tetano
Editor, Senior Moderator
BMC Infect Dis
. 2025 Nov 7;25(1):1523.
doi: 10.1186/s12879-025-11956-6. Impact of long COVID phenotypes on quality of life following symptomatic omicron infection in Brazil: a machine learning analysis
Fernando Luis Scolari[SUP] 1 2 3 [/SUP], Julia Spinardi[SUP] 4 [/SUP], Mariana Motta Dias da Silva[SUP] 5 [/SUP], Geraldine Trott[SUP] 5 [/SUP], Cristina de Oliveira Rodrigues[SUP] 6 [/SUP], Marciane Maria Rover[SUP] 5 [/SUP], Emanuel Maltempi de Souza[SUP] 7 [/SUP], Josélia Larger Manfio[SUP] 5 8 [/SUP], Nathan Iori Camargo[SUP] 5 8 [/SUP], Ana Paula de Souza[SUP] 5 [/SUP], Denise de Souza[SUP] 5 [/SUP], Raíne Fogliati De Carli[SUP] 5 [/SUP], Emelyn de Souza Roldão[SUP] 5 [/SUP], Duane Mocellin[SUP] 5 [/SUP], Aline Paula Miozzo[SUP] 5 [/SUP], Gabrielle Nunes da Silva[SUP] 5 [/SUP], Jennifer Menna Barreto de Souza[SUP] 5 [/SUP], Rosa da Rosa Minho Dos Santos[SUP] 5 [/SUP], Carolina Rothmann Itaqui[SUP] 5 [/SUP], Gabriela Soares Rech[SUP] 5 [/SUP], Vivian Menezes Irineu[SUP] 9 [/SUP], Saionara Cristina Francisco[SUP] 10 [/SUP], Odilson Silvestre[SUP] 11 [/SUP], Precil Diego Miranda de Menezes Neves[SUP] 12 [/SUP], Lucas Tramujas[SUP] 13 [/SUP], Vandack Nobre[SUP] 14 [/SUP], Sidiclei Machado Carvalho[SUP] 5 [/SUP], Carlos Delmar do Amaral Ferreira[SUP] 5 [/SUP], Jaqueline Carvalho de Oliveira[SUP] 15 [/SUP], Carla Adriane Royer[SUP] 15 [/SUP], Rafael Messias Luiz[SUP] 6 [/SUP], Valter Antonio Baura[SUP] 7 [/SUP], Daniela Fiori Gradia[SUP] 15 [/SUP], Ana Paula Carneiro Brandalize[SUP] 6 [/SUP], Hellen Abreu Pereira[SUP] 15 [/SUP], Carolina Gracia Poitevin[SUP] 15 [/SUP], Caroline Cabral Robinson[SUP] 5 8 [/SUP], Bruna Brandao Barreto[SUP] 16 [/SUP], Paulo R Schvartzman[SUP] 5 [/SUP], Milena Marcolino[SUP] 14 [/SUP], Ana Carolina Peçanha Antonio[SUP] 17 [/SUP], Carisi Anne Polanczyk[SUP] 5 17 18 [/SUP], Juçara Gasparetto Maccari[SUP] 5 [/SUP], Luiz Antonio Nasi[SUP] 5 18 [/SUP], Srinivas Rao Valluri[SUP] 4 [/SUP], Viviane Wal Julião[SUP] 4 [/SUP], Florence Lefebvre d'Hellencourt[SUP] 4 [/SUP], Moe H Kyaw[SUP] 4 [/SUP], Graciela Del Carmen Morales Castillo[SUP] 4 [/SUP], Maicon Falavigna[SUP] 5 8 [/SUP], Regis Goulart Rosa[SUP] 5 8 18 [/SUP]
Affiliations
Background: This study aimed to identify phenotypes of long COVID symptoms in adults following Omicron infection and assess their association with health-related quality of life (HRQoL).
