Infection https://doi.org/10.1007/s15010-021-01662-1 ORIGINAL PAPER Incidence and risk factors for early readmission after hospitalization for SARS‑CoV‑2 infection: results from a retrospective cohort study Cristina Kirkegaard1 · Anna Falcó‑Roget1 · Adrián Sánchez‑Montalvá1,2 · Ángel Valls3 · David Clofent4 · Isabel Campos‑Varela5 · Sonia García‑García6 · Lina María Leguízamo7 · Júlia Sellarès‑Nadal1 · Simeon Eremiev1 · Miguel Villamarín1 · Blanca Marzo1 · Benito Almirante1,8 · Òscar Len1,8 Received: 10 May 2021 / Accepted: 5 July 2021 © Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract Purpose We aim to assess risk factors related to early readmission in previous hospitalized patients with COVID-19. Methods We analyzed a retrospective cohort of patients with laboratory-confirmed COVID-19 admitted to Vall d’Hebron University Hospital, Barcelona, Spain. Early readmission was defined as the need for hospitalization within a period of 60 days after discharge. A descriptive analysis of the readmission was performed, including hospitalization outcome. We also performed a multivariate logistic regression to define risk factors for readmission Results A total of 629 patients were followed up during 60 days with a readmission cumulative incidence of 5.4% (34 out of 629) and an incidence rate of 0.034 person-years. Main reasons for readmission were respiratory worsening (13, 38.2%), decompensation of previous disease (12, 35.3%) or infectious complications (6, 17.6%). Median time to readmission was 12 days (interquartile range 7–33 days). Prior diagnosis of heart failure (OR 4.09; 95% CI 1.35–12.46; p = 0.013), length of stay during index admission greater than 13 days (OR 2.72; 95% CI 1.21–6.12; p = 0.015), treatment with corticosteroids (OR 2.39; 95% CI 1.01–5.70; p = 0.049) and developing pulmonary thromboembolism (OR 11.59; 95% CI 2.89–46.48; p = 0.001) were the risk factors statistically associated with early readmission. Conclusion Readmission cumulative incidence was 5.4%. Those patients with prior diagnosis of heart failure, length of stay greater than 13 days, treated with corticosteroids or who developed pulmonary thromboembolism might benefit from close monitoring after being discharged. Keywords SARS-CoV-2 · Readmission · Risk factors Cristina Kirkegaard and Anna Falcó-Roget authors contributed equally to the work. 5 * Òscar Len Internal Medicine‑Hepatology Department, University oscar.len@vhir.org Hospital Vall d’Hebron, Universitat Autónoma de Barcelona, Barcelona, Spain 1 Infectious Diseases Department, University Hospital Vall 6 Pharmacy Department, University Hospital Vall d’Hebron, d’Hebron, Universitat Autónoma de Barcelona, Barcelona, Universitat Autónoma de Barcelona, Barcelona, Spain Spain 7 2 Clinical Pharmacology Department, University Hospital Vall Programa de Salut Internacional de Catalunya del Institut d’Hebron, Universitat Autónoma de Barcelona, Barcelona, Català de la Salut (PROSICS), Barcelona, Spain Spain 3 Internal Medicine Department, University Hospital Vall 8 Spanish Network for the Study of Infectious Diseases d’Hebron, Universitat Autónoma de Barcelona, Barcelona, (REIPI), Barcelona, Spain Spain 4 Pneumology Department, University Hospital Vall d’Hebron, Universitat Autónoma de Barcelona, Barcelona, Spain 13 Vol.:(0123456789) C. Kirkegaard et al. Introduction Study objectives The ongoing coronavirus disease pandemic (COVID-19) The primary objective was to determine the risk factors caused by severe acute respiratory syndrome coronavirus associated with the readmission. Secondary objectives were 2 (SARS-CoV-2) was first described in Wuhan, China, and establishing the cumulative incidence and defining the rea- rapidly progressed worldwide affecting more than 179 mil- sons for readmission. lion people and causing more than 3.8 million deaths [1]. The spectrum of this disease goes from asymptomatic patients to severe pneumonia. In this last group, some Data collection patients develop rapidly progressing respiratory failure