In-hospital predictors of 60-day readmission in COVID-19 patients

Introduction

Preventing hospital readmissions can improve a patient's quality of life and decrease healthcare costs. While prior work has focused on pre-existing comorbidities to predict COVID-19 readmissions, the prognostic role of in-hospital data and complications has been less studied.

Methods

Data was collected on adult patients diagnosed with COVID-19 and admitted to a multicenter hospital system in Illinois between March and November 2020. Our cohort consisted of COVID-19 hospitalization survivors excluding those discharged to hospice care. Major adverse events (MAEs) were defined as venous thromboembolism (VTE), myocardial injury (troponin greater than upper limit of normal), stroke, new requirement for renal replacement therapy (RRT), life-threatening arrhythmia, or acute heart failure exacerbation. The primary outcome was readmission within 60 days of initial hospitalization.

Results

From the 1406 survivors of the index hospitalization, 223 (15.9%) patients were readmitted within 60 days. Those readmitted were older and more likely to have underlying comorbidities including atrial fibrillation, coronary artery disease, and hypertension (Table 1). Length of stay between the readmission and non-readmission groups was trending towards statistical significance (10.52 days vs 8.95 days, p=0.053).

Those with one or more MAE during their index hospitalization, when adjusted for age and body mass index, were at an increased risk of readmission (adjusted odds ratio [aOR] 1.90, p<0.01). Readmitted patients were more likely to have VTE during their index hospitalization than those not readmitted (7.2% vs 3.7%, p<0.05). The incidence of new RRT (4.9% vs 2.5%, p=0.083) and myocardial injury (3.6% vs 1.5%, p=0.067) between the groups was also trending towards statistical significance (Table 1). No statistical difference was present between the other individual MAEs; however, this is limited by small sample sizes of certain MAEs. Of the 322 patients with echocardiography during the index admission, 82 (25.5%) were readmitted. In this cohort, left ventricular ejection fraction (LVEF) that was reduced (LVEF <50%) or hyperdynamic (LVEF >65%) was not a statistically significant predictor of readmission (Figure 1).

Lastly, discharge disposition was predictive of readmission as those being sent to acute rehab (OR 2.04, p<0.01), long-term acute care (OR 2.58, p<0.01), or skilled nursing facility (OR 2.67, p<0.001) were at higher risk compared to those who were discharged to home (Figure 1).

Conclusion

In this cohort, the occurrence of any MAE during index COVID-19 hospitalization, particularly VTE, RRT, and myocardial injury, can be used to predict 60-day readmission. Furthermore, discharge disposition, but not LVEF, demonstrated prognostic value in our cohort. Identifying high risk patients prior to discharge helps health care providers focus resources on patients most likely to be readmitted.

Funding Acknowledgement

Type of funding sources: None.

Cardiac arrest in patients hospitalized for COVID-19: a tertiary medical center retrospective cohort study

Background/Introduction

Patients with COVID-19 are at increased risk for mortality during hospitalization. Better definition of the incidence, predictors, and outcomes of cardiac arrest during hospitalization for COVID-19 may support early identification and intervention.

Purpose

To estimate the incidence of in-hospital cardiac arrest in patients with COVID-19, describe the temporal trends in incidence of and survival after cardiac arrest, summarise characteristics of those who experienced a cardiac arrest, and compare the characteristics of survivors versus non-survivors of cardiac arrest.

Methods

We conducted a retrospective cohort study of patients admitted for COVID-19 to a tertiary medical center comprising three hospitals between March and November 2020. Data entry is ongoing for more than 2000 patients admitted through 2021. Clinical variables extracted via review of electronic medical records included age, sex, race/ethnicity, body mass index, history of cardiovascular disease (ie., coronary artery disease, congestive heart failure, atrial fibrillation, or cerebrovascular event), other comorbidities included in the Charlson comorbidity index, date of admission, duration of hospitalization, all cardiac arrest events during hospitalization, presenting rhythm during first cardiac arrest, and death. Data were described using summary statistics. Multivariable logistic regression was used to evaluate associations.

Results

Among 1666 patients, 107 (6.4%) experienced at least one in-hospital cardiac arrest event during hospitalization for COVID-19, of which 25 (23%) survived to hospital discharge. From March to October 2020, there was a decrease in estimated cardiac arrest incidence in-hospital from 8.2% to 3%, whereas estimated survival to hospital discharge after an arrest remained similar at approximately 20% (Figure). Compared to those who did not, patients who experienced in-hospital cardiac arrest were older and more likely to have existing cardiovascular disease, as well as other comorbidities. Similar factors were associated with lower chance of survival after cardiac arrest (Table). Patients with pulseless ventricular tachycardia/fibrillation (VT/VF) as presenting rhythm in cardiac arrest had better survival to hospital discharge compared to those with other rhythms (OR 3.3, p=0.02). Younger age (per 10 years, OR=0.7, p=0.03) and fewer comorbidities (per one fewer comorbidity, OR=1.5, p=0.05) were associated with better survival after cardiac arrest in multivariable logistic regression.

Conclusion

There was a decline in estimated incidence of cardiac arrest during hospitalization for COVID-19 since beginning of pandemic, with survival to hospital discharge after cardiac arrest estimated to be stable at around 20%. Younger age and fewer comorbidities especially cardiovascular disease were associated with better survival after an in-hospital cardiac arrest.

Funding Acknowledgement

Type of funding sources: Public hospital(s). Main funding source(s): Rush University Medical Center Figure 1Table 1