Health-related quality of life and readmission of patients with cardiovascular disease in South Korea

High risk of rehospitalization within 1 year following a pulmonary embolism-insights from the Danish nationwide registries from 2000-2020

AIM

To identify the absolute risk, causes, and factors associated with rehospitalization within 1 year of discharge with a pulmonary embolism (PE).

METHODS AND RESULTS

Using the Danish nationwide registries, all patients admitted with a first-time PE between 2000 and 2020 and discharged alive were included. Subsequent hospitalizations were categorized and crude cumulative incidences were used to estimate the absolute risk (AR) of any rehospitalization and specific causes of rehospitalizations. Risk factors for rehospitalization were investigated using cause specific Cox regression models.A total of 55 201 patients were identified. The median age of the study population was 70 years (inter quartile range: 59;79), and the most prevalent comorbidities were cancer (29.3%) and ischemic heart disease (12.7%). The 1-year AR of any rehospitalization after discharge with a PE was 48.6% (95% confidence interval (CI); 48.2%-48.8%). The most common cause for being rehospitalized was due to respiratory disease [1-year AR: 9.5% (95% CI: 9.3%-9.8%)], followed by cardiovascular disease [1-year AR: 6.3% (95% CI: 5.9%-6.5%)], cancer [1-year AR: 6.0% (95% CI: 5.8%-6.4%)], venous thromboembolism [1-year AR: 5.2% (95% CI: 5.0%-5.2%)], and symptom diagnoses [1-year AR: 5.2% (95% CI: 5.0%-5.4%)]. Factors that were associated with an increased risk of rehospitalization were cancer, liver disease, chronic obstructive pulmonary disease, chronic kidney disease, and immobilization.

CONCLUSION

Patients with PE have a high risk of rehospitalization, with almost half of patients being rehospitalized within 1 year. Identification of high-risk patients may help target interventions aiming at reducing the risk of rehospitalization.

Effectiveness of the triglyceride-glucose index and triglyceride-glucose-related indices in predicting cardiovascular disease in middle-aged and older adults: A prospective cohort study

BACKGROUNDS

Cardiovascular disease (CVD) risk assessment is a crucial component of public health. We aimed to determine the predictive value of the triglyceride-glucose (TyG) index and TyG-related indices for new-onset CVD.

METHODS

This prospective study included 7,808 participants aged 40-69 years from the Ansung-Ansan cohort database. Our analysis was stratified by diabetes status. The hazard ratio (HR) with a 95% confidence interval (CI) for incident CVD was computed using multiple Cox proportional-hazards regression models. To evaluate the predictive performance of these indices for new-onset CVD, we calculated the Harrell's C-index (95% CI).

RESULTS

In this study, a total of 6,890 participants did not have diabetes at baseline, while 918 participants had diabetes. In participants without diabetes, compared to the lowest tertile, fully adjusted HR and 95% CI for new-onset CVD in the highest tertile were as follows: TyG (HR 1.42, 95% CI 1.06-1.90), TyG-body mass index (BMI) (HR 1.92, 95% CI 1.19-3.10), TyG-waist circumference (WC) (HR 2.37, 95% CI 1.61-3.49), and TyG-waist-to-height ratio (WHtR) (HR 2.20, 95% CI 1.47-3.28). However, no significant associations were observed between TyG, modified TyG indices, and new-onset CVD in participants with diabetes. Notably, the C-indice of TyG-WC and TyG-WHtR were significantly higher than those of TyG and TyG-BMI in participants without diabetes.

CONCLUSIONS

TyG-BMI, TyG-WC, and TyG-WHtR were associated with an increased risk of new-onset CVD in participants without diabetes. Furthermore, TyG-WC and TyG-WHtR showed better predictive performances for new-onset CVD than TyG and TyG-BMI in participants without diabetes.

The Effect of a Healthcare Services Hotline on Quality of Life and Hospital Readmissions for Patients with Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is a common debilitating disease marked by frequent exacerbations and hospitalizations, economic burden, and reduced quality of life. This study aimed to determine the effect of a healthcare hotline on quality of life and hospital readmissions within 30 days of discharge for patients with COPD. Sixty patients with COPD who needed home healthcare services were recruited for this quasi-experimental study. A direct hotline was provided to patients and their caregivers in the intervention group to answer their questions about the disease. Data were collected using a demographics checklist, and St. George Respiratory Questionnaire. The number of hospitalizations and mean length of hospital stay in the intervention group within 30 days was significantly lower than the control group (p < 0.05). As for quality of life, only the mean score of symptoms was significantly different between the intervention and control groups (p < 0.05). The results showed the positive effect of a healthcare hotline on reducing readmission rates within 30 days of discharge and its low effect on quality of life of COPD patients.

LACE Index to Predict the High Risk of 30-Day Readmission in Patients With Acute Myocardial Infarction at a University Affiliated Hospital

Background

The LACE index (length of stay, acuity of admission, comorbidity index, and emergency room visit in the past 6 months) has been used to predict the risk of 30-day readmission after hospital discharge in both medical and surgical patients. This study aimed to utilize the LACE index to predict the risk of 30-day readmission in hospitalized patients with acute myocardial infraction (AMI).

Methods

This was a retrospective study. Data were extracted from the hospital's electronic medical records of patients admitted with AMI between 2015 and 2019. LACE index was built on admission patient demographic data, and clinical and laboratory findings during the index of admission. The multivariate logistic regression was performed to determine the association and the risk prediction ability of the LACE index, and 30-day readmission were analyzed by receiver operator characteristic curves with C-statistic.

Results

Of the 3,607 patients included in the study, 5.7% (205) were readmitted within 30 days of discharge from the hospital. The adjusted odds ratio based on logistic regression of all baseline variables showed a statistically significant association with the LACE score and revealed an increased risk of readmission within 30 days of hospital discharge. However, patients with high LACE scores (≥10) had a significantly higher rate of emergency revisits within 30 days from the index discharge than those with low LACE scores. Despite this, analysis of the receiver operating characteristic curve indicated that the LACE index had favorable discrimination ability C-statistic 0.78 (95%CI; 0.75–0.81). The Hosmer–Lemeshow goodness- of-fit test P value was p = 0.920, indicating that the model was well-calibrated to predict risk of the 30-day readmission.

Conclusion

The LACE index demonstrated the good discrimination power to predict the risk of 30-day readmissions for hospitalized patients with AMI. These results can help clinicians to predict the risk of 30-day readmission at the early stage of hospitalization and pay attention during the care of high-risk patients. Future work is to be focused on additional factors to predict the risk of 30-day readmissions; they should be considered to improve the model performance of the LACE index with other acute conditions by using administrative data.

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.