and acute respiratory distress syndrome (ARDS), multi-organ Data were collected in a dedicated web-based individual and systemic manifestations and/or complications during password-protected database with real-time data quality hospitalization, such as heart failure, acute kidney failure, rules and data traceability system hosted in REdCAP. The liver dysfunction, deep vein thrombosis, pulmonary throm- following information was retrieved from the database: boembolism (PTE), superinfection, arrhythmia or stroke [2, demographic characteristics, baseline diseases and past 3]. medical history (arterial hypertension, diabetes mellitus, Previous researches have analyzed the data of COVID-19 chronic kidney disease, pulmonary disease, liver disease, patients to describe risk factors of mortality. Older age, high heart failure, history of cancer, autoimmune disease, immu- number of comorbidities, higher levels of acute-phase reac- nosuppression, hematologic disease and obesity), Charlson tants, such as C-reactive protein (CRP), procalcitonin (PCT) Comorbidity Index and analytical, clinical, microbiological and D-dimer, were associated with more severity of infection and radiological data from the acute infection and its evolu- [4–6]. Unfortunately, limited studies have paid attention to tion. Readmission information was collected retrospectively the risk factors related to readmission after being discharged from the electronic health record system of the patients. [7–11]. In this context, we aim to describe the characteristics of hospitalized patients with COVID-19 pneumonia who were Definitions readmitted early after discharge and determine risk factors of readmission. Early readmission was determined as the need for hospi- talization by any cause within a period of 60 days after the initial COVID-19 episode. Readmission was assessed in the Methods network of public hospitals of the Catalan Institute of Health and the private hospitals of the metropolitan area of Barce- Study setting and population lona. Readmissions occurring in others outside Catalonia were missed. Those patients who only attended the emer- The Vall d’Hebron COVID-19 Cohort Study includes all gency department were excluded. Patients lost to follow-up consecutive adult patients (≥ 18 years old) admitted for were those who did not have contact with any health facility COVID-19 at Vall d’Hebron University Hospital, Barcelona, for 60 days or more after being discharged. Spain. Between March 1, 2020 and May 31, 2020, data were Treatment with corticoids was defined as a dose greater collected from 870 patients. The presence of SARS-CoV-2 than 0.5 mg/kg per day of prednisone (or equivalent) for was determined by RT-PCR performed on any respiratory at least 3 days during admission. Regarding complica- sample (nasopharyngeal swab, sputum, bronchoalveolar lav- tions, ARDS was defined as an acute beginning and a age or aspirate, tracheal aspirate). P/F ratio < 200 or SF ratio < 235 (equals the arterial ­pO2 The standard of care in our hospital consisted of the first or oxygen saturation, respectively, divided by the fraction wave of lopinavir/ritonavir or darunavir/cobicistat accord- of inspired oxygen expressed as a decimal) with bilateral ing to underlying diseases and tolerance, hydroxychloro- infiltrates in the chest radiography and clinical evidence of quine and azithromycin. At the beginning, azithromycin left auricular hypertension. Respiratory failure was defined was administered as an antibiotic but later it was used as as a p­ O2 < 60 mmHg, an oxygen saturation < 90%, a P/F an immunomodulatory agent. Antimicrobial prescription ratio < 300 or a SF ratio < 315. Septic shock was designated depended on clinician criteria. as a need of vasoactive drugs to maintain a mean arte- rial pressure greater than 65 mmHg and hyperlactatemia (> 2 mmol/L) in absence of hypovolemia. Acute renal failure was characterized as an increase in serum creatinine by ≥ 1.5 times baseline or a fall of 25% of glomerular filtration