Heart transplant policy and outcomes, cost-effectiveness, mathematical modeling
Continuous-flow left ventricular assist devices (CF-LVADs) are increasingly used in advanced heart failure patients. Recent studies suggest that low socioeconomic status (SES) predicts worst survival after heart transplantation. Both individual-level and neighborhood-level SES (nSES) have been linked to cardiovascular health; however, the impact of SES in CF-LVAD patients remains unknown. We hypothesized that SES is a major determinant of CF-LVAD candidacy and postimplantation outcomes. A retrospective chart review was conducted on 362 patients between February 2009 and May 2016. Neighborhood-level SES was measured using the American Community Survey data and the Agency for Healthcare Research and Quality SES index score. Individual-level SES was self reported. Kaplan-Meier survival analysis and multivariable Cox proportional hazards regression determined survival statistics. Patients in the highest SES tertile were older (58 ± 13 vs. 53 ± 14; p < 0.001), less likely to be black or Hispanic (26% vs. 70%; p < 0.001), more likely to be married (87% vs. 65%; p < 0.001), more likely to have private insurance (50% vs. 39%; p < 0.001), and more likely to have employment (29% vs. 15%; p < 0.001) compared with patients in the lowest tertile. Low nSES was associated with a decreased risk of death (hazard ratio [HR], 0.580; 95% confidence interval [CI], 0.347-0.970; p = 0.038) in comparison to the high nSES. However, after adjusting for baseline clinical morbidities, the relationship was no longer present. When selecting patients for a LVAD, SES should not be thought of as an immutable risk factor. Carefully selected low-SES patients could be safely implanted with CF-LVAD with outcomes comparable to high-SES patients.
View details for DOI 10.1097/MAT.0000000000001009
View details for PubMedID 31192839
This study sought to evaluate the impact of moderate to severe aortic insufficiency (AI) on outcomes in patients with continuous flow left ventricular assist devices (CF-LVADs).Development of worsening AI is a common complication of prolonged CF-LVAD support and portends poor prognosis in single-center studies. Predictors of worsening AI and its impact on clinical outcomes have not been examined in a large cohort.We conducted a retrospective analysis of patients with CF-LVAD in the INTERMACS (Interagency Registry for Mechanically Assisted Circulatory Support) study. Development of significant AI was defined as the first instance of at least moderate AI. Primary outcomes of interest were survival after development of significant AI and time to adverse events, including device complications and rehospitalizations.Among 10,603 eligible patients, 1,399 patients on CF-LVAD support developed moderate to severe AI. Prevalence of significant AI progressively increased over time. Predictors of worsening AI included older age, female sex, smaller body mass index, mild pre-implantation AI, and destination therapy strategy. Moderate to severe AI was associated with significantly higher left ventricular end-diastolic diameter, reduced cardiac output, and higher levels of brain natriuretic peptide. Significant AI was associated with higher rates of rehospitalization (32.1% vs. 26.6%, respectively, at 2 years; p = 0.015) and mortality (77.2% vs. 71.4%, respectively, at 2 years; p = 0.005), conditional upon survival to 1 year.Development of moderate to severe AI has a negative impact on hemodynamics, hospitalizations, and survival on CF-LVAD support. Pre- and post-implantation management strategies should be developed to prevent and treat this complication.
View details for DOI 10.1016/j.jchf.2018.07.012
View details for PubMedID 30384913
View details for PubMedCentralID PMC6217859
There is mixed evidence of racial and socioeconomic disparities in heart transplant outcomes. Their underlying cause-and whether individual- or community-level traits are most influential-remains unclear. The current study aimed to characterize socioeconomic disparities in outcomes and identify time trends and mediators of these disparities.We used United Network for Organ Sharing registry data and included 33?893 adult heart transplant recipients between 1994 and 2014. Socioeconomic status (SES) indicators included insurance, education, and neighborhood SES measured using a composite index. Black race and multiple indicators of low SES were associated with the primary outcome of death or retransplant, independent of baseline clinical characteristics. Blacks had lower HLA and race matching, but further adjustment for these and other graft characteristics only slightly attenuated the association with black race (HR, 1.25 after adjustment). This and the associations with neighborhood SES (HR, 1.19 for lowest versus highest decile), Medicare (HR, 1.17), Medicaid (HR, 1.29), and college education (HR, 0.90) remained significant after full adjustment. When comparing early (1994-2000) and late (2001-2014) cohorts, the disparities associated with the middle (second and third) quartiles significantly decreased over time, but those associated with lowest SES quartile and black race persisted. Low neighborhood SES was also associated with higher risks of noncompliance (HR, 1.76), rejection (HR, 1.28), hospitalization (HR, 1.13), and infection (HR, 1.10).Racial and socioeconomic disparities exist in heart transplant outcomes, but the latter may be narrowing over time. These disparities are not explained by differences in clinical or graft characteristics.
