Gender Differences in the Rate of 30-Day Readmissions after Percutaneous Coronary Intervention for Acute Coronary Syndrome

Sex and Psychosocial Differences in Acute Stress Symptoms Prior to Open-Heart Surgery

BACKGROUND

Acute stress symptoms can occur while cardiac patients await open-heart surgery (OHS). The distress leads to poor outcomes. This study aimed to investigate the association of sex and psychosocial factors (quality-of-life and character strengths).

METHOD

Our study cohort included 481 pre-OHS patients (female 42%; mean age 62 years). Medical indices/factors were obtained from the Society of Thoracic Surgeon's national database. Multiple regression analyses were performed following pre-planned steps and adjusting medical factors.

RESULTS

Our findings revealed that sex differences in trauma-related symptoms were associated with poor mental well-being, alongside comorbidities. Both mental well-being and comorbidity factors were directly related to acute stress symptoms, while dispositional optimism had an inverse association with this outcome.

CONCLUSION

To improve OHS outcomes, our findings suggest healthcare providers be attentive to pre-OHS acute stress symptoms, pay greater attention to the emotional well-being of their female patients, and develop supportive interventions to enhance personality strengths.

Systematic Review and Critical Appraisal of Prediction Models for Readmission in Coronary Artery Disease Patients: Assessing Current Efficacy and Future Directions

Purpose

Coronary artery disease (CAD) patients frequently face readmissions due to suboptimal disease management. Prediction models are pivotal for detecting early unplanned readmissions. This review offers a unified assessment, aiming to lay the groundwork for enhancing prediction models and informing prevention strategies.

Methods

A search through five databases (PubMed, Web of Science, EBSCOhost, Embase, China National Knowledge Infrastructure) up to September 2023 identified studies on prediction models for coronary artery disease patient readmissions for this review. Two independent reviewers used the CHARMS checklist for data extraction and the PROBAST tool for bias assessment.

Results

From 12,457 records, 15 studies were selected, contributing 30 models targeting various CAD patient groups (AMI, CABG, ACS) from primarily China, the USA, and Canada. Models utilized varied methods such as logistic regression and machine learning, with performance predominantly measured by the c-index. Key predictors included age, gender, and hospital stay duration. Readmission rates in the studies varied from 4.8% to 45.1%. Despite high bias risk across models, several showed notable accuracy and calibration.

Conclusion

The study highlights the need for thorough external validation and the use of the PROBAST tool to reduce bias in models predicting readmission for CAD patients.

Predictors of 30-Day Re-admission in Cardiac Patients at Heart Hospital, Qatar

Background

Cardiovascular disease patients are more likely to be readmitted within 30 days of being discharged alive. This causes an enormous burden on health-care systems in terms of poor care of patients and misutilization of resources.

Aims and Objective

This study aims to find out the risk factors associated with 30-day readmission in cardiac patients at Heart Hospital, Qatar.

Methods

A total of 10,550 cardiac patients who were discharged alive within 30 days at the heart hospital in Doha, Qatar, from January 2015 and December 2019 were analyzed. The bootstrap method, an internal validation statistical technique, was applied to present representative estimates for the population.

Results

Out of the 10,550 cardiac patients, there were 8418 (79.8%) index admissions and 2132 (20.2%) re-admitted at least once within 30 days after the index admission. The re-admissions group was older than the index admission group (65.6 ± 13.2 vs. 56.0 ± 13.5, P = 0.001). Multinomial regression analysis showed that females were 30% more likely to be re-admitted than males (adjusted odds ratio [aOR] 1.30, 95% confidence interval [CI]: 1.11-1.50, P = 0.001). Diabetes (aOR 1.36, 95% CI: 1.20-1.53, P = 0.001), chronic renal failure (aOR 1.93, 95% CI: 1.66-2.24, P = 0.001), previous MI (aOR 3.22, 95% CI: 2.85-3.64, P = 0.001), atrial fibrillation (aOR 2.17, 95% C.I. : 1.10-2.67, P = 0.01), cardiomyopathy (aOR 1.72, 95% CI 1.47-2.02, P = 0.001), and chronic heart failure (aOR 1.56, 95% C.I.: 1.33-1.82, P = 0.001) were also independent predictors for re-admission in the regression model. C-statistics showed these variables could predict 82% accurately hospital readmissions within 30 days after being discharged alive.

Conclusion

The model was more than 80% accurate in predicting 30-day readmission after being discharged alive. The presence of five or more risk factors was found to be crucial for readmissions within 30 days. The study may help design interventions that may result in better outcomes with fewer resources in the population.