rate 13 Incidence and risk factors for early readmission after hospitalization for SARS-CoV-2… and liver dysfunction referred to an absolute increase in serum transaminases by ≥ 3 times baseline or gamma-glu- tamyl transferase (GGT) and alkaline phosphatase (ALP) by ≥ 5. Finally, a secondary infection was described as another infection different from SARS-CoV-2. Statistical analysis Continuous variables are presented as mean and standard deviation while those variables that do not follow a normal distribution are presented as median and interquartile range. Both were compared using Student’s t test or Mann–Whitney U Test, respectively. Categorical variables are presented as N and percentage (%) and were compared using Chi-square or Fisher’s exact test. Receiver operating characteristic curve (ROC) analysis was performed to determine cut-off values for continuous variables. Fig. 1  Study cohort and patients’ selection Uni- and multivariate odds ratios (OR) were calculated using multiple logistic regression analysis to identify risk factors. Variables showing statistically significant differ- Patients’ baseline characteristics ences between patients with or without readmission in the univariate analysis were then tested in multivariate models. The mean age of patients was approximately 60 years and Models were performed in a sequential fashion beginning 50.6% were male. The main comorbidities were arterial with the variable most strongly associated with readmission. hypertension (40.4%), obesity (18.6%), diabetes (18.1%) In addition, clinically relevant factors with p values < 0.1 and pulmonary disease (17%). The main epidemiological that were considered to be potential confounders based on and clinical data of included patients are shown in Table 2. experience and data in the literature were forced into the Among patients’ characteristics, male gender (p = 0.040) multivariate model to investigate their effect. and both smoking (p = 0.013) and alcohol abuse (p = 0.004) The threshold of statistical significance was p ≤ 0.05. The were significantly different among groups. Readmitted statistical analysis was performed using IBM SPSS Statis- patients were also more likely to have a previous diagnosis tics for Windows, Version 25.0. Armonk, NY: IBM Corp. of cancer (p = 0.025), heart failure (p = 0.001) and Charlson Released 2017. Comorbidity Index greater than 3 (CCI; p = 0.003). Finally, the median length of stay during index admis- sion was 9 days. An increased length of stay was observed Results in those patients who required re-hospitalization (20 days versus 9 days, p < 0.001). Patients Laboratory and radiological characteristics Flow diagram for patient selection is shown in Fig. 1. The readmission cumulative incidence was 5.4%. Among Laboratory and radiological findings are detailed in Tables 3 readmitted patients, one patient died during the second and 4, respectively. hospitalization episode. The median time for readmission Readmitted patients were more likely to present lower was 12 days (IQR 7–33 days) with half of the 60-day read- absolute lymphocyte count (p = 0.014) and higher levels of missions occurring within 2 weeks of discharge. Thirteen d-dimer (p = 0.014). No other statistically significant differ- out of 34 (38.2%) were secondary to respiratory worsen- ences were found amongst the other variables. ing, 12 patients (35.3%) related to a decompensation of a Radiological abnormalities were seen in 534 hospitalized known underlying disease, and six (17.6%) due to infectious patients (84.9%) and included the presence of focal con- complications. Three patients were readmitted because of solidation, ground glass opacities, pleural effusion and/other pregnancy related events, one was a post-cesarean wound abnormalities. Readmitted patients had a lower percentage complication, and the other two were not considered a com- (57.9%) than that of non-readmitted patients (86.6%) regard- plication of acute COVID-19 (one term labor, one hyperem- ing pulmonary