Unplanned hospital readmissions after acute myocardial infarction: a nationwide analysis of rates, trends, predictors and causes in the United States between 2010 and 2014

30-Day unplanned readmission rates, causes and outcomes of patients hospitalized for acute coronary syndrome based on the trial participation status

BACKGROUND

This study aimed to investigate the association between index trial participation status and 30-day unplanned readmission rates, causes, and outcomes in acute coronary syndrome (ACS) patients.

METHODS

The National Readmission Database was analysed for all index hospitalizations with a principal diagnosis of ACS between October 2015 to November 2019, stratified by index trial participation status (International Classification of Diseases - 10th edition code: Z00.6). The 30-day unplanned readmission rates, causes and outcomes were analysed, including the assessment of factors associated with readmission. Multivariable regression analyses were reported as adjusted odds ratios (aOR) with 95 % confidence intervals (95 % CI). All analyses were weighted and utilized hierarchical multi-level organization.

RESULTS

A total of 2,066,328 cases with a principal diagnosis of ACS were included in the study, of which there were 4061 trial participants (0.2 %) and 189,240 (9.2 %) cases experienced unplanned 30-day readmission. Rates of unplanned 30-day readmission were similar between trial participants and non-participants (9.8 % vs. 9.2 %, p = 0.16). Consistently, after multivariable adjustment, there was no significant association between trial participation and unplanned 30-day readmissions (aOR 0.96, 95 % CI 0.86-1.07, p = 0.45). Compared with trial participants, the majority of readmissions in non-participants were related to cardiovascular conditions (55.2 % vs. 46.7 %, p = 0.005, respectively). There was no significant difference in all-cause mortality (5.5 % vs. 4.6 %, p = 0.368, respectively), but trial participants were more likely to develop major bleeding (3.5 % vs. 2.1 %, p = 0.044), ischemic stroke (4.0 % vs. 2.1 %, p = 0.008) and haemorrhagic stroke (2.0 % vs. 0.6 %, p < 0.001) at readmissions.

CONCLUSION

Overall rates of unplanned 30-day readmissions after ACS are similar between trial participants and non-participants, but non-participation in trials was associated with a higher likelihood of cardiovascular readmission.

A Detailed Analysis of Cardiac Rehabilitation on 180-Day All-Cause Hospital Readmission and Mortality

PURPOSE

Cardiac rehabilitation (CR) is endorsed for coronary artery disease (CAD), but studies report inconsistent findings regarding efficacy. The objective of this study was to determine whether confounding factors, potentially contributing to these heterogeneous findings, impact the effect of CR on all-cause readmission and mortality.

METHODS

Patients (n = 2641) with CAD, CR eligible, and physically able were identified. Electronic medical records were inspected individually for each patient to extract demographic, clinical characteristic, readmission, and mortality information. Patients (n = 214) attended ≥1 CR session (CR group). Survival was considered free from: all-cause readmission; or composite outcome of all-cause readmission or death. Cox proportional hazards models, adjusting for demographics, comorbidities, and discharge criteria, were used to determine HR with 95% CI and to compare 180-d survival rates between the CR and no-CR groups.

RESULTS

During 180 d of follow-up, 12.1% and 18.7% of the CR and non-CR patients were readmitted to the hospital. There was one death (0.5%) in the CR group, while 98 deaths (4.0%) occurred in the non-CR group. After adjustment for age, sex, race, depression, anxiety, dyslipidemia, hypertension, obesity, smoking, type 2 diabetes, and discharge criteria, the final model revealed a significant 42.7% reduction in readmission or mortality risk for patients who attended CR (HR = 0.57: 95% CI, 0.33-0.98; P = .043).

CONCLUSIONS

Regardless of demographic characteristics, comorbidities, and cardiovascular discharge criteria, the risk of 180-d all-cause readmission or death was markedly decreased in patients who attended CR compared with those who did not.

Heart Failure Readmission in Patients With ST-Segment Elevation Myocardial Infarction and Active Cancer

Background

Although numerous studies have examined readmission with heart failure (HF) after acute myocardial infarction (AMI), limited data are available on HF readmission in cancer patients post-AMI.

Objectives

This study aimed to assess the rates and factors associated with HF readmission in cancer patients presenting with ST-segment elevation myocardial infarction (STEMI).

Methods

A nationally linked cohort of STEMI patients between January 2005 and March 2019 were obtained from the UK Myocardial Infarction National Audit Project registry and the UK national Hospital Episode Statistics Admitted Patient Care registry. Multivariable Fine-Gray competing risk models were used to evaluate HF readmission at 30 days and 1 year.

