(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.

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.

García-Cervera C, et al. Infect Chemother. 2024 Jul;56:e30. https://doi.org/10.3947/ic.2024.0026

(1) Background: 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 March 1, to July 31, 2020, from the nationwide Spanish SEMI-COVID-19 Registry. (3) Results: Of the total of 12,066 patients included in the study, most were males (7,052, 58.5%) and Caucasian (10,635, 89.5%), with a mean age at diagnosis of 67 years (SD 16). The main pre-admission comorbidities were arterial hypertension (6,030, 50%), hyperlipidemia (4,741, 39.4%) and diabetes mellitus (2,309, 19.2%). The average number of days from COVID-19 symptom onset to hospital admission was 6.7 days (SD 7). The triad of fever, cough, and dyspnea was present almost uniformly in all 4 clinical phenotypes identified by clustering. Cluster C1 (8,737 patients, 72.4%) was the largest, and comprised patients with the triad alone. Cluster C2 (1,196 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 (1,253 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 phenotypic clusters as an independent factor for in-hospital death. (4) Conclusion: The present study identified 4 phenotypic clusters in patients with COVID-19 pneumonia, which predicted the in-hospital prognosis of clinical outcomes.