Socioeconomic Disparities in Referral for Invasive Hemodynamic Evaluation for Advanced Heart Failure: A Nationwide Cohort Study

The relation between socioeconomic status and invasive haemodynamics at evaluation for advanced heart failure

AIMS

Socioeconomic deprivation is a risk marker for worse prognosis in patients with heart failure (HF), and a potential barrier to referral for advanced HF evaluation. The relationship between socioeconomic status (SES) and invasive haemodynamics in patients undergoing evaluation for advanced HF therapies is unknown.

METHODS

We combined a consecutive clinical registry of patients evaluated for advanced HF with patient-level data on SES (household income, education, workforce status, cohabitant status and distance from home to tertiary HF centre) derived from nationwide registries. Using this information, the cohort was divided into groups of low-, medium- and high degree of socioeconomic deprivation. The associations between SES and invasive haemodynamics were explored with multiple linear regression adjusted for age and sex.

RESULTS

A total of 631 patients were included. The median age was 53 years, and 23% were women. Patients in the highest income quartile versus the lowest (Q4 vs. Q1) were older (median age 57 vs. 50 years) and more often male (83% vs. 67%), both P < 0.001. Increasing household income (per 100 000 Danish kroner,1 EUR = 7.4 DKK) was associated with lower pulmonary capillary wedge pressure (PCWP) [-0.18 mmHg, 95% confidence interval (CI) -0.36 to -0.01, P = 0.036] but not significantly associated with central venous pressure (CVP) (-0.07 mmHg, 95% CI -0.21 to 0.06, P = 0.27), cardiac index (-0.004 L/min/m2, 95% CI -0.02 to 0.01, P = 0.60), or pulmonary vascular resistance (PVR) (-0.003 Wood units, 95% CI -0.37 to 0.16, P = 0.84). Comparing the most deprived with the least deprived group, adjusted mean PVR was higher (0.35 Wood units, 95% CI 0.02 to 0.68, P = 0.04), but PCWP (0.66 mmHg, 95% CI -1.49 to 2.82, P = 0.55), CVP (-0.26 mmHg, 95% CI -1.76 to 1.24, P = 0.73) and cardiac index (-0.03 L/min/m2, 95% CI -0.22 to 0.17, P = 0.78) were similar.

CONCLUSIONS

Most haemodynamic measurements were similar across layers of SES. Nevertheless, there were some indications of worse haemodynamics in patients with lower household income or a high accumulated burden of socioeconomic deprivation. Particular attention may be warranted in socioeconomically deprived patients to ensure timely referral for advanced HF evaluation.

Socio-economic inequalities and heart failure morbidity and mortality: A systematic review and data synthesis

Socio-economic status (SES) has been associated with incident and prevalent heart failure (HF), as well as its morbidity and mortality. However, the precise nature of the relationship between SES and HF remains unclear due to inconsistent data. This study aims to provide a comprehensive assessment and data synthesis of the relationship between SES and HF morbidity and mortality. We performed a systematic search and data synthesis using six databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines. The included studies comprised observational studies that reported on HF incidence and prevalence, HF hospitalizations, worsening HF (WHF) and all-cause mortality, as well as treatment options (medical, device and advanced HF therapies). SES was measured on both individual and area levels, encompassing single (e.g., income, education, employment, social risk score, living conditions and housing characteristics) and composite indicators. Among the 4124 studies screened, 79 were included, with an additional 5 identified through cross-referencing. In the majority of studies, a low SES was associated with an increased HF incidence (72%) and prevalence (75%). For mortality, we demonstrated that low SES was associated with increased mortality in 45% of the studies, with 18% of the studies showing mixed results (depending on the indicator, gender or follow-up) and 38% showing non-significant results. Similar patterns were observed for the association between SES, WHF, medical therapy prescriptions and the utilization of devices and advanced HF therapies. There was no clear pattern in the used SES indicators and HF outcomes. This systematic review, using contemporary data, shows that while socio-economic disparity may influence HF incidence, management and subsequent adverse events, these associations are not uniformly predictive. Our review highlights that the impact of SES varies depending on the specific indicators used, reflecting the complexity of its influence on health disparities. Assessment and recognition of SES as an important risk factor can assist clinicians in early detection and customizing HF treatment, while also aiding policymakers in optimizing resource allocation.