Results

A total of 326,551 STEMI indexed admissions were included, with 7,090 (2.2%) patients having active cancer. The cancer group was less likely to be admitted under the care of a cardiologist (74.5% vs 81.9%) and had lower rates of invasive coronary angiography (62.2% vs 72.7%; P < 0.001) and percutaneous coronary intervention (58.4% vs. 69.5%). There was a significant prescription gap in the administration of post-AMI medications upon discharge such as an angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (49.5% vs 71.1%) and beta-blockers (58.4% vs 68.0%) in cancer patients. The cancer group had a higher rate of HF readmission at 30 days (3.2% vs 2.3%) and 1 year (9.4% vs 7.3%). However, after adjustment, cancer was not independently associated with HF readmission at 30 days (subdistribution HR: 1.05; 95% CI: 0.86-1.28) or 1 year (subdistribution HR: 1.03; 95% CI: 0.92-1.16). The opportunity-based quality indicator was associated with higher rates of HF readmission independent of cancer diagnosis.

Conclusions

Cancer patients receive care that differs in important ways from patients without cancer. Greater implementation of evidence-based care may reduce HF readmissions, including in cancer patients.

Prediction of Early and Long-Term Hospital Readmission in Patients with Severe Obesity: A Retrospective Cohort Study

Adults with obesity have a higher risk of hospitalization and high hospitalization-related healthcare costs. However, a predictive model for the risk of readmission in patients with severe obesity is lacking. We conducted a retrospective cohort study enrolling all patients admitted for severe obesity (BMI ≥ 40 kg/m2) between 2009 and 2018 to the Istituto Auxologico Italiano in Piancavallo. For each patient, all subsequent hospitalizations were identified from the regional database by a deterministic record-linkage procedure. A total of 1136 patients were enrolled and followed up for a median of 5.7 years (IQR: 3.1-8.2). The predictive factors associated with hospital readmission were age (HR = 1.02, 95%CI: 1.01-1.03, p < 0.001), BMI (HR = 1.02, 95%CI: 1.01-1.03, p = 0.001), smoking habit (HR = 1.17, 95%CI: 0.99-1.38, p = 0.060), serum creatinine (HR = 1.22, 95%CI: 1.04-1.44, p = 0.016), diabetes (HR = 1.17, 95%CI: 1.00-1.36, p = 0.045), and number of admissions in the previous two years (HR = 1.15, 95%CI: 1.07-1.23, p < 0.001). BMI lost its predictive role when restricting the analysis to readmissions within 90 days. BMI and diabetes lost their predictive roles when further restricting the analysis to readmissions within 30 days. In conclusion, in this study, we identified predictive variables associated with early and long-term hospital readmission in patients with severe obesity. Whether addressing modifiable risk factors could improve the outcome remains to be established.

The IL-1 Family and Its Role in Atherosclerosis

The IL-1 superfamily of cytokines is a central regulator of immunity and inflammation. The family is composed of 11 cytokines (with agonist, antagonist, and anti-inflammatory properties) and 10 receptors, all tightly regulated through decoy receptor, receptor antagonists, and signaling inhibitors. Inflammation not only is an important physiological response against infection and injury but also plays a central role in atherosclerosis development. Several clinical association studies along with experimental studies have implicated the IL-1 superfamily of cytokines and its receptors in the pathogenesis of cardiovascular disease. Here, we summarize the key features of the IL-1 family, its role in immunity and disease, and how it helps shape the development of atherosclerosis.

Ability of the LACE Index to Predict 30-Day Readmissions in Patients with Acute Myocardial Infarction

Aims: This study aimed to utilize the existing LACE index (length of stay, acuity of admission, comorbidity index and emergency room visit in the past six months) to predict the risk of 30-day readmission and to find the associated factors in patients with AMI. Methods: This was a retrospective study and LACE index scores were calculated for patients admitted with AMI between 2015 and 2019. Data were utilized from the hospital’s electronic medical record. Multivariate logistic regression was performed to find the association between covariates and 30-day readmission. The risk prediction ability of the LACE index for 30-day readmission was analyzed by receiver operating characteristic curves with the C statistic. Results: A total of 205 (5.7%) patients were readmitted within 30 days. The odds ratio of older age group (OR = 1.78, 95% CI: 1.54–2.05), admission via emergency ward (OR = 1.45; 95% CI: 1.42–1.54) and LACE score ≥10 (OR = 2.71; 95% CI: 1.03–4.37) were highly associated with 30-day readmissions and statistically significant. The receiver operating characteristic curve C statistic of the LACE index for AMI patients was 0.78 (95% CI: 0.75–0.80) and showed favorable discrimination in the prediction of 30-day readmission. Conclusion: The LACE index showed a good discrimination to predict the risk of 30-day readmission for hospitalized patients with AMI. Further study would be recommended to focus on additional factors that can be used to predict the risk of 30-day readmission; this should be considered to improve the model performance of the LACE index for other acute conditions by using the national-based administrative data.

Readmission After ACS: Burden, Epidemiology, and Mitigation

PURPOSE OF REVIEW

The past decade has brought increased efforts to better understand causes for ACS readmissions and strategies to minimize them. This review seeks to provide a critical appraisal of this rapidly growing body of literature.

