Symptom Clustering Patterns and Population Characteristics of COVID-19 Based on Text Clustering Method

Abstract

BackgroundDescriptions of single clinical symptoms of coronavirus disease 2019 (COVID-19) have been widely reported. However, evidence of symptoms associations was still limited. We sought to explore the potential symptom clustering patterns and high-frequency symptom combinations of COVID-19 to enhance the understanding of people of this disease.MethodsIn this retrospective cohort study, a total of 1,067 COVID-19 cases were enrolled. Symptom clustering patterns were first explored by a text clustering method. Then, a multinomial logistic regression was applied to reveal the population characteristics of different symptom groups. In addition, time intervals between symptoms onset and the first visit were analyzed to consider the effect of time interval extension on the progression of symptoms.ResultsBased on text clustering, the symptoms were summarized into four groups. Group 1: no-obvious symptoms; Group 2: mainly fever and/or dry cough; Group 3: mainly upper respiratory tract infection symptoms; Group 4: mainly cardiopulmonary, systemic, and/or gastrointestinal symptoms. Apart from Group 1 with no obvious symptoms, the most frequent symptom combinations were fever only (64 cases, 47.8%), followed by dry cough only (42 cases, 31.3%) in Group 2; expectoration only (21 cases, 19.8%), followed by expectoration complicated with fever (10 cases, 9.4%) in Group 3; fatigue complicated with fever (12 cases, 4.2%), followed by headache complicated with fever was also high (11 cases, 3.8%) in Group 4. People aged 45–64 years were more likely to have symptoms of Group 4 than those aged 65 years or older (odds ratio [OR] = 2.66, 95% CI: 1.21–5.85) and at the same time had longer time intervals.ConclusionsSymptoms of COVID-19 could be divided into four clustering groups with different symptom combinations. The Group 4 symptoms (i.e., mainly cardiopulmonary, systemic, and/or gastrointestinal symptoms) happened more frequently in COVID-19 than in influenza. This distinction could help deepen the understanding of this disease. The middle-aged people have a longer time interval for medical visit and was a group that deserve more attention, from the perspective of medical delays.

Characterising patterns of COVID-19 and long COVID symptoms: evidence from nine UK longitudinal studies

“…Decrease in symptom burden has been previously observed in older age groups compared with younger (e.g. [ 32 ]), reflecting our results here. The identified symptom patterns among individuals with COVID-19 > 12 weeks ago were found to be strongly associated with length of time unable to function as normal due to COVID-19 symptoms.…”

“…In the symptom clustering analyses, the data did not support more than two symptom patterns among any of the COVID-19 groups in any of the studies, though relatively small sample sizes in these groups may have affected our ability to identify further symptom patterns of low prevalence. Other studies using differing clustering methods and study designs have found greater than two symptom patterns annotated as distinct symptom sets when studying acute COVID-19 [ 32 , 33 ] and long COVID [ 34 ]. However, some studies have similarly found two symptom patterns to best fit the data: in the Norwegian Mother, Father and Child Cohort Study, Caspersen et al [ 1 ] analysed 73,727 adults followed throughout the pandemic and observed distinct patterns of post-acute symptoms characterised as ‘neurocognitive’ and ‘cardiorespiratory’.…”

Characterising patterns of COVID-19 and long COVID symptoms: Evidence from nine UK longitudinal studies

“…In the symptom clustering analyses, the data did not support more than two symptom patterns among any of the COVID-19 groups in any of the studies, though relatively small sample sizes in these groups may have affected our ability to identify further symptom patterns of low prevalence. Other studies using differing clustering methods and study designs have found greater than two symptom patterns annotated as distinct symptoms sets when studying acute COVID-19 (32, 33) and long COVID (34). However, some studies have similarly found two symptom patterns to best fit the data: in the Norwegian Mother, Father and Child Cohort Study, Caspersen et al 2022 (1) analysed 73,727 adults followed throughout the pandemic and observed distinct patterns of post-acute symptoms characterised as ‘neurocognitive’ and ‘cardiorespiratory’.…”

Symptom profiles and vaccination status for COVID‐19 after the adjustment of the dynamic zero‐COVID policy in China: An observational study

“…[absent (0), mild (1), moderate (2), and severe (3)]. The study covered 33 symptoms; those like cough, fatigue, and running nose were referred from validated studies 7,9 ; other symptoms frequently occurring on social media were also included. These symptoms were divided into four syndromes: respiratory symptoms (nine types), neurological symptoms (nine types), digestive symptoms (eight types), and other symptoms (seven types).…”