Impact of cardiac- and noncardiac-related conditions on adverse outcomes in patients hospitalized with acute myocardial infarction

The Association of Health Literacy With the Quality of Discharge Planning and Readiness for Hospital Discharge in Jordanian Acute Myocardial Infarction Patients

AIM

To examine the relationship between health literacy with the quality of discharge planning and readiness for hospital discharge in acute myocardial infarction patients in Jordan.

BACKGROUND

Acute myocardial infarction is a major heart disease caused by plaque formation in coronary arteries. Complications after acute myocardial infarction include readmission and physical complications such as chest pain, and limited health literacy increases the risk of complications. Improving the health literacy of patients can improve postdischarge outcomes and decrease complications.

METHODS

This study was conducted using a cross-sectional design. Data were collected from 123 patients who were recruited from three hospitals in Jordan. A demographics questionnaire and three valid and reliable instruments (Health Literacy Questionnaire, Readiness for Hospital Discharge Scale and Quality of Discharge Teaching Scale) were used to collect the data. The authors adhered to the STROBE checklist during the preparation of this study.

RESULTS

The results demonstrated that the Readiness for Hospital Discharge had weak to moderate positive correlations with health literacy scales (r = 0.24-0.36, p < 0.05). The content subscale of the Quality of Discharge Teaching Scale showed weak positive correlations with navigating the healthcare system, finding good health information and understanding health information scales of the Health Literacy Questionnaire.

CONCLUSION

The results reported here indicate that health literacy positively correlates with readiness for hospital discharge and quality of discharge teaching.

RELEVANCE TO CLINICAL PRACTICE

Improving the health literacy of acute myocardial infarction patients can enhance their discharge planning outcomes. The findings of this study are beneficial for healthcare providers in designing targeted interventions that correspond to health literacy among acute myocardial infarction patients.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

Combined use of the GRACE ACS risk score and comorbidity indices to increase the effectiveness of hospital mortality risk assessment in patients with acute coronary syndrome

Aim. To assess the possibilities of using comorbidity indices together with the GRACE (Global Registry of Acute Coronary Events) scale to assess the risk of hospital mortality in acute coronary syndrome (ACS). Materials and methods. The registry study included 2,305 patients with ACS. The frequency of coronary angiography was 54.0%, percutaneous coronary intervention (PCI) 26.9%. Hospital mortality with ACS was 4.8%, with myocardial infarction 9.4%. All patients underwent a comorbidity assessment according to the CIRS system (Cumulative Illness Rating Scale), according to the CCI (Charlson Comorbidity Index) and the CDS (Chronic Disease Score) scale, according to their own scale, which is based on the summation of 9 diseases (diabetes mellitus, atrial fibrillation, stroke, arterial hypertension, obesity, peripheral atherosclerosis, thrombocytopenia, anemia, chronic kidney disease). All patients underwent a mortality risk assessment using the GRACE ACS Risk scale. Results. It was found that the CDS and CIRS indices are not associated with the risk of hospital mortality. With CCI3, the frequency of death outcomes increased from 4.1 to 6.1% (2=4.12, p=0.042). With an increase in the severity of comorbidity from minimal (no more than 1 disease) to severe (4 or more diseases) according to its own scale, hospital mortality increased from 1.2 to 7.4% (2=23.8, p0.0001). In contrast to other scales of comorbidity, our own model more efficiently estimates the hospital prognosis both in the conservative treatment group (2=8.0, p=0.018) and in the PCI group (2=28.5, p=0.00001). It was in the PCI subgroup that the comorbidity factors included in their own model made it possible to increase the area under the ROC curve of the GRACE scale from 0.80 (0.740.87) to 0.90 (0.850.95). Conclusion. CCI and its own comorbidity model, but not CDS and CIRS, are associated with the risk of hospital mortality. The model for assessing comorbidity on a 9-point scale, but not CCI, CDS and CIRS, can significantly improve the predictive value of the GRACE scale.

Impact of diabetes on long-term all-cause re-hospitalization after revascularization with percutaneous coronary intervention

PURPOSE

The purpose of the study was to investigate the incidence, cause and probability of re-hospitalization within 30 and 365 days after percutaneous coronary intervention (PCI) in patients with diabetes.

METHOD

Between January 2010 and September 2014, 2763 patients with diabetes were treated with PCI at two Hospitals in Western Denmark. Reasons for readmission within 30 and 365 days were identified.

RESULTS

Readmission risks for patients with diabetes were 58% within 365 days and 18% within 30 days. Reason for readmission was ischemic heart disease (IHD) in 725 patients (27%), and non-IHD-related reasons in 826 patients (31%). IHD-related readmission within 365 days was associated with female gender (OR 1.3, 95% CI: 1.1-1.5), and non-ST-segment elevation myocardial infarction, compared to stable angina at the index hospitalization (OR 1.3, 95% CI: 1.1-1.6). Among patients with diabetes, increased risk of readmission due to other reasons were age (OR 1.3, 95% CI: 1.2-1.5) and higher scores of modified Charlson Comorbidity index (CCI): CCI ≥3 (OR 3.6, 95% CI: 2.8-4.6).

CONCLUSION

More than half of the patients with diabetes mellitus undergoing PCI were readmitted within 1 year. Comorbidities were the strongest predictor for non-IHD-related readmission, but did not increase the risk for IHD-related readmissions.