affectation (p < 0.001). We distinguished esis). Diagnosis made during the readmission and days until between unilateral or bilateral affectation; we found no sig- readmission are detailed in Table 1 and Fig. 2. nificant difference between the two groups. On the other 13 C. Kirkegaard et al. Table 1  Diagnosis of Cases Diagnosis (days until readmission) readmitted patients and days until readmission after Related with pregnancy 3 (8.8) 1 Hyperemesis gravidarum (2) hospitalization for SARS-CoV-2 1 Term labor (48) infection 1 Surgical wound dehiscence post-cesarean Section (7) Respiratory worsening 13 (38.2) 3 Pulmonary thromboembolism (3, 7, 7) 1 Organizing pneumonia (17) 4 Hypoxic respiratory failure (2, 1, 1, 4) 1 Tracheal granuloma after endotracheal intubation (44) 1 Acute pleuropericarditis (14) 2 Thoracic pain (18, 8) 1 Self-limited febrile syndrome (9) Decompensation of an underlying 2 Cirrhosis decompensation (49, 35) disease 12 (35.3) 2 Bile duct pathology (9, 39) 1 Bronchoaspiration due to dysphagia (60) 4 Acute heart failure (4, 21, 39, 8) 1 Percutaneous endoscopic gastrostomy dysfunction (11) 1 Esophageal stent migration (19) 1 Pacemaker mediated atrial tachycardia (13) Infectious complications 6 (17.6) 2 Infection caused by Clostridiodes difficile (25, 32) 1 Fever due to teicoplanin (11) 1 Acute appendicitis (10) 1 Herpetic stomatitis (18) 1 Pneumonia caused by Pseudomonas aeruginosa (25) *Data are expressed as numbers and percentages unless otherwise indicated Fig. 2  Reasons and timing of 60-day readmission in patients discharged from a tertiary hos- pital in Barcelona. 52.9% were readmitted within 10 days after discharge hand, more patients presented with radiological affectation patients who received corticosteroids during their first greater than 33% in the readmitted group (11/22, 50% versus admission (p = 0.001). Patients with higher levels of IL-6 140/512, 27.3%; p = 0.007). (greater than 40 pg/L) could receive tocilizumab as a res- cue treatment. Although these patients had higher rates of Treatment readmission (26.5% versus 17.1%), there were no statisti- cally significant differences between both groups. The treatment administered to patients is detailed in Table 5. Non-readmitted patients received prophylactic anti- Seventy-two patients (11.4%) received corticosteroids coagulation in higher percentages than that of readmitted during hospitalization and ten were readmitted (29.4%). patients (69.9% versus 48.5%, p < 0.001). Prophylactic Higher readmission rates were observed among those 13 Incidence and risk factors for early readmission after hospitalization for SARS-CoV-2… Table 2  Epidemiological and Global (N = 629) Readmitted (N = 34) Non-readmit- P value clinical data from patients ted (N = 595) discharged after hospitalization for SARS-CoV-2 infection Age (mean ± SD) 60.28 ± 17.37 62.59 ± 20.23 60.42 ± 17.2 0.479 Male 318 (50.6) 23 (67.6) 295 (49.6) 0.040 Sometime smoker 163 (25.9) 15 (44.1) 148 (24.9) 0.013 Sometime drinker 29 (4.6) 5 (14.7) 24 (4.0) 0.004 Diabetes 114 (18.1) 10 (29.4) 104 (17.5) 0.079 Immunosuppression 53 (8.4) 5 (14.7) 48 (8.1) 0.175 Autoimmune disease 6 (1) 0 (0) 6 (1) 1.000 Cancer diagnosis 60 (9.6) 7 (20.6) 53 (8.9) 0.025 Hematologic disease 24 (3.8) 1 (2.9) 23 (3.9) 1.000 Arterial hypertension 254 (40.4) 16 (47.1) 238 (40) 0.415 Heart-failure 26 (4.1) 5 (14.7) 21 (3.5) 0.001 Asthma 31 (4.9) 3 (8.8) 28 (4.7) 0.231 COPD 30 (4.8) 2 (5.9) 28 (4.7) 0.673 Interstitial lung disease 46 (7.3) 4 (11.8) 42 (7.1) 0.302 Chronic kidney disease 65 (10.3) 3 (8.8) 62 (10.4) 1.000 Dialysis 10 (1.6) 0 (0) 10 (1.7) 1.000 Liver disease 24 (3.8) 2 (5.9) 22 (3.7) 0.377 Obesity 117 (18.6) 5 (14.7) 112 (18.8) 0.548 CCI > 3 29.0 (181) 17 (51.5) 164 (27.7) 0.003 Previous treatment with ACEI 88 (14) 4 (11.8) 84 (14.1) 1.000 Previous treatment with ARB 66 (10.5) 4 (11.8) 62 (10.4) 0.773 Previous treatment with NSAID 24 (3.8) 2 (5.9) 22 (3.7) 0.377 Length of stay (days, median, IQR) 9 (6–19) 20 (9–36) 9 (9–18) < .001 Bold values