RECENT FINDINGS

Prior to 2010, readmission rates for patients suffering from ACS remained relatively constant. More recently, several strategies have been implemented to mitigate this including improved risk assessment models, transition care bundles, and development of targeted programs by federal organizations and professional societies. These strategies have been associated with a significant reduction in ACS readmission rates in more recent years. With this, improvements in 30-day post-discharge mortality rates are also being appreciated. As we continue to expand our knowledge on independent risk factors for ACS readmissions, further strategies targeting at-risk populations may further decrease the rate of readmissions. Efforts to understand and reduce 30-day ACS readmission rates have resulted in overall improved quality of care for patients.

Epidemiology of Geographic Disparities of Myocardial Infarction Among Older Adults in the United States: Analysis of 2000-2017 Medicare Data

Background: There are substantial geographic disparities in the life expectancy (LE) across the U.S. with myocardial infarction (MI) contributing significantly to the differences between the states with highest (leading) and lowest (lagging) LE. This study aimed to systematically investigate the epidemiology of geographic disparities in MI among older adults.

Methods: Data on MI outcomes among adults aged 65+ were derived from the Center for Disease Control and Prevention-sponsored Wide-Ranging Online Data for Epidemiologic Research database and a 5% sample of Medicare Beneficiaries for 2000–2017. Death certificate-based mortality from MI as underlying/multiple cause of death (CBM-UCD/CBM-MCD), incidence-based mortality (IBM), incidence, prevalence, prevalence at age 65, and 1-, 3-, and 5-year survival, and remaining LE at age 65 were estimated and compared between the leading and lagging states. Cox model was used to investigate the effect of residence in the lagging states on MI incidence and survival.

Results: Between 2000 and 2017, MI mortality was higher in the lagging than in the leading states (per 100,000, CBM-UCD: 236.7–583.7 vs. 128.2–357.6, CBM-MCD: 322.7–707.7 vs. 182.4–437.7, IBM: 1330.5–1518.9 vs. 1003.3–1197.0). Compared to the leading states, lagging states had higher MI incidence (1.1–2.0% vs. 0.9–1.8%), prevalence (10.2–13.1% vs. 8.3–11.9%), pre-existing prevalence (2.5–5.1% vs. 1.4–3.6%), and lower survival (70.4 vs. 77.2% for 1-year, 63.2 vs. 67.2% for 3-year, and 52.1 vs. 58.7% for 5-year), and lower remaining LE at age 65 among MI patients (years, 8.8–10.9 vs. 9.9–12.8). Cox model results showed that the lagging states had greater risk of MI incidence [Adjusted hazards ratio, AHR (95% Confidence Interval, CI): 1.18 (1.16, 1.19)] and death after MI diagnosis [1.22 (1.21, 1.24)]. Study results also showed alarming declines in survival and remaining LE at age 65 among MI patients.

Conclusion: There are substantial geographic disparities in MI outcomes, with lagging states having higher MI mortality, incidence, and prevalence, lower survival and remaining LE at age 65. Disparities in MI mortality in a great extent could be due to between-the-state differences in MI incidence, prevalence at age 65 and survival. Observed declines in survival and remaining LE require an urgent analysis of contributing factors that must be addressed.

The changing landscape of atherosclerosis

Emerging evidence has spurred a considerable evolution of concepts relating to atherosclerosis, and has called into question many previous notions. Here I review this evidence, and discuss its implications for understanding of atherosclerosis. The risk of developing atherosclerosis is no longer concentrated in Western countries, and it is instead involved in the majority of deaths worldwide. Atherosclerosis now affects younger people, and more women and individuals from a diverse range of ethnic backgrounds, than was formerly the case. The risk factor profile has shifted as levels of low-density lipoprotein (LDL) cholesterol, blood pressure and smoking have decreased. Recent research has challenged the protective effects of high-density lipoprotein, and now focuses on triglyceride-rich lipoproteins in addition to low-density lipoprotein as causal in atherosclerosis. Non-traditional drivers of atherosclerosis-such as disturbed sleep, physical inactivity, the microbiome, air pollution and environmental stress-have also gained attention. Inflammatory pathways and leukocytes link traditional and emerging risk factors alike to the altered behaviour of arterial wall cells. Probing the pathogenesis of atherosclerosis has highlighted the role of the bone marrow: somatic mutations in stem cells can cause clonal haematopoiesis, which represents a previously unrecognized but common and potent age-related contributor to the risk of developing cardiovascular disease. Characterizations of the mechanisms that underpin thrombotic complications of atherosclerosis have evolved beyond the 'vulnerable plaque' concept. These advances in our understanding of the biology of atherosclerosis have opened avenues to therapeutic interventions that promise to improve the prevention and treatment of now-ubiquitous atherosclerotic diseases.