View details for DOI 10.1161/CIRCHEARTFAILURE.117.004173
View details for PubMedID 29664403
Patients with restrictive cardiomyopathy (RCM) and hypertrophic cardiomyopathy (HCM) generally are considered poor candidates for mechanical circulatory support devices (MCSDs) and often not able to be bridged mechanically to heart transplantation. This study characterized MCSD utilization and transplant waitlist outcomes in patients with RCM/HCM under the current allocation system and discusses changes in the era of the new donor allocation system.Patients waitlisted from 2006 to 2016 in the United Network for Organ Sharing registry were stratified by RCM/HCM versus other diagnoses. MCSD utilization and waitlist duration were analyzed by propensity score models. Waitlist outcomes were assessed by cumulative incidence functions with competing events. Predictors of waitlist mortality or delisting for worsening status in patients with RCM/HCM were identified by proportional hazards model. Of 30?608 patients on the waitlist, 5.1% had RCM/HCM. Patients with RCM/HCM had 31 fewer waitlist days (P<0.01) and were ?26% less likely to receive MCSD (P<0.01). Cumulative incidence of waitlist mortality was similar between cohorts; however, patients with RCM/HCM had higher incidence of heart transplantation. Predictors of waitlist mortality or delisting for worsening status in patients with RCM/HCM without MCSD support included estimated glomerular filtration rate <60 mL/min per 1.73 m2, pulmonary capillary wedge pressure >20 mm?Hg, inotrope use, and subjective frailty.Patients with RCM/HCM are less likely to receive MCSD but have similar waitlist mortality and slightly higher incidence of transplantation compared with other patients. The United Network for Organ Sharing RCM/HCM risk model can help identify patients who are at high risk for clinical deterioration and in need of expedited heart transplantation.
View details for DOI 10.1161/CIRCHEARTFAILURE.117.004665
View details for PubMedID 29664407
View details for PubMedCentralID PMC5905429
Low socioeconomic status (SES) is a known risk factor for heart failure, mortality among those with heart failure, and poor post heart transplant (HT) outcomes. This study sought to determine whether SES is associated with decreased waitlist survival while on left ventricular assist device (LVADs) support and after HT.A total of 3361 adult patients bridged to primary HT with an LVAD between May 2004 and April 2014 were identified in the UNOS database (United Network for Organ Sharing). SES was measured using the Agency for Healthcare Research and Quality SES index using data from the 2014 American Community Survey. In the study cohort, SES did not have an association with the combined end point of death or delisting on LVAD support (P=0.30). In a cause-specific unadjusted model, those in the top (hazard ratio, 1.55; 95% confidence interval, 1.14-2.11; P=0.005) and second greatest SES quartile (hazard ratio 1.50; 95% confidence interval, 1.10-2.04; P=0.01) had an increased risk of death on device support compared with the lowest SES quartile. Adjusting for clinical risk factors mitigated the increased risk. There was no association between SES and complications. Post-HT survival, both crude and adjusted, was decreased for patients in the lowest quartile of SES index compared with all other SES quartiles.Freedom from waitlist death or delisting was not affected by SES. Patients with a higher SES had an increased unadjusted risk of waitlist mortality during LVAD support, which was mitigated by adjusting for increased comorbid conditions. Low SES was associated with worse post-HT outcomes. Further study is needed to confirm and understand a differential effect of SES on post-transplant outcomes that was not seen during LVAD support before HT.
View details for DOI 10.1161/CIRCHEARTFAILURE.116.003215
View details for PubMedID 27758810
View details for PubMedCentralID PMC5123683
To determine rates of publication and reporting of results within two years for all completed clinical trials registered in ClinicalTrials.gov across leading academic medical centers in the United States.Cross sectional analysis.Academic medical centers in the United States.Academic medical centers with 40 or more completed interventional trials registered on ClinicalTrials.gov.Using the Aggregate Analysis of ClinicalTrials.gov database and manual review, we identified all interventional clinical trials registered on ClinicalTrials.gov with a primary completion date between October 2007 and September 2010 and with a lead investigator affiliated with an academic medical center.The proportion of trials that disseminated results, defined as publication or reporting of results on ClinicalTrials.gov, overall and within 24 months of study completion.We identified 4347 interventional clinical trials across 51 academic medical centers. Among the trials, 1005 (23%) enrolled more than 100 patients, 1216 (28%) were double blind, and 2169 (50%) were phase II through IV. Overall, academic medical centers disseminated results for 2892 (66%) trials, with 1560 (35.9%) achieving this within 24 months of study completion. The proportion of clinical trials with results disseminated within 24 months of study completion ranged from 16.2% (6/37) to 55.3% (57/103) across academic medical centers. The proportion of clinical trials published within 24 months of study completion ranged from 10.8% (4/37) to 40.3% (31/77) across academic medical centers, whereas results reporting on ClinicalTrials.gov ranged from 1.6% (2/122) to 40.7% (72/177).Despite the ethical mandate and expressed values and mission of academic institutions, there is poor performance and noticeable variation in the dissemination of clinical trial results across leading academic medical centers.