indicate statistically significant COPD Chronic Obstructive Pulmonary Disease; CCI Charlson Comorbidity Index; ACEI Angiotensin- Converting-Enzyme Inhibitors; ARB Angiotensin-II receptor blockers; NSAID Non-Steroidal Anti-Inflam- matory Drug *Data are expressed as number and percentages unless otherwise indicated Table 3  Laboratory findings Global (N = 629) Readmitted (N = 34) Non-readmitted (N = 595) P value from patients discharged after hospitalization for SARS-CoV-2 Leucocytes 6.21 (4.72–8.00) 6.98 (4.77–9.06) 6.18 (4.72–7.92) 0.192 infection ANC 4.43 (3.11–6.26) 4.93 (3.14–7.15) 4.44 (3.11–6.11) 0.253 ALC 1.01 (0.76–1.40) 0.83 (0.57–1.23) 1.02 (0.77–1.40) 0.018 Fibrinogen 4.98 (4.42–5.76) 4.89 (4.31–5.35) 4.99 (4.42–5.77) 0.197 d-dimer 252.00 (168.00–436.00) 313 (237–1153.75) 247 (166–425) 0.014 LDH 316.00 (264.00–412.75) 284 (214.5–494.5) 318 (265–412) 0.362 C-reactive protein 8.08 (3.52–15.99) 10.79 (3.68–17.54) 8.01 (3.50–15.92) 0.757 Ferritin 510.00 (266.50–886.75) 548.5 (268–1045.5) 510 (266.50–886.75) 0.726 Interleukin-6 41.64 (22.77–75.45) 58.16 (26.8–153.15) 41.17 (22.52–74.82) 0.145 Bold values indicate statistically significant IQR interquartile range; Leucocytes (×10E9/L); ANC Absolute Neutrophil Count (×10E9/L); ALC Abso- lute Lymphocyte Count (×10E9/L); Fibrinogen (g/L); d-dimer (ng/mL); LDH lactate dehydrogenase (UI/L); CRP C-reactive Protein (mg/dL); Ferritin (ng/mL); IL-6 Interleukin-6 (pg/mL) *Data are expressed as median and IQR anti-coagulation was based on low molecular weight hepa- Eighty-eight patients (14.0%) required admission in inten- rin, 40 mg administered subcutaneously every day. sive care units (ICU) of whom sixty-five (73.9%) required invasive mechanical ventilation (IMV). In those patients 13 C. Kirkegaard et al. Table 4  Radiological findings from patients discharged after hospitalization for SARS-CoV-2 infection Global (N = 629) Readmitted (N = 34) Non-readmitted P value (N = 595) Radiological abnor- 534 (84.9) 20 (58.8) 514 (86.4) < 0.001 mality Bilateral affectation 379 (71) 17 (85) 362 (70.4) 0.159 Extension > 33% 151 (28.3) 11 (55) 140 (27.3) 0.007 Bold values indicate statistically significant *Data are expressed as numbers and percentages unless otherwise indicated Table 5  Treatment during the admission Global (N = 629) Readmitted (N = 34) Non-readmitted (N = 595) P value Corticosteroids 72 (11.4) 10 (29.4) 62 (10.4) 0.001 Immunotherapy 111 (17.6) 9 (26.5) 102 (17.1) 0.165 Anticoagulation < 0.001 None 137 (21.8) 6 (18.2) 131 (22.0) Prophylactic dosage 432 (68.8) 16 (48.5) 416 (69.9) Full dosage 59 (9.4) 11 (33.) 48 (8.1) Admission in ICU 88 (14) 8 (23.5) 80 (13.4) 0.099 Days in ICU (median, IQR) 15 (8–28) 19 (11–29) 15 (8–27) 0.486 HFNC 80 (12.7) 7 (20.6) 73 (12.3) 0.157 NIMV 13 (2.1) 1 (2.9) 12 (2) 0.518 IMV 65 (10.3) 6 (17.6) 59 (9.9) 0.150 Days with IMV (median, IQR) 18 (10–22) 20 (15–25) 15 (8–22) 0.509 ECMO 3 (0.5) 0 (0) 3 (0.5) 1.000 Maximum FiO2 needed (median, IQR) 0.26 (0.21–0.31) 0.26 (0.21–0.8) 0.26 (0.21–0.31) 0.148 FiO2 1 35 (5.6) 3 (8.8) 32 (5.4) 0.427 Cytokine absorption 3 (0.5) 1 (2.9) 2 (0.3) 0.154 Vasoactive support 51 (8.1) 6 (17.6) 45 (7.6) 0.036 Dialysis 9 (1.4) 1 (2.9) 8 (1.3) 0.396 Bold values indicate statistically significant ICU Intensive Care Unit; IQR Intercuartilic range; HFNC High Flow Nasal Cannula; NIMV Non-Invasive Mechanical Ventilation; IMV Invasive Mechanical Ventilation; ECMO Extracorporeal Membrane Oxygenation; FiO2 Fraction of Inspired Oxygen *Data are expressed as numbers and percentages unless otherwise indicated who required admission in ICU, the median days of stay significant differences among the need for vasoactive sup- were 19 in readmitted patients and 15 in non-readmitted; for port (p = 0.036). mechanical ventilation were 20 and 15 days, respectively. No statistically significant differences were found between Complications developed during admission both groups. The readmitted group required more respiratory support. Several complications were described in hospitalized