Frequency, risk factors, and outcomes of hospital readmissions of COVID-19 patients.

To determine the proportion of patients with COVID-19 who were readmitted to the hospital and the most common causes and the factors associated with readmission. Multicenter nationwide cohort study in Spain. Patients included in the study were admitted to 147 hospitals from March 1 to April 30, 2020. Readmission was defined as a new hospital admission during the 30 days after discharge. Emergency department visits after discharge were not considered readmission. During the study period 8392 patients were admitted to hospitals participating in the SEMI-COVID-19 network. 298 patients (4.2%) out of 7137 patients were readmitted after being discharged. 1541 (17.7%) died during the index admission and 35 died during hospital readmission (11.7%, p = 0.007). The median time from discharge to readmission was 7 days (IQR 3-15 days). The most frequent causes of hospital readmission were worsening of previous pneumonia (54%), bacterial infection (13%), venous thromboembolism (5%), and heart failure (5%). Age [odds ratio (OR): 1.02; 95% confident interval (95% CI): 1.01-1.03], age-adjusted Charlson comorbidity index score (OR: 1.13; 95% CI: 1.06-1.21), chronic obstructive pulmonary disease (OR: 1.84; 95% CI: 1.26-2.69), asthma (OR: 1.52; 95% CI: 1.04-2.22), hemoglobin level at admission (OR: 0.92; 95% CI: 0.86-0.99), ground-glass opacification at admission (OR: 0.86; 95% CI:0.76-0.98) and glucocorticoid treatment (OR: 1.29; 95% CI: 1.00-1.66) were independently associated with hospital readmission. The rate of readmission after hospital discharge for COVID-19 was low. Advanced age and comorbidity were associated with increased risk of readmission.

Risk Categories in COVID-19 Based on Degrees of Inflammation: Data on More Than 17,000 Patients from the Spanish SEMI-COVID-19 Registry.

(1) Background: The inflammation or cytokine storm that accompanies COVID-19 marks the prognosis. This study aimed to identify three risk categories based on inflammatory parameters on admission. (2) Methods: Retrospective cohort study of patients diagnosed with COVID-19, collected and followed-up from 1 March to 31 July 2020, from the nationwide Spanish SEMI-COVID-19 Registry. The three categories of low, intermediate, and high risk were determined by taking into consideration the terciles of the total lymphocyte count and the values of C-reactive protein, lactate dehydrogenase, ferritin, and D-dimer taken at the time of admission. (3) Results: A total of 17,122 patients were included in the study. The high-risk group was older (57.9 vs. 64.2 vs. 70.4 years; p < 0.001) and predominantly male (37.5% vs. 46.9% vs. 60.1%; p < 0.001). They had a higher degree of dependence in daily tasks prior to admission (moderate-severe dependency in 10.8% vs. 14.1% vs. 17%; p < 0.001), arterial hypertension (36.9% vs. 45.2% vs. 52.8%; p < 0.001), dyslipidemia (28.4% vs. 37% vs. 40.6%; p < 0.001), diabetes mellitus (11.9% vs. 17.1% vs. 20.5%; p < 0.001), ischemic heart disease (3.7% vs. 6.5% vs. 8.4%; p < 0.001), heart failure (3.4% vs. 5.2% vs. 7.6%; p < 0.001), liver disease (1.1% vs. 3% vs. 3.9%; p = 0.002), chronic renal failure (2.3% vs. 3.6% vs. 6.7%; p < 0.001), cancer (6.5% vs. 7.2% vs. 11.1%; p < 0.001), and chronic obstructive pulmonary disease (5.7% vs. 5.4% vs. 7.1%; p < 0.001). They presented more frequently with fever, dyspnea, and vomiting. These patients more frequently required high flow nasal cannula (3.1% vs. 4.4% vs. 9.7%; p < 0.001), non-invasive mechanical ventilation (0.9% vs. 3% vs. 6.3%; p < 0.001), invasive mechanical ventilation (0.6% vs. 2.7% vs. 8.7%; p < 0.001), and ICU admission (0.9% vs. 3.6% vs. 10.6%; p < 0.001), and had a higher percentage of in-hospital mortality (2.3% vs. 6.2% vs. 23.9%; p < 0.001). The three risk categories proved to be an independent risk factor in multivariate analyses. (4) Conclusion: The present study identifies three risk categories for the requirement of high flow nasal cannula, mechanical ventilation, ICU admission, and in-hospital mortality based on lymphopenia and inflammatory parameters.

Predicting Clinical Outcome with Phenotypic Clusters in COVID-19 Pneumonia: An Analysis of 12,066 Hospitalized Patients from the Spanish Registry SEMI-COVID-19.

(1) Background: Different clinical presentations in COVID-19 are described to date, from mild to severe cases. This study aims to identify different clinical phenotypes in COVID-19 pneumonia using cluster analysis and to assess the prognostic impact among identified clusters in such patients. (2) Methods: Cluster analysis including 11 phenotypic variables was performed in a large cohort of 12,066 COVID-19 patients, collected and followed-up from 1 March to 31 July 2020, from the nationwide Spanish Society of Internal Medicine (SEMI)-COVID-19 Registry. (3) Results: Of the total of 12,066 patients included in the study, most were males (7052, 58.5%) and Caucasian (10,635, 89.5%), with a mean age at diagnosis of 67 years (standard deviation (SD) 16). The main pre-admission comorbidities were arterial hypertension (6030, 50%), hyperlipidemia (4741, 39.4%) and diabetes mellitus (2309, 19.2%). The average number of days from COVID-19 symptom onset to hospital admission was 6.7 (SD 7). The triad of fever, cough, and dyspnea was present almost uniformly in all 4 clinical phenotypes identified by clustering. Cluster C1 (8737 patients, 72.4%) was the largest, and comprised patients with the triad alone. Cluster C2 (1196 patients, 9.9%) also presented with ageusia and anosmia; cluster C3 (880 patients, 7.3%) also had arthromyalgia, headache, and sore throat; and cluster C4 (1253 patients, 10.4%) also manifested with diarrhea, vomiting, and abdominal pain. Compared to each other, cluster C1 presented the highest in-hospital mortality (24.1% vs. 4.3% vs. 14.7% vs. 18.6%; p < 0.001). The multivariate study identified age, gender (male), body mass index (BMI), arterial hypertension, chronic obstructive pulmonary disease (COPD), ischemic cardiopathy, chronic heart failure, chronic hepatopathy, Charlson's index, heart rate and respiratory rate upon admission >20 bpm, lower PaO2/FiO2 at admission, higher levels of C-reactive protein (CRP) and lactate dehydrogenase (LDH), and the phenotypic cluster as independent factors for in-hospital death. (4) Conclusions: The present study identified 4 phenotypic clusters in patients with COVID-19 pneumonia, which predicted the in-hospital prognosis of clinical outcomes.