36. Clinical Features of and Risk Factors for 30-day Readmission after an Initial Hospitalization with COVID-19

Abstract Background Little is known about risk factors for readmission after COVID-19 hospitalizations. Knowledge of these factors may help to identify patients at increased risk and may help to prevent these rehospitalizations. Methods This historical cohort study was conducted at a tertiary care academic medical center. We included COVID-19 cases diagnosed by reverse-transcriptase polymerase-chain-reaction (RT-PCR) assay between March 8th and June 14th, 2020. Patients readmitted within 30 days were identified. Using the electronic medical record, we collected data on demographic and clinical information. Data were analyzed using Student’s t-test, the chi-squared test and multivariable logistic regression. Results We included 391 patients who survived after the index hospitalization for COVID-19. The readmission rate was 13.3% (52/391). The mean time to readmission was 9.2 ± 7.9 days. The mean age (±SD) was 66.3 ± 18.6 years, 44.2% were male, and 78.8% were black/African-American. The most common presenting complaint was shortness of breath (50%). The most frequent diagnosis during the readmission was infectious process (57.7%). The mortality rate on readmission was 11.5%. Patients with a 30-day readmission were older than those not readmitted, mean age (±SD) 66.3 ± 18.6 vs. 61.0 ± 16.0, respectively (p=0.03). Readmitted patients also had a higher prevalence of heart failure and renal disease as comorbidities. Elevated alanine aminotransferase (AST) and low albumin level were also associated with readmission (Table 1). Intensive care unit (ICU) admission or mechanical ventilation during the index admission did not increase the risk of readmission. From multivariable analysis, independent predictors of 30-day readmission were higher Charlson score (p=0.004), higher creatinine on admission in the index hospitalization (p=0.009), and presence of rhabdomyolysis during the index hospitalization (p=0.039) (Table 2). Table 1. Univariable Analysis of Predictors for Readmission within 30 days from COVID-19 Infection Table 2. Multivariable Analysis of Predictors for Readmission within 30 days from COVID-19 Infection Conclusion In our cohort, infectious etiologies were common among those readmitted within 30 days of COVID-19. A higher Charlson score, acute renal failure, and rhabdomyolysis during the index admission were independent predictors of a 30-day readmission. Further studies are required to investigate these contributing factors. Disclosures All Authors: No reported disclosures

Blue line is after 3 months, orange line is after 6 months, green line is after 12 months, yellow line is healthy control. The p-value in the right-upper corner shows statistical significant difference between all total scores, the asterisks indicate significance between groups. PF = physical functioning; SF = social functioning; RP = role limitations-physical; RE = role limitations-emotional; MH = mental health; VT = vitality; BP = pain; GH = general health; HC = health change.

Figure 2
The blue column is after 3 months, the orange after 6 months and the green after 12 months. The numbers above the columns are percentages per group.

Figure 3
The blue column is after 3 months, the orange after 6 months and the green after 12 months. The numbers above the columns are percentages per group.
Conclusion. Although, COVID-19 may cause a decreased health-related quality of life and impaired mental health, this study shows important recovery up to normal levels after one year.
Disclosures. Background. Little is known about risk factors for readmission after COVID-19 hospitalizations. Knowledge of these factors may help to identify patients at increased risk and may help to prevent these rehospitalizations.
Methods. This historical cohort study was conducted at a tertiary care academic medical center. We included COVID-19 cases diagnosed by reverse-transcriptase polymerase-chain-reaction (RT-PCR) assay between March 8 th and June 14 th , 2020. Patients readmitted within 30 days were identified. Using the electronic medical record, we collected data on demographic and clinical information. Data were analyzed using Student's t-test, the chi-squared test and multivariable logistic regression.
Results. We included 391 patients who survived after the index hospitalization for COVID-19. The readmission rate was 13.3% (52/391). The mean time to readmission was 9.2 ± 7.9 days. The mean age (±SD) was 66.3 ± 18.6 years, 44.2% were male, and 78.8% were black/African-American. The most common presenting complaint was shortness of breath (50%). The most frequent diagnosis during the readmission was infectious process (57.7%). The mortality rate on readmission was 11.5%. Patients with a 30-day readmission were older than those not readmitted, mean age (±SD) 66.3 ± 18.6 vs. 61.0 ± 16.0, respectively (p=0.03). Readmitted patients also had a higher prevalence of heart failure and renal disease as comorbidities. Elevated alanine aminotransferase (AST) and low albumin level were also associated with readmission (Table 1). Intensive care unit (ICU) admission or mechanical ventilation during the index admission did not increase the risk of readmission. From multivariable analysis, independent predictors of 30-day readmission were higher Charlson score (p=0.004), higher creatinine on admission in the index hospitalization (p=0.009), and presence of rhabdomyolysis during the index hospitalization (p=0.039) ( Table 2).  Background. The impact of COVID-19 has been profound with >170,000,000 confirmed cases worldwide and emerging variants being a cause of global concern. Defects in T-cell function and trafficking have been described among those with severe illness, and immunodeficiency is a risk factor for persistent viral shedding and prolonged symptoms. Because of our prior clinical data demonstrating that allogeneic, off-the-shelf virus-specific T cells (VSTs) can safely and effectively treat viral infections, we investigated the feasibility of targeting COVID-19 using banked, SARS-CoV-2-specific VSTs.
Results. Using overlapping peptide libraries spanning these antigens as a stimulus, we achieved a mean 7.6±0.9 fold expansion (n=13) of VSTs (96±0.5%), with a mixture of cytotoxic (CD8+) and helper (CD4+) T cells that expressed activation and central/effector memory markers. These VSTs were potent, Th1-polarized and polyfunctional, producing IFNγ, TNFα, GM-CSF and Granzyme B. Moreover, the VSTs were able to kill pepmix-loaded autologous targets with no evidence of auto-or alloreactivity, attesting to their virus selectivity and safety for clinical use (Figure 1). Finally, though initially generated against the reference strain NC_045512.2 (Wuhan), these VSTs were able to recognize other clinically important variants including B1.1.7 (UK), B1.351 (South Africa) and P1 (Brazil). This demonstrates the cross-reactive potential of these polyclonal and diverse VSTs, which were developed to provide potent antiviral effects and minimize the risk of immune escape due to sequence variation.