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

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 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.

Six-Month Post-Acute Sequelae of COVID-19: High Self-Reported Morbidity among Women and Younger Adults

Background. Long term sequelae across multiple medical domains, including the respiratory, psychiatric, and neurocognitive have been reported after COVID-19. Studies evaluating the impact of this symptom burden, however, are lacking. We aimed to describe the self-reported occurrence of symptoms and their effect on patient functioning six months after their acute hospitalization for COVID-19. Methods. From a historical cohort study of patients hospitalized for COVID-19 between March 8, and June 14, 2020, we identified patients discharged home. The purpose of the study was explained, and they were asked to consent to a telephone questionnaire. We used a modified version of a previously validated general symptom questionnaire (GSQ-30) to assess multi-system symptom burden. The Patient Health Questionnaire-2 (PHQ-2) was used to screen for major depression. Results. Of the original 565 patients, 258 patients were discharged home (45%). Of these, 57 (22%) patients were able to be contacted and agreed to participate in the survey. The mean (SD) age of the respondents was 55.1 (14.8) years, and 37 (64.9%) were female. The most common symptoms at follow-up were fatigue (60.0%), dyspnea (57.1%), feeling irritable, sad or decreased pleasure (56.4%), and memory difficulty (56.4%). Females had a significantly higher GSQ score (0.02) than males. Patients ages < 60 years tended to experience similar, if not greater, impaired functioning (p=0.07) compared with those ages ≥ 60 years (Table 1). Females were more likely to be irritable or sad (p=0.007), not feel rested on awakening (p=0.04), have shooting, stabbing and burning pain (p=0.02), have discomfort with normal light and sound (p=0.04), and have memory difficulty (p=0.04) than males (Table 2). Conclusion. Our study describes the clinical burden of post-acute sequelae of COVID-19 (PASC) in four core domains: fatigue, neurologic, neuro-psychiatric and viral-like symptoms. Over 45% of patients ages < 60 years suffered impaired functioning, compared with 21.1% of patient's ages 60 years and above. Females had significantly higher GSQ scores than men which strongly corelates with the functional impairment among the females. Larger studies are needed to further validate our findings.

Sex-Related Differences in Mortality from COVID-19: Survival Analysis of Patients from an Urban Hospital

Background. Mortality from COVID-19 is associated with male sex, older age, black race, and comorbidities including obesity. Our study identified risk factors for in-hospital mortality from COVID-19 using survival analysis at an urban center in Detroit, MI. Methods. This was a single-center historical cohort study. We reviewed the electronic medical records of patients positive for severe acute respiratory syndrome coronavirus 2 (the COVID-19 virus) on qualitative polymerase-chain-reaction assay, who were admitted between 3/8-6/14/20. We assessed risk factors for mortality using Kaplan-Meier analysis and Cox proportional hazards models. Results. We included 565 patients with mean age (standard deviation) 64.4 (16.2) years, 52.0% male (294) and 77.2% (436) black/African American. The overall mean body mass index (BMI) was 32.0 (9.02) kg/m2. At least one comorbidity was present in 95.2% (538) of patients. The overall case-fatality rate was 30.4% (172/565). The unadjusted mortality rate among males was 33.7% compared to 26.9% in females (p=0.08);the median time to death (range) for males was 16.8 (0.3, 33.9) compared to 14.2 (0.32, 47.7) days for females (p=0.04). Univariable survival analysis with Cox proportional hazards models revealed that age (p=< 0.0001), admission from a facility (p=0.002), public insurance (p< 0.0001), respiratory rate ≥ 22 bpm (p=0.02), lymphocytopenia (p=0.07) and serum albumin (p=0.007) were additional risk factors for mortality (Table 1). From multivariable Cox proportional hazards modeling (Table 2), after controlling for age, Charlson score and qSofa, males were 40% more likely to die than females (p=0.03). Conclusion. After controlling for risk factors for mortality including age, comorbidity and sepsis-related organ failure assessment, males continued to have a higher hazard of death. These demographic and clinical factors may help healthcare providers identify risk factors from COVID-19.