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 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

Post-Hospital Syndrome and Hyponatremia

Introduction: Post-hospital syndrome (PHS) is defined as a period of vulnerability during the first 30 days after a patient is discharged from hospital, in which multiple factors come into play. Hyponatremia is the most frequent hydroelectrolytic disorder in hospitalized patients and may be related to the appearance of PHS. Objective: The objective is to estimate the prevalence of PHS that is assessed as the rate of readmissions in the first 30 days after discharge, in patients with hyponatremia. Material and Methods: It is a descriptive observational study of patients with hyponatremia who were discharged from 1 September 2010 to 2 February 2020 at the Internal Medicine Service of the Hospital University of San Juan (Alicante, Spain). Results: Of the 25 included patients, 5 (20%) were readmitted within a month of discharge, after a mean of 11.4 days (standard deviation [SD] 5.1). The overall mortality of the study was 20% (n = 5), with one case of death in the first 30 days post-hospitalization (4%). In 12 patients (48%) the origin of the hyponatremia was undetermined. The most frequently recorded etiology for the condition was pharmacological (n = 7, 28%), and there was pronounced variability in its clinical and laboratory study. The most widely used corrective measure was drug withdrawal, in 16 patients (64%). Water intake restriction was the most common treatment after discharge (5 patients, 20%), followed by urea (2 patients, 8%), while tolvaptan was not used. Conclusion: Hyponatremia may be the cause of PHS, which could increase the rate of early readmission. Hyponatremia is an underdiagnosed and undertreated entity, so it is necessary to apply an appropriate system to optimize its management and, in future studies, to assess its impact on PHS

Nutritional and Functional Impact of Acute SARS-CoV-2 Infection in Hospitalized Patients

Aim: To assess the prevalence of malnutrition, frailty, and sarcopenia and the relationships between them in patients hospitalized for COVID-19. Methods: This was a cross-sectional study of the prevalence, determinants, and associations between malnutrition (GLIM 2019 criteria), sarcopenia (SARC-F scale, dynamometry, and calf circumference), and frailty (FRAIL scale) upon discharge following hospitalization for COVID 19. Results: A total of 101 patients (67.3% men, mean age 66.3 years) were recruited. Malnutrition was diagnosed in 49.5%, sarcopenia in 32.7%, and frailty in 28.7% of patients. Of the patients with malnutrition, 48% were also sarcopenic, and 42% were frail. There was a significant association between malnutrition and the severity of pneumonia according to the CURB-65 scale (odds ratio [OR] 2.61, p = 0.036), between sarcopenia and a Barthel score lower than 60 points (OR 29.52, p < 0.001), and between frailty and both a Barthel score lower than 60 points (OR 32.27, p < 0.001) and a length of hospital stay of over 30 days (OR 9.11, p = 0.008). Conclusions: Malnutrition, sarcopenia, and frailty are prevalent and interrelated entities in patients hospitalized for acute SARS CoV-2 infection, especially in patients with greater baseline functional impairment prior to admission and a higher infection severity