Introduction of specialized heart failure nurses in primary care and its impact on readmissions

BACKGROUND

Heart failure (HF) has a 2% prevalence in the population and is a major cause of morbidity and mortality. Multiple efforts have been made worldwide to improve quality of care and decrease unplanned readmissions for HF patients, one of which has been the introduction of specialist HF nurses (HFN) in primary health care. The present evidence on the benefits of HFN is contradicting. This study aims to evaluate the impact of a quality improvement intervention, availability of a HFN in Swedish primary care, on hospital readmissions.

METHODS

All patients over the age of 65 with a HF diagnosis and with complete information on availability of a HFN were included in this retrospective register-based study. Using propensity score matching (PSM) techniques, two comparable groups of 128 patients each were created according to the exposure status, availability or no availability of a HFN. The rate of readmission was compared between the groups.

RESULTS

Using PSM, 256 patients were matched, 128 in the HFN group and 128 in the no-HFN group. A total of 50% and 46.09% of patients in the HFN and no-HFN groups were readmitted, respectively. Mean number of readmissions per patient was 1.19 (SD 0.61) in the HFN group and 1.10 (SD 0.44) in the no-HFN group. Patients in the HFN had 17.6% higher odds of being readmitted during the study period, OR: 1.176 (CI: 0.716-1.932), and 3.8% lower odds of being readmitted within 30 days, OR: 0.962 (CI: 0.528-1.750).

CONCLUSIONS

Availability of a HFN in primary care was not significantly associated with reduced readmissions for the patients included in this study. Further investigations are warranted looking at the impacts of availability and access to a HFN in primary care on readmissions and other patient outcomes.

Predictive Modeling of Hospital Readmission: Challenges and Solutions

Hospital readmission prediction is a study to learn models from historical medical data to predict probability of a patient returning to hospital in a certain period, e.g. 30 or 90 days, after the discharge. The motivation is to help health providers deliver better treatment and post-discharge strategies, lower the hospital readmission rate, and eventually reduce the medical costs. Due to inherent complexity of diseases and healthcare ecosystems, modeling hospital readmission is facing many challenges. By now, a variety of methods have been developed, but existing literature fails to deliver a complete picture to answer some fundamental questions, such as what are the main challenges and solutions in modeling hospital readmission; what are typical features/models used for readmission prediction; how to achieve meaningful and transparent predictions for decision making; and what are possible conflicts when deploying predictive approaches for real-world usages. In this paper, we systematically review computational models for hospital readmission prediction, and propose a taxonomy of challenges featuring four main categories: (1) data variety and complexity; (2) data imbalance, locality and privacy; (3) model interpretability; and (4) model implementation. The review summarizes methods in each category, and highlights technical solutions proposed to address the challenges. In addition, a review of datasets and resources available for hospital readmission modeling also provides firsthand materials to support researchers and practitioners to design new approaches for effective and efficient hospital readmission prediction.

Readmission in Patients With ST-Elevation Myocardial Infarction in 4 Age Groups (<45, >45 to <60, 60 to <75, and >75)

The incidence of ST-elevation myocardial infarction (STEMI) among younger adults is increasing due to an increased prevalence of cardiometabolic risk factors. Readmissions after STEMI in young patients could lead to substantial health care costs and a significant burden on health care resources. Although STEMI readmissions are well studied in elderly patients, limited data are available regarding readmissions after STEMI in young patients and the etiologies remain poorly understood. Because younger patients with STEMI have different sociodemographic profiles th;an older patients with STEMI, one would postulate that the risk factors for readmissions in young patients would differ from that reported in the older patients with STEMI. We performed a contemporary nationwide study using the 2016 and 2017 Nationwide Readmissions Database to identify patterns of readmissions after STEMI in the young adult population. Our analysis of the Nationwide Readmissions Database revealed a total of 243,747 hospitalizations for STEMI between 2016 and 2017. Readmission rates demonstrated a steady increase from discharge, increasing to 7.8% at 30 days and 10.3% at 60 days before relatively plateauing at 12.1% at 90 days. Cardiovascular etiologies were the most common cause of readmission (53.6%). After multivariable analysis, development of cardiogenic shock (adjusted odds ratio 1.48, 95% confidence interval 1.11 to 1.97; p = 0.008) and acute renal failure (adjusted odds ratio 1.46, 95% confidence interval 1.14 to 1.87; p = 0.003) during the index admission were associated with significantly higher rates of readmission. In conclusion, close monitoring in young patients who presented with STEMI and concomitant with cardiogenic shock or acute renal failure, and possibly, aggressive therapy during index admission may be needed. However, this population may be heterogeneous and further research is needed.

