Characterization of Patients Who Return to Hospital Following Discharge from Hospitalization For COVID-19

Abstract

Background: Data on patients with coronavirus disease 2019 (COVID-19) who return to hospital after discharge are scarce. Characterization of these patients may inform post-hospitalization care. Methods and Findings: Retrospective cohort study of patients with confirmed SARS-CoV-2 discharged alive from five hospitals in New York City with index hospitalization between February 27th-April 12th, 2020, with follow-up of ≥14 days. Significance was defined as P<0.05 after multiplying P by 125 study-wide comparisons. Of 2,864 discharged patients, 103 (3.6%) returned for emergency care after a median of 4.5 days, with 56 requiring inpatient readmission. The most common reason for return was respiratory distress (50%). Compared to patients who did not return, among those who returned there was a higher proportion of COPD (6.8% vs 2.9%) and hypertension (36% vs 22.1%). Patients who returned also had a shorter median length of stay (LOS) during index hospitalization (4.5 [2.9,9.1] vs. 6.7 [3.5, 11.5] days; Padjusted=0.006), and were less likely to have required intensive care on index hospitalization (5.8% vs 19%; Padjusted=0.001). A trend towards association between absence of in-hospital anticoagulation on index admission and return to hospital was also observed (20.9% vs 30.9%, Padjusted=0.064). On readmission, rates of intensive care and death were 5.8% and 3.6%, respectively. Conclusions: Return to hospital after admission for COVID-19 was infrequent within 14 days of discharge. The most common cause for return was respiratory distress. Patients who returned had higher proportion of COPD and hypertension with shorter LOS on index hospitalization, and a trend towards lower rates of in-hospital treatment-dose anticoagulation. Future studies should focus on whether these comorbid conditions, longer LOS and anticoagulation are associated with reduced readmissions.

Analysis of Risk Factors on Readmission Cases of COVID-19 in the Republic of Korea: Using Nationwide Health Claims Data

“…By gender, men were 1.340 times more likely to be readmitted due to COVID-19 than women. Somani S et al found that out of 103 readmitted patients, 65 were men, two times more than women [5], and a study by Lina Marcela Parra Ramírez et al on COVID-19 readmitted patients showed that more men were readmitted due to COVID-19 [19]. Previous studies found differences in the effects of COVID-19 by gender.…”

“…A recent study in Spain by Lina Marcela Parra Ramírez et al reported that the duration of symptom onset and the length of stay was shorter in the readmitted patient group [19]. This may suggest improper patient care after discharge [5] or hasty discharge before complete recovery [18].…”

“…A correlation between COVID-19 readmission and underlying diseases has already been demonstrated in other studies. A study in Switzerland that observed the characteristics of two readmitted patients reported that the patients had coronary artery disease, atrial fibrillation, and aortic stenosis as underlying diseases [29], and a recent study on patients readmitted with COVID-19 to five hospitals in New York City reported that the probability of readmission is higher in patients with hypertension and chronic obstructive pulmonary disease [5]. The finding that the rate of readmission is higher for patients with hypertension as the underlying disease was also confirmed in a study in Spain [19].…”

“…In addition, Xian et al found that 27 out of 285 hospitalized COVID-19 patients in Guangdong, China tested positive again after recovering [4]. In a study by Somani S et al that investigated 2864 COVID-19 patients admitted to five hospitals in New York, 103 patients (3.6%) tested positive again after discharge and were readmitted to the hospitals [5].…”

Privacy-Protecting, Reliable Response Data Discovery Using COVID-19 Patient Observations

“…Although efforts are underway to understand post-discharge outcomes in COVID-19 infected patients, to date they have been limited to case series ( 12 ), modest sample sizes ( 13 ), or single-center or geographically concentrated health systems ( 14 , 15 ). These extant studies may also be hampered by fixed inclusion/exclusion criteria ( 16 ).…”