Management and outcomes of acute myocardial infarction in patients with pre-existing heart failure: an analysis of 2 million patients from the national inpatient sample

BACKGROUND

Inpatient management and outcomes of patients presenting with acute myocardial infarction (AMI) with a history of heart failure (HF) have not been well characterized.

METHODS

: Hospitalizations for AMI from the Nationwide Inpatient Sample (2015-2018) were categorized according to a pre-existing diagnosis of HF with preserved ejection fraction (HFpEF), reduced ejection fraction (HFrEF), or absence of HF. Utilization of invasive management and in-hospital outcomes were analyzed.

RESULTS

: Among 2,434,639 hospitalizations with an AMI, 19.8% had a history of HFrEF and 11.9% had a history of HFpEF. Coronary angiography and PCI respectively were performed significantly less among patients with HF (36.6% and 17.4% in HFpEF, 51.1% and 24.6% in HFrEF, and 64.4% and 42.3% among patients without HF, all p<0.0001). Mortality was more common among patients with HFrEF (10.3%) and HFpEF (8.3%) when compared to patients without a history of HF (6.4%), p<0.0001. In multivariable analyses compared to patients without HF, mortality was higher among patients with HFrEF (aOR 1.27, CI 1.26-1.29, p<0.0001) but not different among patients with HFpEF.

CONCLUSION

HF is a common pre-existing comorbidity among patients presenting with AMI and is associated with lower utilization of invasive procedures and higher complications including mortality, particularly among those with HFrEF.

Multimorbidity in Patients With Acute Coronary Syndrome Is Associated With Greater Mortality, Higher Readmission Rates, and Increased Length of Stay: A Systematic Review

OBJECTIVE

The aims of this systematic review were to determine the magnitude and impact of multimorbidity (≥2 chronic conditions) on mortality, length of stay, and rates of coronary intervention in patients with acute coronary syndrome (ACS) and to compare the prevalence of cardiovascular versus noncardiovascular multimorbidities.

METHODS

MEDLINE, PubMed, MedlinePlus, EMBASE, OVID, and CINAHL databases were searched for studies published between 2009 and 2019. Eight original studies enrolling patients with ACS and assessing cardiovascular and noncardiovascular comorbid conditions met the inclusion criteria. Study quality was evaluated using the Crowe Critical Appraisal Tool.

RESULTS

The most frequently examined cardiovascular multimorbidities included hypertension, diabetes, heart failure, atrial fibrillation, stroke/transient ischemic attack, coronary heart disease, and peripheral vascular disease; the most frequently examined noncardiovascular multimorbidities included cancer, anemia, chronic obstructive pulmonary disease, renal disease, liver disease, and depression. The prevalence of multimorbidity in the population with ACS is high (25%-95%). Patients with multimorbidities receive fewer evidence-based treatments, including coronary intervention and high-dose statins. Patients with multimorbidities experience higher in-hospital mortality (5%-13.9% vs 2.6%-6.1%), greater average length of stay (5-9 vs 3-4 days), and lower rates of revascularization (9%-14% vs 39%-42%) than nonmultimorbid patients. Women, despite being the minority in all sample populations, exhibited greater levels of multimorbidity than men.

CONCLUSIONS

Multimorbid patients with ACS are at a greater risk for worse outcomes than their nonmultimorbid counterparts. Lack of consistent measurement makes interpretation of the impact of multimorbidity challenging and emphasizes the need for more research on multimorbidity's effects on postdischarge healthcare utilization.

Multimorbidity phenotypes in patients presenting to the emergency department with possible acute coronary syndrome

BACKGROUND

Multimorbidity (> 2 conditions) increases the risk of adverse outcomes and challenges health care systems for patients with acute coronary syndrome (ACS). These complications may be partially attributed to ACS clinical care which is driven by single-disease-based practice guidelines; current guidelines do not consider multimorbidity.

OBJECTIVES

To identify multimorbidity phenotypes (combinations of conditions) with suspected ACS. We hypothesized that: 1) subgroups of patients with similar multimorbidity phenotypes could be identified, 2) classes would differ according to diagnosis, and 3) class membership would differ by sex, age, functional status, family history, and discharge diagnosis.

METHODS

This was a secondary analysis of data from a large multi-site clinical study of patients with suspected ACS. Conditions were determined by items on the Charlson Comorbidity Index and the ACS Patient Information Questionnaire. Latent class analysis was used to identify phenotypes.

RESULTS

The sample (n = 935) was predominantly male (68%) and middle-aged (mean= 59 years). Four multimorbidity phenotypes were identified: 1) high multimorbidity (Class 1) included hyperlipidemia, hypertension (HTN), obesity, diabetes, and respiratory disorders (COPD or asthma); 2) low multimorbidity (Class 2) included only obesity; 3) cardiovascular multimorbidity (Class 3) included HTN, hyperlipidemia, and coronary heart disease; and 4) cardio-oncology multimorbidity (Class 4) included HTN, hyperlipidemia, and cancer. Patients ruled-in for ACS primarily clustered in Classes 3 and 4 (OR 2.82, 95% CI 1.95-4.05, p = 0.001 and OR 1.76, 95% CI 1.13-2.74, p = 0.01).

CONCLUSION

Identifying and understanding multimorbidity phenotypes may assist with risk-stratification and better triage of high-risk patients in the emergency department.

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.