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

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.

Evolving perspectives in reverse cardio-oncology: A review of current status, pathophysiological insights, and future directives

Cardiovascular disease (CVD) and cancer are leading causes of mortality worldwide, traditionally linked through adverse effects of cancer therapies on cardiovascular health. However, reverse cardio-oncology, a burgeoning field, shifts this perspective to examine how cardiovascular diseases influence the onset and progression of cancer. This novel approach has revealed a higher likelihood of cancer development in patients with pre-existing cardiovascular conditions, attributed to shared risk factors such as obesity, a sedentary lifestyle, and smoking. Underlying mechanisms like chronic inflammation and clonal hematopoiesis further illuminate the connections between cardiovascular ailments and cancer. This comprehensive narrative review, spanning a broad spectrum of studies, outlines the syndromic classification of cardio-oncology, the intersection of cardiovascular risk factors and oncogenesis, and the bidirectional dynamics between CVD and cancer. Additionally, the review also discusses the pathophysiological mechanisms underpinning this interconnection, examining the roles of cardiokines, genetic factors, and the effects of cardiovascular therapies and biomarkers in cancer diagnostics. Lastly, it aims to underline future directives, emphasising the need for integrated healthcare strategies, interdisciplinary research, and comprehensive treatment protocols.

Interventional cardiology in cancer patients: A position paper from the Portuguese Cardiovascular Intervention Association and the Portuguese Cardio-Oncology Study Group of the Portuguese Society of Cardiology

The field of Cardio-Oncology has grown significantly, especially during the last decade. While awareness of cardiotoxicity due to cancer disease and/or therapies has greatly increased, much of the attention has focused on myocardial systolic disfunction and heart failure. However, coronary and structural heart disease are also a common issue in cancer patients and encompass the full spectrum of cardiotoxicity. While invasive percutaneous or surgical intervention, either is often needed or considered in cancer patients, limited evidence or guidelines are available for dealing with coronary or structural heart disease. The Society for Cardiovascular Angiography and Interventions consensus document published in 2016 is the most comprehensive document regarding this particular issue, but relevant evidence has emerged since, which render some of its considerations outdated. In addition to that, the recent 2022 ESC Guidelines on Cardio-Oncology only briefly discuss this topic. As a result, the Portuguese Association of Cardiovascular Intervention and the Cardio-Oncology Study Group of the Portuguese Society of Cardiology have partnered to produce a position paper to address the issue of cardiac intervention in cancer patients, focusing on percutaneous techniques. A brief review of available evidence is provided, followed by practical considerations. These are based both on the literature as well as accumulated experience with these types of patients, as the authors are either interventional cardiologists, cardiologists with experience in the field of Cardio-Oncology, or both.

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.

Interventional Cardio-Oncology: Unique Challenges and Considerations in a High-Risk Population

OPINION STATEMENT

Patients with cancer are at risk of developing cardiovascular disease (CVD) including atherosclerotic heart disease (AHD), valvular heart disease (VHD), and atrial fibrillation (AF). Advances in percutaneous catheter-based treatments, including percutaneous coronary intervention (PCI) for AHD, percutaneous valve replacement or repair for VHD, and ablation and left atrial appendage occlusion devices (LAAODs) for AF, have provided patients with CVD significant benefit in the recent decades. However, trials and registries investigating outcomes of these procedures often exclude patients with cancer. As a result, patients with cancer are less likely to undergo these therapies despite their benefits. Despite the inclusion of cancer patients in randomized clinical trial data, studies suggest that cancer patients derive similar benefits of percutaneous therapies for CVD compared with patients without cancer. Therefore, percutaneous interventions for CVD should not be withheld in patients with cancer, as they may still benefit from these procedures.

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.

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.

The Impact of Artificial Intelligence on Health Equity in Oncology: Scoping Review

BACKGROUND

The field of oncology is at the forefront of advances in artificial intelligence (AI) in health care, providing an opportunity to examine the early integration of these technologies in clinical research and patient care. Hope that AI will revolutionize health care delivery and improve clinical outcomes has been accompanied by concerns about the impact of these technologies on health equity.

