Citations

ABSTRACT Background Transvenous lead removal (TLR) is a Class I indication for patients with cardiac implantable electronic device (CIED) infections. However, disparities in the utilization of TLR have not been fully explored, particularly concerning demographic and socioeconomic factors. Objectives This study aims to examine whether disparities exist among patients hospitalized for CIED infections with respect to the utilization of TLR, focusing on sex, race, and income characteristics. Methods We utilized the 2019 National Inpatient Sample (NIS) to assess patients hospitalized with CIED infections and identify those who underwent TLR. Multiple logistic regression was used to examine risk factors for TLR utilization, including age, sex, race/ethnicity, and socioeconomic characteristics. Results A total of 56 709 patients were hospitalized for CIED infection in the United States in 2019, of which 9867 (17.4%) underwent TLR. On an adjusted analysis, females and Black patients were found to have lower odds of undergoing TLR compared to males and White patients (OR: 0.62; 95% CI: 0.59–0.78; p < 0.01; and OR: 0.47; 95% CI: 0.39–0.57; p < 0.01, respectively). Hispanic patients also had reduced odds of TLR (OR: 0.73; 95% CI: 0.58–0.93; p = 0.01). No significant associations were observed between income or insurance status and the likelihood of receiving TLR after adjustment. Conclusions This study identified significant disparities in the utilization of TLR among patients hospitalized for CIED infections. Female, Black, and Hispanic patients were significantly less likely to receive TLR.

Abstract Background/Introduction Access to timely healthcare in disadvantaged areas remains essential to achieving equitable health outcomes, especially in regions facing structural and social vulnerabilities. Purpose To assess wait times for cardiovascular disease consultations in US-Mexico border regions compared to non-border regions among US Veterans. Methods This cross-sectional analysis included all veteran cardiovascular consultations referred through the Veterans Choice Program to community healthcare centers from 2014 to 2020. We obtained the average wait times in days for consultation approval, scheduling, completion, and total wait time from approval to consultation completion. All consultations were classified by county of residence as either within a US-Mexico border region or a non-border region, as per the La Paz Agreement. Multivariable linear regression analyses were performed to evaluate the impact of border status on average wait times. ARIMA modeling was completed to estimate forecasted wait times during the COVID-19 pandemic. Results A total of 485,158 consultations related to outpatient cardiovascular disease were retrieved from the VA Healthcare System. Amongst these, 461,696 of the consultations were placed in non-border regions whereas 23,462 consultations were placed in US-Mexico border regions. The most common consultation requests were made for general cardiology clinic (n=365,227), echocardiography (n=32,017), cardio-pulmonary rehabilitation (n=40,699), and cardiac stress testing (n=16,258). Wait times for cardiovascular disease consultations were not higher in US-Mexico border counties than in non-border regions. For electrophysiology consultations specifically, border counties exhibited significantly shorter total wait times (coeff = -10.81, p=0.008). Additionally, while the COVID-19 pandemic led to increased total wait times in non-border areas (Figure 1), total wait times in border regions remained stable during this period (Figure 2). Conclusions Our findings suggest that US-Mexico border region status does not result in longer wait times for cardiovascular disease consultations, with the exception of shorter wait times for electrophysiology services. This study provides important insights into the unique dynamics of healthcare access in structurally disadvantaged regions, highlighting that wait times are not a significant barrier to cardiovascular care in border areas, and emphasizes the need to consider regional differences in healthcare delivery policies.