This support consisted of high-flow nasal cannula (20.6% patients: ARDS (14.9%), respiratory failure (28.6%), heart versus 12.3%), non-invasive mechanical ventilation (2.9% failure (2.1%), secondary infection (10.3%), arrhythmia versus 2%), mechanical ventilation (17.6% versus 9.9%) and (5.6%) or PTE (1.6%) among others. Clinical complications fraction of inspired oxygen (FiO2) of 100% administered are detailed in Table 6. with any device (8.8% versus 5.4%). Additionally, this group No statistical differences were found between patients required vasoactive support (17.6% versus 7.6%) and dialy- who developed or did not ARDS or respiratory failure. sis (2.9% versus 1.3%) in a greater percentage than the non- Acute kidney failure and liver dysfunction were described readmitted group. In spite of that, we only found statistically in 5.7 and 4.0% of the patients, respectively. None of the 13 Incidence and risk factors for early readmission after hospitalization for SARS-CoV-2… Table 6  Complications Global (N = 629) Readmitted (N = 34) Non-readmit- P value developed during the admission ted (N = 595) ARDS 94 (14.9) 9 (26.5) 85 (14.3) 0.053 Respiratory failure 180 (28.6) 13 (38.2) 167 (28.1) 0.202 Acute heart failure 13 (2.1) 3 (8.8) 10 (1.7) 0.028 Septic shock 11 (1.7) 1 (2.9) 10 (1.7) 0.460 Acute kidney failure 36 (5.7) 3 (8.8) 33 (5.5) 0.435 Secondary infection 65 (10.3) 10 (29.4) 55 (9.2) < 0.001 Seizures 1 (0.2) 0 (0) 1 (0.2) 1.000 Stroke 1 (0.2) 0 (0) 1 (0.2) 1.000 Myocarditis 1 (0.2) 0 (0) 1 (0.2) 1.000 Pericarditis 2 (0.3) 1 (2.9) 1 (0.2) 0.105 Endocarditis 1 (0.2) 1 (2.9) 0 (0) 0.054 Arrhythmia 15 (2.4) 2 (5.9) 13 (2.2) 0.192 PTE 10 (1.6) 4 (11.8) 6 (1) 0.001 DVP 13 (2.1) 2 (5.9) 11 (1.8) 0.152 Anemia, required transfusions 14 (2.2) 2 (5.9) 12 (2) 0.172 Liver dysfunction 25 (4) 1 (2.9) 24 (4) 1.000 Bold values indicate statistically significant ARDS Acute Respiratory Distress Syndrome; PTE Pulmonary Thromboembolism; DVP Deep-Vein Throm- bosis *Data are expressed as numbers and percentages unless otherwise indicated Table 7  Univariate and Variable Univariate analysis Multivariate analysis multivariate analysis of risk factors associated p OR 95% CI p OR 95% CI with readmission after hospitalization for SARS-CoV-2 PTE < 0.001 13.09 3.51–48.86 0.001 11.59 2.89–46.48 infection Secondary infection < 0.001 4.09 1.86–9.00 Length of stay > 13 days < 0.001 4.07 1.94–8.51 0.015 2.72 1.21–6.12 Treatment with corticoids 0.001 3.58 1.64–7.84 0.049 2.39 1.01–5.70 Prior diagnosis of heart failure 0.004 4.71 1.66–13.39 0.013 4.09 1.35–12.46 CCI > 3 0.005 2.77 1.37–5.61 Drinking habit 0.007 4.10 1.46–11.53 Radiologic affectation > 33% 0.010 3.26 1.32–8.03 ALC < 0.789 × 109/L 0.010 2.52 1.25–5.06 Acute heart failure (complication) 0.011 5.66 1.48–21.62 Smoking habit 0.015 2.38 1.18–4.81 d-dimer > 233 ng/mL 0.015 3.46 1.28–9.50 Prior diagnosis of cancer 0.030 2.64 1.10–6.36 Need of vasoactive support 0.043 2.62 1.03–6.66 Male gender 0.045 2.13 1.02–4.44 ADRS 0.058 2.16 0.98–4.79 Diabetes mellitus 0.084 1.97 0.91–4.24 Admission in ICU 0.105 1.98 0.87–4.53 OR Odds Ratio; CI Confidence Interval; PTE Pulmonary thromboembolism; CCI Charlson Comorbidity Index; ALC Absolute Lymphocyte Count; ADRS Acute Distress Respiratory Syndrome; ICU Intensive Care Unit 13 C. Kirkegaard et al. complications mentioned above showed statistically signifi- In addition, the above-mentioned pro-inflammatory state cant differences nor the presence of septic shock. In con- may play a role for the decompensation of a stable disease. trast, those patients who underwent a secondary infection It has been proposed that neuro-hormonal activation, inflam- (p < 0.001), acute heart failure (p = 0.028) or PTE (p = 0.001) matory activation and oxidative stress may have a primary had higher rates of readmission. role in the progression of a stable/chronic disease, mostly in acute heart failure or decompensated cirrhosis [15, 16]. These complications may not be associated only with SARS- Risk factors associated