Performance of risk models to predict mortality risk for patients with heart failure: evaluation in an integrated health system

BACKGROUND

Referral of patients with heart failure (HF) who are at high mortality risk for specialist evaluation is recommended. Yet, most tools for identifying such patients are difficult to implement in electronic health record (EHR) systems.

OBJECTIVE

To assess the performance and ease of implementation of Machine learning Assessment of RisK and EaRly mortality in Heart Failure (MARKER-HF), a machine-learning model that uses structured data that is readily available in the EHR, and compare it with two commonly used risk scores: the Seattle Heart Failure Model (SHFM) and Meta-Analysis Global Group in Chronic (MAGGIC) Heart Failure Risk Score.

DESIGN

Retrospective, cohort study.

PARTICIPANTS

Data from 6764 adults with HF were abstracted from EHRs at a large integrated health system from 1/1/10 to 12/31/19.

MAIN MEASURES

One-year survival from time of first cardiology or primary care visit was estimated using MARKER-HF, SHFM, and MAGGIC. Discrimination was measured by the area under the receiver operating curve (AUC). Calibration was assessed graphically.

KEY RESULTS

Compared to MARKER-HF, both SHFM and MAGGIC required a considerably larger amount of data engineering and imputation to generate risk score estimates. MARKER-HF, SHFM, and MAGGIC exhibited similar discriminations with AUCs of 0.70 (0.69-0.73), 0.71 (0.69-0.72), and 0.71 (95% CI 0.70-0.73), respectively. All three scores showed good calibration across the full risk spectrum.

CONCLUSIONS

These findings suggest that MARKER-HF, which uses readily available clinical and lab measurements in the EHR and required less imputation and data engineering than SHFM and MAGGIC, is an easier tool to identify high-risk patients in ambulatory clinics who could benefit from referral to a HF specialist.

Influence of socioeconomic status on rates of advanced heart failure therapies

BACKGROUND

Socioeconomic deprivation is associated with a lower likelihood of referral for advanced heart failure (HF) evaluation, but it is not known whether it influences rates of advanced HF therapies independently of key hemodynamic measures and comorbidity following advanced HF evaluation in a universal healthcare system.

METHODS

We linked data from a single-center Danish clinical registry of consecutive patients evaluated for advanced HF with patient-level information on socioeconomic status. Patients were divided into groups based on the level of education (low, medium, and high), combined degree of socioeconomic deprivation (low, medium, and high), and household income quartiles. Rates of the combined outcome of left ventricular assist device implantation or heart transplantation (advanced HF therapy) with death as a competing risk were estimated with cumulative incidence functions, and Cox proportional hazards models adjusted for age, sex, central venous pressure, cardiac index, and comorbidities.

RESULTS

We included 629 patients, median age 53 years, of whom 77% were men. During a median follow-up of 5 years, 179 (28%) underwent advanced HF therapy. The highest level of education was associated with higher rates (high vs low, adjusted HR 1.81 95% CI 1.14-2.89, p = 0.01), whereas household income quartile groups (Q4 vs Q1, adjusted HR 1.37 95% CI 0.76-2.47, p = 0.30) or groups of combined socioeconomic deprivation (high vs low degree of deprivation, adjusted HR 0.86 95% CI 0.50-1.46, p = 0.56) were not significantly associated with rates of advanced HF therapy.

CONCLUSIONS

Patients with a lower level of education might be disfavored for advanced HF therapies and could require specific attention in the advanced HF care center.

Socioeconomic status and in-hospital outcomes for patients undergoing heart transplantation or ventricular assist device implantation

INTRODUCTION

Although lower socioeconomic status (SES) has been associated with worse in-hospital outcomes among patients with heart failure, the in-hospital outcomes for patients undergoing durable Left Ventricular Assist Device (LVAD) implantation or Heart Transplantation (HT) based on SES have not been well characterized.