Background: Aortic stenosis (AS) imposes a significant mortality burden. Understanding demographic influences on the location of AS-related death is crucial for advancing equitable end-of-life care. Therefore, we investigated how demographic factors influence the location of death among AS patients in the United States. Methods: We completed a cross-sectional study utilizing US mortality data from the CDC’s WONDER database for 2019. All files related to decedents with AS identified as the primary cause of death were obtained, including demographic information and death locations (i.e., inpatient facilities, outpatient/ER facilities, home, or hospice/nursing facilities). Associations between demographic factors (age, sex, race/ethnicity, marital status, and education) and place of death were assessed using multivariable logistic regression models, yielding odds ratios (ORs). Results: In 2019, most AS-related deaths occurred in inpatient facilities (38.3%, n = 5062), home (29.2%, n = 3859), or hospice/nursing facilities (28.6%, n = 3775). Higher odds of inpatient death were observed among Black (OR 1.67, p < 0.001) and Hispanic individuals (OR 1.91, p < 0.001) compared to White decedents. Those aged >85 years were more likely to die at home (OR 1.76, p < 0.001) or in hospice/nursing facilities (OR 7.80, p < 0.001). Males had increased odds of inpatient death (OR 1.09, p = 0.044) but decreased odds of hospice/nursing facility death (OR 0.87, p = 0.003). Higher education levels were associated with increased odds of home death (OR 1.33, p = 0.023) and decreased odds of hospice/nursing facility death (OR 0.71, p = 0.015). Conclusions: Demographic factors significantly influence the location of death among AS patients, emphasizing the need for culturally and socioeconomically tailored interventions to promote equitable end-of-life care.

ABSTRACT Background Cardiac implantable electronic device (CIED) infections are a serious complication associated with significant morbidity, mortality, and healthcare costs. Despite guideline recommendations for complete device removal, disparities in healthcare access and resource availability between urban and rural settings may influence patient outcomes. This study aims to evaluate rural–urban disparities in the management and outcomes of patients hospitalized with CIED infections. Methods A retrospective cohort analysis was conducted using the National Readmissions Database (NRD) from 2016 to 2021. Patients aged ≥ 18 years hospitalized with CIED infections were identified using ICD‐10 codes. Hospital location was categorized as urban or rural based on the Urban Influence Codes. Baseline characteristics, complications, and outcomes were compared using chi‐square and t ‐tests, and a multivariable logistic regression model was employed to assess the independent association of hospital settings with transvenous lead removal (TLR) utilization. Results A total of 288,402 patients were hospitalized for CIED infections, with 94.9% treated in urban hospitals and 5.1% in rural hospitals. Urban hospital patients had a higher prevalence of key comorbidities, including heart failure, valvular heart disease, atrial fibrillation and peripheral vascular disorders. In‐hospital mortality was significantly higher in urban hospitals (6.2% vs. 4.8%, p < 0.01) likely due to higher burden of comorbidities and higher rates of acute complications such as stroke (3.1% vs. 1.8%, p < 0.01) and systemic embolism (1.4% vs. 0.7%, p < 0.01). TLR was more frequently performed in urban hospitals (20.1% vs. 9.6%, p < 0.01), with rural hospitals exhibiting 59% lower odds of receiving TLR (OR: 0.41, 95% CI: 0.36–0.47, p < 0.01). TLR was associated with reduced in‐hospital mortality, 30‐day mortality, and 30‐day readmission rates across both hospital settings. Conclusion Our study highlights significant rural–urban disparities in CIED infection management. Despite rural hospitals admitting patients with a lower comorbidity burden, TLR utilization was significantly lower, potentially due to limited access to specialized expertise and procedural resources. Given TLR's association with improved survival and reduced readmissions, regardless of the hospital setting, targeted interventions are needed to enhance access to specialized care in rural settings. Further research is warranted to explore strategies for bridging these disparities and optimizing CIED infection outcomes nationwide.

