% underwent an inpatient PCI (of whom 11.07% had cancer and 0.07% had metastases), and 2.19% died inpatient. In fully adjusted analyses, PCI vs. medical management significantly reduced mortality for patients overall (among all adult inpatients regardless of cancer status) and specifically for cancer patients (OR 0.82, 95% CI 0.75-0.89; p < 0.001), mainly driven by active vs. prior malignancy, head and neck and hematological malignancies. PCI also significantly reduced cancer patients' total hospitalization costs (beta USD$ -8,668.94, 95% CI -9,553.59 to -7,784.28; p < 0.001) independent of length of stay. There were no significant income or disparities among PCI subjects. Conclusions: Our study suggests among all eligible adult inpatients, PCI does not increase mortality or cost for cancer patients, while there may be particular benefit by cancer type. The presence or history of cancer should not preclude these patients from indicated cardiovascular care.

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). Analyses were also adjusted for the complex survey design to produce nationally representative estimates. Centers for Disease Control and Prevention (CDC)-based cost effectiveness ratio (CER) analysis was performed. RESULTS: Of the 30,195,722 hospitalized patients meeting criteria, 1.27% had gynecological cancer of whom 0.02% underwent PCI including 0.04% with metastases. In propensity score adjusted regression among all patients, the interaction of PCI and gynecological cancer (vs. not having PCI) significantly reduced mortality (OR 0.53, 95%CI 0.36-0.77; p = 0.001) while increasing LOS (Beta 1.16 days, 95%CI 0.57-1.75; p < 0.001) and total cost (Beta $31,035.46, 95%CI 26758.86-35312.06; p < 0.001). Among gynecological cancer patients, mortality was significantly reduced by PCI (OR 0.58, 95%CI 0.39-0.85; p = 0.006) and being in East North Central, West North Central, South Atlantic, and Mountain regions (all p < 0.03) compared to New England. PCI reduced mortality but not significantly for metastatic patients (OR 0.74, 95%CI 0.32-1.71; p = 0.481). Eighteen extra gynecological cancer patients' lives were saved with PCI for a net national cost of $3.18 billion and a CER of $176.50 million per averted death. CONCLUSION: This large propensity score analysis suggests that PCI may cost inefficiently reduce mortality for gynecological cancer patients, amid income and geographic disparities in outcomes.

Effect of culinary education curriculum on Mediterranean diet adherence and food cost savings in families: a randomised controlled trial.

OBJECTIVE: Diet-related diseases are the leading cause of morbidity and mortality in the USA. While the critical aspects of a healthy diet are well known, the relationship between community-based, teaching kitchen education and dietary behaviours is unclear. We examined the effect of a novel culinary medicine education programme on Mediterranean diet adherence and food cost savings. DESIGN: Families were randomised to a hands-on, teaching kitchen culinary education class (n = 18) or non-kitchen-based dietary counselling (n = 23) for 6 weeks. The primary outcome was adherence to the validated nine-point Mediterranean diet score, and the secondary outcome was food cost savings per family. SETTING: The Goldring Center for Culinary Medicine, a community teaching kitchen in New Orleans. PARTICIPANTS: Families (n = 41) of at least one child and one parent. RESULTS: Compared with families receiving traditional dietary counselling, those participating in hands-on, kitchen-based nutrition education were nearly three times as likely to follow a Mediterranean dietary pattern (OR 2·93, 95% CI 1·73, 4·95; P  <  0·001), experiencing a 0·43-point increase in Mediterranean diet adherence after 6 weeks (B  =  0·43; P  <  0·001). Kitchen-based nutrition education projects to save families $US 21·70 per week compared with standard dietary counselling by increasing the likelihood of consuming home-prepared v. commercially-prepared meals (OR 1·56, 95% CI 1·08, 2·25; P  =  0·018). CONCLUSIONS: Community-based culinary medicine education improves Mediterranean diet adherence and associates with food cost savings among a diverse sample of families. Hands-on culinary medicine education may be a novel evidence-based tool to teach healthful dietary habits and prevent chronic disease.

Etiological Role of Diet in 30-Day Readmissions for Heart Failure: Implications for Reducing Heart Failure-Associated Costs via Culinary Medicine.

Background. Reducing the under-30-day readmission for heart failure (HF) patients is a modifiable quality-of-care measure, yet the role of diet in HF readmissions and cost-effective HF care remain ill-defined. Methods. Medical chart review was conducted to determine cause(s) for HF treatment failure. Randomized controlled trial-backed machine learning models were employed to assess the relationship of culinary medicine education with HF 30-day readmission rate and cost. Results. Of 1031 HF admissions, 130 occurred within 30 days of discharge (12.61%.) Nearly two-thirds of individuals were male (64.02%), while the mean age and median length of stay were 64.33 ± 14.02 and 2, respectively. Medication noncompliance (34.62%) was the most common etiology for 30-day readmissions, followed by dietary noncompliance (16.92%), comorbidity (16.92%), a combination of dietary and medication noncompliance (10%), HF exacerbation (10%), iatrogenic (10%), and drug abuse (1.54%). Medication noncompliance contributed to the highest gross charge by readmission, costing a total of $1 802 096. Compared with traditional care, culinary medicine education for HF patients would prevent 93 HF readmissions and save $3.9 million in an estimated 4-year period. Conclusion. Though pharmacological treatment remains a focal point of HF management, diet-based approaches may improve tertiary HF prevention and reduce HF-associated health care expenditures.

Outcomes of Patients Undergoing Transcatheter Aortic Valve Implantation With Incidentally Discovered Masses on Computed Tomography.

Routine preprocedural chest and abdomen computed tomography is done prior to transcatheter aortic valve implantation (TAVI), which, in turn, have led to the discovery of radiographic potentially malignant incidental masses (pMIM). It is largely unknown whether pMIM impact the outcomes of patients undergoing TAVI. In this retrospective cohort study from a single center, 1,081 patients underwent TAVI from 2012 to 2016, who had available computed tomographies, survived the index hospitalization, and also had 1 year follow-up data for review. Machine learning (backward propagation neural network)-augmented multivariable regression for mortality by pMIM was conducted. In this cohort of 1,081 patients, the mean age was 79.1 (± 9.0), 48.8% were females, 16.8% had a history of prior malignancy, and 21.1% had pMIM. One-year mortality for the entire cohort was 12.6%. The most common prior malignancies were prostate, breast, and lymphoma and the most common pMIM were present in the lung, kidneys, and thyroid. In a fully adjusted regression analysis, neither prior malignancy nor pMIM increased mortality odds. However, having both was associated with a higher 1-year mortality (odds ratio 4.02, 95% confidence interval 1.50 to 10.73, p = 0.006). In conclusion, presence of pMIM alone was not associated with an increased 1-year mortality among patients undergoing TAVI. However, the presence of pMIM and a history of prior malignancy was associated with a significant increase in 1-year mortality.