METHODS

We analyzed data from the National Inpatient Sample of hospitalizations between January 2016 and December 2020 of patients aged 18 and over who underwent a HT or newly implanted LVAD. Quartile classification of the median household income of the patient's residential zip code was used to estimate SES. Multivariable analyses with logistic and linear regression were used to evaluate the effects of SES on inpatient outcomes including inpatient mortality, length of stay, and key inpatient complications.

RESULTS

A total of 16,265 weighted hospitalizations for new LVAD implantation and 14,320 weighted hospitalizations for HT were identified. In multivariable analysis, among patients undergoing HT or LVAD implantation respectively, there were no significant differences between the lowest and highest SES quartiles among important in-hospital outcomes including length of stay (adj B-coeff .56, (-3.59)-(4.71), p = .79 and adj B-coeff 2.40, (-.21)-(5.02), p = .07) and mortality (aOR 1.02, .61-1.70, p = .94 and aOR 1.08, .72-1.62, p = .73). There were also no differences based on SES quartile in important inpatient complications including stroke and cardiac arrest.

CONCLUSION

In this analysis from the National Inpatient Sample, we demonstrate that SES, evaluated by median zip code income, was not associated with important in-hospital metrics including mortality and length of stay among patients undergoing LVAD or HT.

Diabetes mellitus and hemodynamics in advanced heart failure

BACKGROUND

The presence of diabetes in patients with heart failure (HF) is associated with a worse prognosis. It is unclear if hemodynamics in HF patients with DM differ from those of non-diabetic patients and how this might influence outcome. This study aims to discover the impact of DM on hemodynamics in HF patients.

METHODS

Consecutive patients (n = 598) with HF and reduced ejection fraction (LVEF ≤40%) undergoing invasive hemodynamic evaluation were included (non-DM: n = 473, DM: n = 125). Hemodynamic parameters included pulmonary capillary wedge pressure (PCWP), central venous pressure (CVP), cardiac index (CI) and mean arterial pressure (MAP). Mean follow-up was 9.5 ± 5.1 years.

RESULTS

Patients with DM (82.7% male, mean age 57.1 ± 10.1 years, mean HbA1c 60 ± 21 mmol/mol) had higher PCWP, mPAP, CVP and higher MAP. Adjusted analysis demonstrated that DM patients had higher PCWP and CVP. Increasing HbA1c-values were correlated with higher PCWP (p = 0.017) and CVP (p = 0.043).

CONCLUSION

Patients with DM, especially those with poor glycemic control, have higher filling pressures. This may be a feature of diabetic cardiomyopathy, however, other unknown mechanisms beyond hemodynamic factors are likely to explain the increased mortality associated with diabetes in HF.

Influence of socioeconomic factors on discharge disposition following traumatic cervicothoracic spinal cord injury at level I and II trauma centers in the United States

BACKGROUND

Discharge to acute rehabilitation is strongly correlated with functional recovery after traumatic injury, including spinal cord injury (SCI). However, services such as acute care rehabilitation and Skilled Nursing Facilities (SNF) are expensive. Our objective was to understand if high-cost, resource-intensive post-discharge rehabilitation or alternative care facilities are utilized at disparate rates across socioeconomic groups after SCI.

METHODS

We performed a cohort analysis using the National Trauma Data Bank® tabulated from 2012-2016. Eligible patients had a diagnosis of cervical or thoracic spine fracture with spinal cord injury (SCI) and were treated surgically. We evaluated associations of sociodemographic and psychosocial variables with non-home discharge (e.g., discharge to SNF, other healthcare facility, or intermediate care facility) via multivariable logistic regression while correcting for injury severity and hospital characteristics.

RESULTS

We identified 3933 eligible patients. Patients who were older, male (OR=1.29 95% Confidence Interval [1.07-1.56], p=.007), insured by Medicare (OR=1.45 [1.08-1.96], p=.015), diagnosed with a major psychiatric disorder (OR=1.40 [1.03-1.90], p=.034), had a higher Injury Severity Score (OR=5.21 [2.96-9.18], p<.001) or a lower Glasgow Coma Score (3-8 points, OR=2.78 [1.81-4.27], p<.001) had a higher chance of a non-home discharge. The only sociodemographic variable associated with lower likelihood of utilizing additional healthcare facilities following discharge was uninsured status (OR=0.47 [0.37-0.60], p<.001).