ABSTRACTBackgroundThe factors contributing to sustained ventricular arrhythmias (VAs) >30 days after left ventricular assist device (LVAD) implantation are not well‐established.ObjectivesThis study aimed to predict the factors associated with late sustained VAs after LVAD implantation and develop a predictive score to identify patients with an increased risk of late sustained VAs after the procedure.MethodsWe performed a retrospective cohort study on a training cohort of 623 patients and a validation cohort of 157 patients who underwent LVAD implantation at the Mayo Clinic (Rochester, Phoenix, and Jacksonville) from January 1, 2000, to December 30, 2020. Late sustained VAs were defined as ventricular tachycardia (VT) and ventricular fibrillation (VF) occurring >30 days after the LVAD procedure. Detailed chart reviews of the electronic health records within the Mayo Clinic and outside medical records were performed.ResultsA total of 780 patients were included in our study. Late sustained VAs occurred in 30% (n = 232) of the patients. The significant factors associated with late sustained VAs after LVAD were the history of VAs prior to LVAD (34.1% vs. 23.0%, p < 0.01), implantable cardiac defibrillator (ICD) (87.9% vs. 77.6%, p < 0.01) or cardiac resynchronization therapy (CRT) in situ (43.5% vs. 33.6%, p = 0.008), VT ablation prior to LVAD (5.2% vs. 1.8%, p = 0.010), use of amiodarone (49.1% vs. 38.7%, p = 0.007), use of mexiletine (15.5% vs. 5.7%, p < 0.01), and higher left ventricular end‐diastolic diameter (LVEDD) on echocardiography prior to LVAD implantation (71.4 vs. 68.7 mm, p = 0.002). During follow‐up, the patients who developed late sustained VAs after LVAD had lower survival than those who did not (HR = 1.96, 95% CI:156–2.4, p < 0.001). The average time from LVAD to orthotopic heart transplant was longer among late sustained VAs patients (23 vs. 14 months, p < 0.01). The “VIN” risk score was created to identify four risk groups: low (scores 0), intermediate (score 1), high (score 2), and very high (score 3). The rates of late VA's in the training cohort at 1 year were 9.5%, 14%, 18%, and 25% which was almost similar to the risk of late VA's at validation cohort 10%, 12%, 20%, and 63%, respectively.ConclusionsLate sustained VAs occurred in 30% of the patients who received LVAD and were associated with lower survival. The VIN risk score was developed and validated to stratify patients into low, intermediate, high, and very high risk of late sustained VAs.

Abstract Introduction Gastrointestinal bleeding (GIB) is often encountered among patients with atrial fibrillation (AF) due to the use of anticoagulation. This study assesses disparities in GIB‐related mortality among decedents with AF in the United States. Methods GIB mortality data in patients with AF from 1999 to 2020 was queried from the CDC database. Decedent demographic information (age, sex, race and ethnicity, and geographic residence) was obtained from death certificates. We calculated age‐adjusted mortality rates (AAMRs) through the direct method and estimated the annual percentage change (APC) in mortality using log‐linear regression models. Results From 11,209 GIB‐related deaths among AF decedents, we observed an increase in AAMR from 0.12 in 1999 to 0.21 in 2020, particularly during the 2009 to 2020 period (APC +4.8, p < .001). Disproportionate mortality rates were noted in males (AAMR 0.18) and White populations (AAMR 0.15) as compared to females (AAMR 0.13) and Black populations (AAMR 0.10), respectively. Rural regions also reported higher mortality (AAMR 0.18) than urban areas (AAMR 0.14). Mortality shifts in urban regions remained stagnant from 1999 to 2009 (APC –0.15, p = .806) followed by an increase from 2009 to 2020 (APC +4.83, p < .001). However, mortality increased consistently from 1999 to 2020 in rural regions (APC +4.08, p < .001). The Northeast US exhibited the highest mortality rate (AAMR 0.18), followed by the Midwest (AAMR 0.16), West (AAMR 0.14), and South (AAMR 0.13). Conclusions Disparities in GIB mortality among AF decedents were identified. These findings accentuate the need for targeted interventions to mitigate GIB risks in vulnerable subgroups.

Introduction: Tricuspid regurgitation (TR) is a common complication of right ventricle lead extraction (RVLE) in 5 to 10% of cases. This study aims to identify clinical outcomes such as predictors of heart failure hospitalization, need for tricuspid valve intervention, and death among patients with new severe TR after device lead removal (DLR). Methods: Patients who underwent DLR (pacemaker/ICD) between 3/1997 and 3/2024 were identified. Those who had an echocardiogram before and after RVLE with evidence of new severe TR were included. Cox univariable regression controlling for current age was used to assess association with death. Prentice Williams Peterson total time (PWPTT) Cox univariable regression was used to determine the rate of heart failure hospitalization up to three events per subject. Bivariable cox regression was used to control for ejection fraction for ICD and coil removal. Analysis was conducted using Stata IC16. Results: We identified 2,122 people who underwent RVLE, of whom 90 (4.24%) developed new severe TR and were included in the analysis. There were 68 hospitalizations among 38 people at a median of 2 years following lead extraction (IQR 0.57 to 4.5 years). The rate of hospitalization was 11.60 [9.14 to 14.71] per 100 person-years. Removal of an ICD was associated with increased hospitalization (HR 5.48 p<0.001) but not mortality (HR 1.21, p=0.707). Removal of a single coil ICD lead was associated with increased hospitalization rate (HR 3.01, p=0.031) but not mortality (HR =0.51, p=0.380). Removal of dual coil ICD lead was associated with more than a tenfold increase in hospitalization rate (HR 11.55, p=0.001) and four times the mortality rate (HR 4.05, p=0.031) (Figures 1&2). The presence of an abandoned (pacemaker/ICD) lead was associated with increased hospitalization (HR 5.75, p=0.004) and mortality (HR4.95, p=0.034). There was no change in hospitalization rate following tricuspid valve replacement (HR 1.33, p=0.716, n=18). Conclusion: Among people with new severe TR following DLR, the characteristics of the leads are strongly correlated with morbidity and mortality.