with readmission CoV-2 infection but also with its indirect medical effects on the healthcare system [17]. In our cohort, more than thirty Table 7 summarizes the results of both univariate and mul- percent of the readmissions were due to a decompensation tivariate analysis of risk factors. of a baseline disease. Among these, thirty percent stemmed Although we found many different risk factors associated from acute heart failure. with readmission, only four of them kept their significance On the other hand, ACE2 receptors are also expressed in in the multivariate analysis. These risk factors were prior endothelial cells and may be dysregulated by SARS-CoV-2 diagnosis of heart failure (OR 4.09; 95% CI 1.35–12.46; infection. This may result in vasoconstriction of microcir- p = 0.013), length of stay >13 days (OR 2.39; 95% CI culation, organ ischaemia and a pro-coagulant state [18]. 1.21–6.12; p = 0.015), treatment with corticoids (OR 2.39; Cytokine release also contributes in a pro-coagulant state 95% CI 1.01–5.7; p = 0.049) and developing PTE (OR 11.59; due to an activation of platelet activity and inducing tis- 95% CI 2.89–46.48; p = 0.001). sue factor [19, 20]. All of it leads to an increased incidence of venous thromboembolism in patients with SARS-CoV-2 pneumonia and poorer prognosis [21]. Low molecular Discussion weight heparin (LMWH) has an anticoagulant effect and reduces the pro-inflammatory cytokines release in patients In this retrospective cohort study of 870 patients admitted with COVID-19 infection [22]. Our findings suggest that to a tertiary care hospital in Spain, we identified an overall PTE is a major cause of readmission and the administra- 60-day readmission cumulative incidence of 5.4%. Of those tion of prophylactic anti-coagulation in hospitalized patients readmitted, half of the patients were readmitted within two might lead to lower readmission rates. weeks of discharge. We found that readmission was associ- Current recommendations on treatment are based on the ated with factors related to a more severe COVID-19, such use of dexamethasone. The benefit of steroid treatment has as a longer hospital stay, the need for corticosteroids or the only been demonstrated in patients requiring oxygen therapy development of PTE, or the presence of previous underlying [23]. Despite that, the optimal dose and duration of treat- disease such as cardiac insufficiency. ment remain unclear. Further studies are required in this On the one hand, the virus principally targets cells which field. The anti-inflammatory properties of steroids seem to express the angiotensin-converting enzyme 2 (ACE2), such reduce hospital stay length, progression to needing IVM and as airway epithelial cells, alveolar epithelial cells, vascular mortality. Conversely, its immunosuppressant effect can lead endothelial cells and macrophages in the lung. This recep- to an increased risk of bacterial superinfection or they may tor has been shown to regulate the renin-angiotensin sys- increase the risk of developing other systemic complications, tem (RAS). The infection appears to reduce ACE2 expres- such as cardiovascular events [24]. Therefore, treatment sion and could result in a dysfunction of the RAS, which with corticoids may play a role in those readmissions due influences blood pressure and fluid/electrolyte balance and to infectious complications and in baseline diseases decom- enhances inflammation and vascular permeability in the air- pensations. In our study, we did not obtain any evidence ways [12]. As a result, a pattern of hematologic, biochemi- about the role of low absolute lymphocyte count and/or cor- cal, inflammatory and immune biomarker abnormalities has ticosteroid administration in fungal invasive infections. In been identified in patients with severe disease and seems to fact, we did not find any fungal infections in the readmitted correlate with the prognosis [13]. Despite that, we did not patients. What we observed was that, in several patients who find