CONCLUSIONS

Uninsured patients are less likely to be discharged to acute rehabilitation or alternative healthcare facilities following surgical management of SCI. High out-of-pocket costs for uninsured patients in the United States may deter utilization of these services.

A survey-based triage tool to identify patients potentially eligible for referral to an advanced heart failure centre

AIMS

Accurate prevalence data for ambulatory advanced heart failure (HF) in European countries remains limited. This study was designed to identify the population of patients potentially eligible for referral for assessment for advanced surgical HF therapies to a National advanced HF and cardiac transplant centre.

METHODS AND RESULTS

A survey comprising 13 potential clinical markers of advanced HF was developed, modified from the 'I NEED HELP' tool from the 2018 position statement of the Heart Failure Association of the European Society of Cardiology, and distributed to all HF clinic services (secondary and tertiary units) nationwide. Each HF clinic unit was asked to complete the survey on consecutive patients over a 3 month period fulfilling the following three criteria: (i) age <65 years; (ii) ejection fraction <40% and (iii) HF of >3 months duration. As a comparison, the number of actual referrals to the advanced HF clinic were also audited over a 9 month period. In all, 21 of 26 HF clinic units participated in the survey. Across the period of inclusion, 4950 all-comer HF patients were seen across all sites. Of these, 375 (7.5%) fulfilled the inclusion criteria and were surveyed (74.4% male, median age 57 years [IQR: 11 years]). In total, 246 (66%) of the surveyed patients had ≥1 potential markers for advanced HF, representing just under 5% of the total all-comer HF population seen across the same time period. Of these, 67 patients (27%) had ≥2, 48 (20%) had 3 and 40 (16%) had ≥4 potential markers. The most frequently noted markers were ≥1 HF hospitalization or unscheduled clinic review (56%), intolerance to renin-angiotensin-aldosterone system inhibitors due to hypotension or renal dysfunction (29%) and intolerance to beta-blockers due to hypotension (27%). Almost one-quarter of patients reported NYHA Class III or IV symptoms. During the advanced HF clinic audit, the number of patients actually referred to the advanced HF clinic during the same time period was <5% of this potentially eligible cohort.

CONCLUSIONS

In this index prospective National survey, approximately 5% of an all-comer routine HF clinic population and two-thirds of a pre-selected HF with reduced EF under 65 years cohort were found to have at least one clinical or biochemical marker suggesting advanced or impending advanced HF. Almost one-quarter of patients in this chronic outpatient 'snapshot' population have NYHA III-IV symptoms. This simple one-page triage survey-modified from the 'I NEED HELP' tool-is useful to identify a population potentially eligible for referral to an advanced HF centre for assessment for advanced surgical therapies, thereby aiding resource and service planning.

Treatment of advanced heart failure

Background: The development of medical and device treatment of heart failure (HF) has improved the survival and quality of life in HF patients. However, not all HF patients respond well to these up-to-date HF treatments. We have termed these non-responders as advanced HF patients. The definition, diagnosis, and treatment of advanced HF are discussed in this review article.Current Concepts: After current guideline-directed treatments, advanced HF patients can experience aggravation and decompensation, usually resulting in hospitalization for the symptoms and volume control. Recurrent decompensation or hospitalization can cause a vicious cycle between the heart and other vital organs, such as the kidney and liver. Current and up-to-date guidelines recommend treatments, including heart transplant, left ventricular assist device (LVAD), and hospice care, for advanced HF. Given the limitation of heart transplant donors, LVAD can be used as a bridge to transplant, in addition to destination therapy. Updated LVAD system can reduce pump-related thrombosis, stroke, and bleeding.Discussion and Conclusion: Current guidelines suggest early recognition of advanced HF and referral to advanced HF specialists. Despite advances in the treatments of advanced HF, unmet needs for further improving clinical outcomes and quality of life exist.