Sex differences in glycemic measures, complications, discharge disposition, and postdischarge emergency room visits and readmission among non-critically ill, hospitalized patients with diabetes

INTRODUCTION

The purpose of this prospective observational cohort study was to examine sex differences in glycemic measures, diabetes-related complications, and rates of postdischarge emergency room (ER) visits and hospital readmissions in non-critically ill, hospitalized patients with diabetes.

RESEARCH DESIGN AND METHODS

Demographic data including age, body mass index, race, blood pressure, reason for admission, diabetes medications at admission and discharge, diabetes-related complications, laboratory data (hematocrit, creatinine, hemoglobin A1c, point-of-care blood glucose measures), length of stay (LOS), and discharge disposition were collected. Patients were followed for 90 days following hospital discharge to obtain information regarding ER visits and readmissions.

RESULTS

120 men and 100 women consented to participate in this study. There were no sex differences in patient demographics, diabetes duration or complications, or LOS. No differences were observed in the percentage of men and women with an ER visit or hospital readmission within 30 (39% vs 33%, p=0.40) or 90 (60% vs 49%, p=0.12) days of hospital discharge. More men than women experienced hypoglycemia prior to discharge (18% vs 8%, p=0.026). More women were discharged to skilled nursing facilities (p=0.007).

CONCLUSIONS

This study demonstrates that men and women hospitalized with an underlying diagnosis of diabetes have similar preadmission glycemic measures, diabetes duration, and prevalence of diabetes complications. More men experienced hypoglycemia prior to discharge. Women were less likely to be discharged to home. Approximately 50% of men and women had ER visits or readmissions within 90 days of hospital discharge.

TRIAL REGISTRATION NUMBER

NCT03279627.

Management of Dyslipidemia in Women and Men with Coronary Heart Disease: Results from POLASPIRE Study

Cardiovascular diseases (CVDs) are the leading cause of death in Poland. Starting from 1992, a gradual decrease in mortality due to CVDs has been observed, which is less noticeable in women. Following this notion, we assessed sex differences in the implementation of ESC recommendations regarding lipid control and the use of statins as part of secondary CVDs prevention in 1236 patients with acute coronary syndrome or elective coronary revascularization within the last 6-24 months. During hospitalization women had more frequently abnormal TC levels than men (p = 0.035), with overall higher TC levels (p = 0.009) and lower HDL-C levels (p = 0.035). In the oldest group, they also had more frequently elevated LDL-C levels (p = 0.033). Similar relationships were found during the follow-up visit. In addition, women less often achieved the secondary lipid therapeutic goal for non-HDL-C (p = 0.009). At discharge from hospital women were less frequently prescribed statins (p = 0.001), which included high-intensity statins (p = 0.002). At the follow-up visit the use of high-intensity statins was still less frequent in women (p = 0.02). We conclude that women generally have less optimal lipid profiles than men and are less likely to receive high-intensity statins. There is a need for more organized care focused on the management of risk factors.

Gender differences in the impact of frailty on 90-day hospital readmission in heart failure patients: a retrospective cohort study

AIMS

Frequent hospital readmissions after heart failure (HF) are common, however, there is limited data on the association between frailty status and hospital readmission in HF patients. This study aimed to examine the 90-day hospital readmission rates and gender differences in the impact of frailty on 90-day hospital readmission in HF patients.

METHODS AND RESULTS

We retrospectively analysed hospital discharge records of 279 patients (men = 169, women = 110) who were diagnosed with HF between January 2017 and December 2018. Frailty was assessed using the Korean version of the FRAIL scale. A logistic regression analysis was conducted to explore the factors predicting 90-day hospital readmission by gender. The prevalence of frailty and 90-day hospital readmissions were ∼54.4% and 22.7% in women, compared with 45.6% and 27.8% in men, respectively. Frail patients with HF have an increased risk of 90-day hospital readmission in both males and females. Particularly, women with frailty had a higher risk of 90-day hospital readmission [adjusted odds ratio (OR) 6.72, 95% confidence interval (CI) 1.41-32.09] than men with frailty (adjusted OR 4.40, 95% CI 1.73-11.17).

CONCLUSION

Our findings highlight that readmission within 90 days of hospitalization for HF can be predicted by patients' frailty. More importantly, we found that women with frailty have a greater risk of readmission than men with frailty. Screening for frailty should therefore be integrated into the assessment of HF patients. Tailored interventions for preventing adverse outcomes should consider gender-associated factors in HF patients with frailty.

