RT Journal Article
T1 Predicting Clinical Outcome with Phenotypic Clusters in COVID-19 Pneumonia: An Analysis of 12,066 Hospitalized Patients from the Spanish Registry SEMI-COVID-19
A1 Rubio-Rivas, Manuel
A1 Corbella, Xavier
A1 Mora-Luján, José María
A1 Loureiro-Amigo, Jose
A1 López Sampalo, Almudena
A1 Yera Bergua, Carmen
A1 Esteve Atiénzar, Pedro Jesús
A1 Díez García, Luis Felipe
A1 Gonzalez Ferrer, Ruth
A1 Plaza Canteli, Susana
A1 Pérez Piñeiro, Antía
A1 Cortés Rodríguez, Begoña
A1 Jorquer Vidal, Leyre
A1 Pérez Catalán, Ignacio
A1 León Téllez, Marta
A1 Martín Oterino, José Ángel
A1 Martín González, María Candelaria
A1 Serrano Carrillo de Albornoz, José Luis
A1 García Sardon, Eva
A1 Alcalá Pedrajas, José Nicolás
A1 Martin-Urda Diez-Canseco, Anabel
A1 Esteban Giner, María José
A1 Tellería Gómez, Pablo
A1 Ramos-Rincón, José Manuel
A1 Gómez-Huelgas, Ricardo
K1 COVID-19
K1 Cluster analysis
K1 Prognosis
K1 Phenotype
K1 Análisis por conglomerados
K1 Pronóstico
K1 Fenotipo
AB (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.
PB MDPI
YR 2020
FD 2020-10-29
LK http://hdl.handle.net/10668/3353
UL http://hdl.handle.net/10668/3353
LA en
NO Rubio-Rivas M, Corbella X, Mora-Luján JM, Loureiro-Amigo J, López Sampalo A, Yera Bergua C, et al. Predicting Clinical Outcome with Phenotypic Clusters in COVID-19 Pneumonia: An Analysis of 12,066 Hospitalized Patients from the Spanish Registry SEMI-COVID-19. J Clin Med. 2020 Oct 29;9(11):3488.
DS RISalud
RD Apr 8, 2025