Background: The optimal timing of pacemaker reimplantation following transvenous lead removal (TLR) of infected cardiac implantable electronic device (CIED) remains unclear. Objective: Our study aimed to assess the impact of timing to pacemaker reimplantation after TLR of infected CIED on hospital outcomes. Method: Using the Nationwide Readmissions Database, patients aged ≥18 years who underwent new pacemaker implantation with percutaneous approach following TLR of infected CIED from 2017 to 2020 were identified. The study population was stratified based on the timing of pacemaker reimplantation following TLR of infected CIED: early (<5 days) vs delayed (≥5 days). Weighted-propensity-score matched conditional multivariable logistic regressions were performed to determine the impact of the timing on various outcomes. Results: In our study, 469 (66.9%) patients received early device reimplantation, and 232 (33.1%) patients received delayed device reimplantation (≥5 days). Post-procedurally, patients in the delayed group had a higher risk of prolonged hospital stay (95% CI OR: 42.37 (6.36 – 282.11); p<0.01) and non-home discharge (95% CI OR: 2.00 (1.35 – 2.95), p<0.01). There was no significant difference between both groups in the early mortality, 30-day readmission, and procedural complications. Conclusion: Our study suggests that time-to-device reimplantation from TLR of infected CIED did not affect the overall short-term in-hospital outcomes. However, delayed device reimplantation was associated with a higher rate of prolonged hospital stay and non-home discharge.

Background Hyperlipidemia is a major cardiovascular disease (CVD) risk factor, but there are limited data on its mortality trends in CVD over time. We assessed annual hyperlipidemia‐related CVD mortality trends in the United States, including the COVID‐19 pandemic's impact. Methods and Results Mortality data were obtained from the Centers for Disease Control and Prevention repository between 1999 and 2020 among patients ≥15 years old, using International Classification of Diseases, Tenth Revision ( ICD‐10 ) codes for hyperlipidemia (E78.0–E78.5) and CVD (I00–I99). Age‐adjusted mortality rates (AAMRs) per 1 000 000 population were standardized to the 2000 US population. Log‐linear regression models were used to evaluate mortality shifts. Average annual percentage change from 1999 to 2019 was used to project 2020 AAMRs, estimating pandemic‐attributed excess deaths. From 1999 to 2020, 483 155 hyperlipidemia‐related CVD deaths occurred. Despite a general CVD mortality decline, hyperlipidemia‐related CVD AAMRs rose from 36.33 in 1999 to 99.77 in 2019. Ischemic heart diseases (AAMR 49.39) were the leading cause, whereas hypertension had the highest mortality increase (average annual percentage change +10.23%). Mortality rates were higher in men (AAMR 104.87) and non‐Hispanic (AAMR 82.49), and rural populations (AAMR 89.98). Highest mortality was observed in Black populations (AAMR 84.35), those ≥75 years old (AAMR 646.45), and Western US regions (AAMR 96.88). During the first pandemic year, deaths exceeded projections by 10.55%, with notable increases among ages 35 to 75 (14.23%), Hispanic (17.96%), Black (14.82%), and urban (11.68%) groups. Conclusions Hyperlipidemia‐related CVD mortality has risen over the past 2 decades, further heightened by the COVID‐19 pandemic, with higher impact on men, Black Americans, the older population, and rural residents. Further study is needed to understand contributing factors and mitigate disparities.