Elucidating the Relationship Between Insomnia, Sex, and Cardiovascular Disease

Sex differences in cardiovascular disease (CVD) mortality have been attributed to differences in pathophysiology between men and women and to disparities in CVD management that disproportionately affect women compared to men. Similarly, there has been investigation of differences in the prevalence and presentation of insomnia attributable to sex. Few studies have examined how sex and insomnia interact to influence CVD outcomes, however. In this review, we summarize the literature on sex-specific differences in the prevalence and presentation of insomnia as well as existing research regarding the relationship between insomnia and CVD outcomes as it pertains to sex. Research to date indicate that women are more likely to have insomnia than men, and there appear to be differential associations in the relation between insomnia and CVD by sex. We posit potential mechanisms of the relationship between sex, insomnia and CVD, discuss gaps in the existing literature, and provide commentary on future research needed in this area. Unraveling the complex relations between sex, insomnia, and CVD may help to explain sex-specific differences in CVD, and identify sex-specific strategies for promotion of cardiovascular health. Throughout this review, terms “men” and “women” are used as they are in the source literature, which does not differentiate between sex and gender. The implications of this are also discussed.

Depression in Patients with Heart Diseases: Gender Differences and Association of Comorbidities, Optimism, and Spiritual Struggle

BACKGROUND

Depression is a well-established comorbidity of heart disease (HD) and is more prevalent in women than in men. Few studies have examined the gender effect on depression in patients with advanced heart disease prior to open heart surgery (OHS), controlling for cardiac indices. Previous studies indicated the health benefit of optimism but often lacked adjustment for medical confounders. This interdisciplinary study investigated gender differences in pre-OHS depression and the role of medical comorbidities and strength factors.

METHOD

Two waves of survey data were collected from 481 patients (mean age = 62, female 42%) along with medical indices in the Society of Thoracic Surgeon's (STS) national database used by all US cardiac surgeons.

RESULTS

A t test showed significantly higher levels of pre-OHS depressive symptoms in women than in men. In multivariate analyses, the gender effect on depression vanished after entry of other socio-demographics, medical comorbidities, objectively assessed cardiac indices in the STS database, and psychosocial strength factors. Depressive symptoms linked inversely with dispositional optimism and positively with medical comorbidities and religious/spiritual struggle, but not with any cardiac indices. A mediation analysis supported the role of comorbidities in the gender difference.

CONCLUSION

Women with heart disease were more depressed, but the gender difference may be partly explained by multiple comorbid conditions that could complicate disease burden. Reinforcing the literature, optimism, but not other strength factors, appeared to counteract depression after adjusting for health and cardiac conditions. The finding suggests that health providers should be more attentive to overall health of women with heart disease and to the positive expectations of OHS patients.

Sex differences in 30-day readmission rates, etiology, and predictors after transcatheter aortic valve replacement

BACKGROUND

The aim of this study is to analyze sex-specific readmission rates, etiology, and predictors of readmission after transcatheter aortic valve replacement (TAVR). Readmissions after TAVR are common, contributing to increased health care utilization and costs. Many factors have been discovered as predictors of readmission; however, sex-specific disparities in readmission rates are limited.

METHODS

Between January 2012 and September 2015, adult patients after TAVR were identified using appropriate international classifications of diseases, ninth revision, clinical modification from the National Readmission Database. Incidence of unplanned 30-days readmission rate was the primary outcome of this study. In addition, this study includes sex-specific etiology and predictors of readmissions. Multivariate logistic regression was performed to analyze adjusted readmission rates. Hierarchical 2-level logistic models were used to evaluate predictors of readmission.

RESULTS

Readmission rate at 30 days was 17.3%, with slightly higher readmission rates in women (OR 1.09; CI: 1.01-1.19, p < 0.001) after multivariate adjusted analysis. Noncardiac causes were responsible for most readmissions in both genders. Etiologies for readmissions such as arrhythmias, pulmonary complications, and infections were slightly higher in women, whereas heart failure and bleeding complications were higher in men. History of heart failure, atrial fibrillation, prior pacemaker, and renal failure significantly strongly predicted readmissions in both genders.

CONCLUSION

Women undergoing TAVR have slightly higher 30-day all-cause readmission rates. These results indicate that women require more attention compared to men to prevent 30-day readmission. In addition, risk stratification for men and women based on predictors will help identify high-risk men and women for readmissions.