OBJECTIVE

We aimed to conduct a scoping review of the literature to address the question, "What are the current and potential impacts of AI technologies on health equity in oncology?"

METHODS

Following PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines for scoping reviews, we systematically searched MEDLINE and Embase electronic databases from January 2000 to August 2021 for records engaging with key concepts of AI, health equity, and oncology. We included all English-language articles that engaged with the 3 key concepts. Articles were analyzed qualitatively for themes pertaining to the influence of AI on health equity in oncology.

RESULTS

Of the 14,011 records, 133 (0.95%) identified from our review were included. We identified 3 general themes in the literature: the use of AI to reduce health care disparities (58/133, 43.6%), concerns surrounding AI technologies and bias (16/133, 12.1%), and the use of AI to examine biological and social determinants of health (55/133, 41.4%). A total of 3% (4/133) of articles focused on many of these themes.

CONCLUSIONS

Our scoping review revealed 3 main themes on the impact of AI on health equity in oncology, which relate to AI's ability to help address health disparities, its potential to mitigate or exacerbate bias, and its capability to help elucidate determinants of health. Gaps in the literature included a lack of discussion of ethical challenges with the application of AI technologies in low- and middle-income countries, lack of discussion of problems of bias in AI algorithms, and a lack of justification for the use of AI technologies over traditional statistical methods to address specific research questions in oncology. Our review highlights a need to address these gaps to ensure a more equitable integration of AI in cancer research and clinical practice. The limitations of our study include its exploratory nature, its focus on oncology as opposed to all health care sectors, and its analysis of solely English-language articles.

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.

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. Regression models of mortality and PCI weighted by the complex survey design were fully adjusted for age, race, income, cancer metastases, NIS-calculated mortality risk by Diagnosis Related Group (DRG), acute coronary syndrome, and likelihood of undergoing PCI RESULTS: Of the 30,195,722 hospitalized adult patients, 15.43% had cancer, and 0.79% of the whole sample presented with cardiac arrest (of whom 20.57% underwent PCI). In fully adjusted regression analysis among patients with cardiac arrest, PCI significantly reduced mortality (OR 0.15, 95%CI 0.13-0.19; p<0.001) among patients with cancer greater than those without it (OR 0.21, 95%CI 0.20-0.23; p<0.001).

CONCLUSIONS

This nationally representative study suggests that post-cardiac arrest PCI is underutilized among patients with cancer despite its significant mortality reduction for such patients (independent of clinical acuity).

EHA Guidelines on Management of Antithrombotic Treatments in Thrombocytopenic Patients With Cancer

In cancer patients, thrombocytopenia can result from bone marrow infiltration or from anticancer medications and represents an important limitation for the use of antithrombotic treatments, including anticoagulant, antiplatelet, and fibrinolytic agents. These drugs are often required for prevention or treatment of cancer-associated thrombosis or for cardioembolic prevention in atrial fibrillation in an increasingly older cancer population. Data indicate that cancer remains an independent risk factor for thrombosis even in case of thrombocytopenia, since mild-to-moderate thrombocytopenia does not protect against arterial or venous thrombosis. In addition, cancer patients are at increased risk of antithrombotic drug-associated bleeding, further complicated by thrombocytopenia and acquired hemostatic defects. Furthermore, some anticancer treatments are associated with increased thrombotic risk and may generate interactions affecting the effectiveness or safety of antithrombotic drugs. In this complex scenario, the European Hematology Association in collaboration with the European Society of Cardiology has produced this scientific document to provide a clinical practice guideline to help clinicians in the management of patients with cancer and thrombocytopenia. The Guidelines focus on adult patients with active cancer and a clear indication for anticoagulation, single or dual antiplatelet therapy, their combination, or reperfusion therapy, who have concurrent thrombocytopenia because of either malignancy or anticancer medications. The level of evidence and the strength of the recommendations were discussed according to a Delphi procedure and graded according to the Oxford Centre for Evidence-Based Medicine.

