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Title: Predicting Clinical Outcome with Phenotypic Clusters in COVID-19 Pneumonia: An Analysis of 12,066 Hospitalized Patients from the Spanish Registry SEMI-COVID-19
Author: Rubio-Rivas, Manuel
Corbella, Xavier
Mora Luján, José María
Loureiro Amigo, José
López Sampalo, Almudena
Yera Bergua, Carmen
Esteve Atiénzar, Pedro Jesús
Díez García, Luis Felipe
Gonzalez Ferrer, Ruth
Plaza Canteli, Susana
Pérez Pineiro, Antía
Cortés Rodríguez, Begoña
Jorquer Vidal, Leyre
Pérez Catalán, Ignacio
León Téllez, Marta
Martín Oterino, José Ángel
Martín González, María Candelaria
Serrano Carrillo de Albornoz, José Luis
García Sardon, Eva
Alcalá Pedrajas, José Nicolás
Martin-Urda Diez-Canseco, Anabel
Esteban Giner, María José
Tellería Gómez, Pablo
Ramos Rincón, José Manuel
Gómez Huelgas, Ricardo
Keywords: COVID-19
Pronòstic mèdic
Issue Date: 1-Nov-2020
Publisher: MDPI
Abstract: (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.
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It is part of: Journal of Clinical Medicine, 2020, vol. 9, num.11
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Appears in Collections:Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))

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