View details for DOI 10.1136/bmj.i637
View details for PubMedID 26888209
View details for PubMedCentralID PMC4768882
View details for DOI 10.1161/CIRCOUTCOMES.113.000831
View details for PubMedID 24425708
Google Trends is a novel, freely accessible tool that allows users to interact with Internet search data, which may provide deep insights into population behavior and health-related phenomena. However, there is limited knowledge about its potential uses and limitations. We therefore systematically reviewed health care literature using Google Trends to classify articles by topic and study aim; evaluate the methodology and validation of the tool; and address limitations for its use in research.PRISMA guidelines were followed. Two independent reviewers systematically identified studies utilizing Google Trends for health care research from MEDLINE and PubMed. Seventy studies met our inclusion criteria. Google Trends publications increased seven-fold from 2009 to 2013. Studies were classified into four topic domains: infectious disease (27% of articles), mental health and substance use (24%), other non-communicable diseases (16%), and general population behavior (33%). By use, 27% of articles utilized Google Trends for casual inference, 39% for description, and 34% for surveillance. Among surveillance studies, 92% were validated against a reference standard data source, and 80% of studies using correlation had a correlation statistic ?0.70. Overall, 67% of articles provided a rationale for their search input. However, only 7% of articles were reproducible based on complete documentation of search strategy. We present a checklist to facilitate appropriate methodological documentation for future studies. A limitation of the study is the challenge of classifying heterogeneous studies utilizing a novel data source.Google Trends is being used to study health phenomena in a variety of topic domains in myriad ways. However, poor documentation of methods precludes the reproducibility of the findings. Such documentation would enable other researchers to determine the consistency of results provided by Google Trends for a well-specified query over time. Furthermore, greater transparency can improve its reliability as a research tool.
View details for DOI 10.1371/journal.pone.0109583
View details for PubMedID 25337815
View details for PubMedCentralID PMC4215636
Recent studies show an association between neighborhood-level measures of socioeconomic status (SES) and outcomes for patients with heart failure. We do not know whether neighborhood SES has a primary effect or is a marker for individual SES.We used the data from participants of the Telemonitoring to Improve Heart Failure Outcomes (Tele-HF) trial, recruited from 33 US internal medicine and cardiology practices and examined the association between neighborhood SES and outcomes of patients with heart failure. We used census tracts as proxies for neighborhoods and constructed summary SES scores that included information about wealth and income, education, and occupation. The primary end points were readmission and all-cause mortality at 6 months. We conducted patient interviews and medical chart reviews to obtain demographic information, clinical factors, therapies, and individual SES. We included 1557 patients: 524, 516, and 517 from low, medium, and high SES neighborhoods, respectively (mean age, 61.1±15.2 years; 42.2% women).Overall, 745 patients (47.8%) had ?1 readmission and 179 patients (11.5%) died. When compared with patients in high SES neighborhoods, those living in low-SES neighborhoods were more likely to be readmitted (odds ratio, 1.35; 95% confidence interval, 1.01-1.82), but the mortality rates were not significantly different (odds ratio, 0.78; 95% confidence interval, 0.50-1.18). The results were consistent after multivariable adjustments for individual demographics, clinical factors, and individual SES.Among patients with heart failure, neighborhood SES was significantly associated with 6-month all-cause readmission even after adjusting for other patient-level factors, including individual SES. Greater number of events and longer follow-up is required to ascertain the potential effect of neighborhood SES on mortality.http://clinicaltrials.gov/. Unique identifier: NCT00303212.
View details for DOI 10.1161/CIRCOUTCOMES.113.000911
View details for PubMedID 25074375
View details for PubMedCentralID PMC5323058
View details for DOI 10.1161/CIRCOUTCOMES.114.000957
View details for PubMedID 24619323
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Latest information on COVID-19
Stanford Medicine is closely monitoring the outbreak of novel coronavirus (COVID-19). A new page is dedicated to the latest information and developments about COVID-19.
Racism and discrimination are direct affronts to Stanford Medicine?s values. Read our leaders? pledge on racial equity.
A leader in the biomedical revolution, Stanford Medicine has a long tradition of leadership in pioneering research, creative teaching protocols and effective clinical therapies.
The Pfizer and Moderna COVID-19 vaccines are the first to use the RNA coding molecule to prompt our bodies to fight the virus. Here's how they work.
Our scientists have launched dozens of research projects as part of the global response to COVID-19. Some aim to prevent, diagnose and treat the disease; others aim to understand how it spreads and how people?s immune systems respond to it.
Marketing principles could help health care professionals and policymakers frame their messaging to encourage vaccine participation.
Graeme Rosenberg's illustrations are resonating with fellow surgeons at Stanford and beyond.
A look at Stanford Medicine?s response to the new coronavirus, as well as outside perspectives on the pandemic.
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