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.

Management of Acute Coronary Syndrome in Cancer Patients: It's High Time We Dealt with It

Cancer patients have an increased risk of cardiovascular disease and, notably, a significant prevalence of acute coronary syndrome (ACS). It has been shown that an elevated presence of cardiovascular risk factors in this setting leads to an interaction between these two conditions, influencing their therapeutic strategies and contributing to higher mortality. Nonetheless, cancer patients have generally not been evaluated in ACS trials, so that the treatment in these cases is still not fully known. We reviewed the current literature and discussed the best management for these very high-risk patients. The treatment strategy must be tailored based on the cancer type and stage, balancing thrombotic and bleeding risks. When the prognosis is longer than six months, especially if a clinical instability coexists, patients with ACS and cancer should be referred for percutaneous coronary intervention (PCI) as soon as possible. Moreover, an invasive strategy should be preferred in STEMI patients as well as in NSTEMI patients who are considered as high risk. On the contrary, in clinically stable NSTEMI patients, a conservative non-invasive strategy could be adopted, especially in cases of a poor life expectancy and/or of high risk of bleeding. Drug-Eluting-Stents (DES) should be the first choice if an invasive strategy is adopted. Conservative therapy could instead be considered in cancer patients with more stable CAD at an increased risk of major bleeding complications. However, the duration of dual antiplatelet therapy (DAPT) with aspirin and clopidogrel is recommended, but it should be as short as possible, whereas triple antithrombotic therapy is non-advised because it significantly increases the risk of bleeding. ACS management among cancer patients should be based on an accurate evaluation of the risk of thrombosis and bleeding. Future studies focused on choosing optimal strategies in tumor patients with ACS should be performed to treat this subset of patients better.

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 &lt; 0.001) and total cost (Beta $31,035.46, 95%CI 26758.86–35312.06; p &lt; 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 &lt; 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.

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.

Disparities in Peripheral Artery Disease Hospitalizations Identified Among Understudied Race-Ethnicity Groups

Background: To assess racial/ethnic differences in disease severity, hospital outcomes, length of stay and healthcare costs among hospitalized patients with peripheral artery disease (PAD).

Methods: This study used data from the National Inpatient Sample (NIS) to explore the racial/ethnic disparities in PAD-related hospitalizations including presence of PAD with chronic limb threatened ischemia (CLI), amputation, in-hospital mortality, length of hospital stays and estimated medical costs. Race-ethnicity groups included non-Hispanic White, Black, Hispanic, Asian or Pacific Islander, Native American, and others (multiple races). Regression analyses adjusted for age, gender, Charlson Comorbidity Index, primary payer, patient location, bed size of the admission hospital, geographic region of the hospital, and rural/urban location of the hospital.

Results: A total of 341,480 PAD hospitalizations were identified. Compared with non-Hispanic Whites, Native Americans had the highest odds of PAD with CLI (OR = 1.77, 95% CI: 1.61, 1.95); Black (OR = 1.71, 95% CI: 1.66, 1.76) and Hispanic (OR = 1.36, 95% CI: 1.31,1.41) patients had higher odds of amputation; Asian or Pacific Islanders had a higher mortality (OR = 1.20, 95% CI: 1.01,1.43), whereas Black (OR = 0.81, 95% CI: 0.76, 0.87) patients has a lower mortality; Asian or Pacific Islanders incurred higher overall inpatient costs (Margin = 30093.01, 95% CI: 28827.55, 31358.48) and most prolonged length of stay (IRR = 0.14, 95% CI: 0.09, 0.18).

Conclusions: Our study identified elevated odds of amputation among Hispanic patients hospitalized with PAD as well as higher hospital mortality and medical expenses among Asian or Pacific Islander PAD inpatients. These two demographic groups were previously thought to have a lower risk for PAD and represent important populations for further investigation.