lymphopenia to maintain independent statistical impact were admitted to the ICU, strains of Aspergillus spp. were in the multivariate analysis. Similar to other viral infections, isolated in tracheal samples. Otherwise, in none of the cases, such as measles, respiratory syncytial virus, SARS-CoV an invasive fungal infection was described. or MERS-CoV, current reports emphasize the presence of Finally, despite several respiratory complications, such lymphopenia in severe COVID-19 cases. The mechanism of as ARDS or respiratory failure, are related to disease sever- lymphopenia remains incompletely understood but it may be ity, none of them had a statistical impact on the readmis- secondary to an increased apoptosis in T cells and pulmo- sion rate. A similar association is highlighted in Townsend nary recruitment of immune cells [14]. et al. [25], where they describe a persistence of ill health 13 Incidence and risk factors for early readmission after hospitalization for SARS-CoV-2… and fatigue following SARS-CoV-2 infection independent Conclusion of initial severity of infection. Similar to an observational cohort study performed by In our study cohort, we had a readmission cumulative inci- Drewett et al. [26], we found that a longer length of stay dur- dence of 5.4%. The most common causes for readmission ing index admission was significantly associated with read- were respiratory worsening or decompensation of an under- mission. This may be associated with a more severe infection lying disease. Independent risk factors for readmission were and complications developed during hospitalization, which previous diagnosis of cardiac insufficiency, increased length would imply a longer admission. of stay, developing PTE and treatment with corticoids. Our Of note, only one admission more than 15 days after the findings can help focusing follow-up after discharge in those discharge was related to a respiratory event. Similar findings patients who are more likely to require re-hospitalization. are reflected in Sulaiman et al. [11] where readmission at 14 days after discharge is mainly due to respiratory distress. Funding This research did not receive any specific grant from funding Infectious complications were more frequent between 10 and agencies in the public, commercial, or not-for-profit sectors. 30 days after discharge. As suggested in previous studies, patients with comorbidities can be at a high risk of decom- Declarations pensation of their chronic diseases for at least two months Conflict of interest The authors declare they have no conflict of inter- after discharge. This suggests that an enhanced follow-up for est. patients with a high comorbidity burden should be warranted to prevent possible readmissions and further complications. Ethics approval The institutional review board provided ethical clear- In a retrospective observational study performed by Yeo ance (local review board code number: PR(AG)183/2020). Patients were asked for oral consent. The institutional review board granted an et al. [7], readmission cumulative incidence at 30 days after informed consent waiver if patients were unable to give oral consent. discharge was 4.5% and mainly due to hypoxic respira- Written consent was waived because of the crisis context and concerns tory failure, PTE and sepsis. Donnelly et al. [10] analyzed about safety when introducing a physical support for the consent in the readmission among 2179 patients; 19.9% of them had to isolation areas. be readmitted, mostly due to COVID-19, sepsis, pneumo- nia and heart failure. Of note, in this study, they found that COVID-19 survivors had lower rates of 60-day readmis- sion than matched survivors of pneumonia and heart failure. References Finally, in another study of 106,543 patients, Lavery et al. 1. European Centre for Disease Prevention and Control (ECDC). [27] found an incidence of 9% within 2 months, mainly due Available at: https://​www.​ecdc.​europa.​eu/​en. 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