Methods: We analyzed three prospective observational studies in Brazil, enrolling adult patients who sought care for symptomatic Omicron infection between December 2021 and March 2023. The infection was confirmed by either an antigen test or reverse transcriptase polymerase chain reaction. Long COVID symptoms were assessed three months after enrollment through structured interviews. Phenotypes of Long COVID-19 were identified using a machine learning-based clustering approach. Exploratory analyses were conducted to examine predisposing factors and health-related quality of life utilities, measured by EQ-5D-3 L, associated with each phenotype.
Results: A total of 2,989 patients were analyzed (39% women, median age 41 years, and 96% had completed the primary series of COVID-19 vaccination). Long COVID symptoms at three months were reported by 1,155 (38.6%) patients. Three phenotypes were identified: cluster 1 (n = 459 [39.7%]), characterized by a median of three symptoms (IQR, 2-5) with memory loss (80.4%), concentration problems (38.3%) and fatigue (35.7%) being most common; cluster 2 (n = 549 [47.5%]), characterized by a median of two symptoms (IQR, 1-4) with fatigue (43.7%), other symptoms (42.3%), and cough (20.6%) being most common; and cluster 3 (n = 147, 12.7%), characterized by a higher number of symptoms (median, 8; IQR, 7-10), with fatigue (89.9%), memory loss (88.4%), and anxiety (64.6%) as the most common. The mean EQ-5D-3 L utility at 3 months was 0.75 for cluster 1, 0.73 for cluster 2, and 0.59 for cluster 3 (p < 0.001). After adjusted regression analysis, cluster 3 was independently associated with the lowest EQ-5D-3 L utilities (mean difference, -0.21; 95%CI, -0.24 to -0.18; p < 0.001).
Conclusions: Distinct phenotypic presentations of Long COVID following Omicron infection in Brazil were identified, with significant differences in quality of life.
Clinical trial number: Not applicable.
Keywords: COVID-19; Cluster analysis; EQ-5D-3L; Omicron; Phenotype; Quality of life.
. 2025 Nov 7;25(1):1523.
doi: 10.1186/s12879-025-11956-6. Impact of long COVID phenotypes on quality of life following symptomatic omicron infection in Brazil: a machine learning analysis
Fernando Luis Scolari[SUP] 1 2 3 [/SUP], Julia Spinardi[SUP] 4 [/SUP], Mariana Motta Dias da Silva[SUP] 5 [/SUP], Geraldine Trott[SUP] 5 [/SUP], Cristina de Oliveira Rodrigues[SUP] 6 [/SUP], Marciane Maria Rover[SUP] 5 [/SUP], Emanuel Maltempi de Souza[SUP] 7 [/SUP], Josélia Larger Manfio[SUP] 5 8 [/SUP], Nathan Iori Camargo[SUP] 5 8 [/SUP], Ana Paula de Souza[SUP] 5 [/SUP], Denise de Souza[SUP] 5 [/SUP], Raíne Fogliati De Carli[SUP] 5 [/SUP], Emelyn de Souza Roldão[SUP] 5 [/SUP], Duane Mocellin[SUP] 5 [/SUP], Aline Paula Miozzo[SUP] 5 [/SUP], Gabrielle Nunes da Silva[SUP] 5 [/SUP], Jennifer Menna Barreto de Souza[SUP] 5 [/SUP], Rosa da Rosa Minho Dos Santos[SUP] 5 [/SUP], Carolina Rothmann Itaqui[SUP] 5 [/SUP], Gabriela Soares Rech[SUP] 5 [/SUP], Vivian Menezes Irineu[SUP] 9 [/SUP], Saionara Cristina Francisco[SUP] 10 [/SUP], Odilson Silvestre[SUP] 11 [/SUP], Precil Diego Miranda de Menezes Neves[SUP] 12 [/SUP], Lucas Tramujas[SUP] 13 [/SUP], Vandack Nobre[SUP] 14 [/SUP], Sidiclei Machado Carvalho[SUP] 5 [/SUP], Carlos Delmar do Amaral Ferreira[SUP] 5 [/SUP], Jaqueline Carvalho de Oliveira[SUP] 15 [/SUP], Carla Adriane Royer[SUP] 15 [/SUP], Rafael Messias Luiz[SUP] 6 [/SUP], Valter Antonio Baura[SUP] 7 [/SUP], Daniela Fiori Gradia[SUP] 15 [/SUP], Ana Paula Carneiro Brandalize[SUP] 6 [/SUP], Hellen Abreu Pereira[SUP] 15 [/SUP], Carolina Gracia Poitevin[SUP] 15 [/SUP], Caroline Cabral Robinson[SUP] 5 8 [/SUP], Bruna Brandao Barreto[SUP] 16 [/SUP], Paulo R Schvartzman[SUP] 5 [/SUP], Milena Marcolino[SUP] 14 [/SUP], Ana Carolina Peçanha Antonio[SUP] 17 [/SUP], Carisi Anne Polanczyk[SUP] 5 17 18 [/SUP], Juçara Gasparetto Maccari[SUP] 5 [/SUP], Luiz Antonio Nasi[SUP] 5 18 [/SUP], Srinivas Rao Valluri[SUP] 4 [/SUP], Viviane Wal Julião[SUP] 4 [/SUP], Florence Lefebvre d'Hellencourt[SUP] 4 [/SUP], Moe H Kyaw[SUP] 4 [/SUP], Graciela Del Carmen Morales Castillo[SUP] 4 [/SUP], Maicon Falavigna[SUP] 5 8 [/SUP], Regis Goulart Rosa[SUP] 5 8 18 [/SUP]
Affiliations
- PMID: 41204118
- PMCID: PMC12595840
- DOI: 10.1186/s12879-025-11956-6
Background: This study aimed to identify phenotypes of long COVID symptoms in adults following Omicron infection and assess their association with health-related quality of life (HRQoL).
Methods: We analyzed three prospective observational studies in Brazil, enrolling adult patients who sought care for symptomatic Omicron infection between December 2021 and March 2023. The infection was confirmed by either an antigen test or reverse transcriptase polymerase chain reaction. Long COVID symptoms were assessed three months after enrollment through structured interviews. Phenotypes of Long COVID-19 were identified using a machine learning-based clustering approach. Exploratory analyses were conducted to examine predisposing factors and health-related quality of life utilities, measured by EQ-5D-3 L, associated with each phenotype.
Results: A total of 2,989 patients were analyzed (39% women, median age 41 years, and 96% had completed the primary series of COVID-19 vaccination). Long COVID symptoms at three months were reported by 1,155 (38.6%) patients. Three phenotypes were identified: cluster 1 (n = 459 [39.7%]), characterized by a median of three symptoms (IQR, 2-5) with memory loss (80.4%), concentration problems (38.3%) and fatigue (35.7%) being most common; cluster 2 (n = 549 [47.5%]), characterized by a median of two symptoms (IQR, 1-4) with fatigue (43.7%), other symptoms (42.3%), and cough (20.6%) being most common; and cluster 3 (n = 147, 12.7%), characterized by a higher number of symptoms (median, 8; IQR, 7-10), with fatigue (89.9%), memory loss (88.4%), and anxiety (64.6%) as the most common. The mean EQ-5D-3 L utility at 3 months was 0.75 for cluster 1, 0.73 for cluster 2, and 0.59 for cluster 3 (p < 0.001). After adjusted regression analysis, cluster 3 was independently associated with the lowest EQ-5D-3 L utilities (mean difference, -0.21; 95%CI, -0.24 to -0.18; p < 0.001).
Conclusions: Distinct phenotypic presentations of Long COVID following Omicron infection in Brazil were identified, with significant differences in quality of life.
Clinical trial number: Not applicable.
Keywords: COVID-19; Cluster analysis; EQ-5D-3L; Omicron; Phenotype; Quality of life.