Age and chest computed tomography severity score are predictors of long-COVID
Introduction: About one-third of acute coronavirus disease 2019 (COVID-19) survivors have suffered from persisting symptoms called long-COVID. Clinical factors such as age and intensity (moderate or acute) of COVID-19 have been found to be associated with long-COVID. Many tissues might be damaged f...
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The Journal of Infection in Developing Countries
2024-02-01
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| Series: | Journal of Infection in Developing Countries |
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| Online Access: | https://jidc.org/index.php/journal/article/view/18276 |
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| author | Merve Erkan |
| author_facet | Merve Erkan |
| author_sort | Merve Erkan |
| collection | DOAJ |
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Introduction: About one-third of acute coronavirus disease 2019 (COVID-19) survivors have suffered from persisting symptoms called long-COVID. Clinical factors such as age and intensity (moderate or acute) of COVID-19 have been found to be associated with long-COVID. Many tissues might be damaged functionally or structurally during acute COVID-19 which can be detected by blood assays and chest computed tomography (CT). We aimed to evaluate the relationship between long-COVID and the initial findings of blood assays and chest CT as possible predictors.
Methodology: The study included patients with acute COVID-19. Laboratory tests and chest CT were obtained from each patient at the time of admission to the hospital. Chest CT was evaluated for pneumonic involvement and severity score. Multivariable regression model was created to find the factors that were independently associated with long-COVID.
Results: There were 60 (38.2%) patients with long-COVID and 97 (61.8%) without. Baseline demographic, laboratory and chest CT parameters were similar in both groups, except for age, chronic lung disease and chest CT severity score (46.9 ± 15.1 years vs 52.6 ± 15.9 years, p = 0.03; 11.7% vs 3.1%, p = 0.03 and 10.3 ± 9.6 vs 6.5 ± 7.6, p = 0.02, respectively). In multivariable model, chest CT severity score (OR: 1.059, 95% CI: 1.002-1.119, p = 0.04) and age (OR: 0.953, 95% CI: 0.928-0.979, p < 0.001) were independently associated with long-COVID.
Conclusions: Chest CT severity score and age were independently associated with long-COVID and may be used to predict the future risk of long-COVID.
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| format | Article |
| id | doaj-art-c09d64b3be3b4eb7aff4852b830e8c01 |
| institution | DOAJ |
| issn | 1972-2680 |
| language | English |
| publishDate | 2024-02-01 |
| publisher | The Journal of Infection in Developing Countries |
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| series | Journal of Infection in Developing Countries |
| spelling | doaj-art-c09d64b3be3b4eb7aff4852b830e8c012025-08-20T02:57:17ZengThe Journal of Infection in Developing CountriesJournal of Infection in Developing Countries1972-26802024-02-01180210.3855/jidc.18276Age and chest computed tomography severity score are predictors of long-COVIDMerve Erkan0University of Health Sciences, Bursa Yuksek Ihtisas Training and Research Hospital, Department of Radiology, Bursa, Turkey Introduction: About one-third of acute coronavirus disease 2019 (COVID-19) survivors have suffered from persisting symptoms called long-COVID. Clinical factors such as age and intensity (moderate or acute) of COVID-19 have been found to be associated with long-COVID. Many tissues might be damaged functionally or structurally during acute COVID-19 which can be detected by blood assays and chest computed tomography (CT). We aimed to evaluate the relationship between long-COVID and the initial findings of blood assays and chest CT as possible predictors. Methodology: The study included patients with acute COVID-19. Laboratory tests and chest CT were obtained from each patient at the time of admission to the hospital. Chest CT was evaluated for pneumonic involvement and severity score. Multivariable regression model was created to find the factors that were independently associated with long-COVID. Results: There were 60 (38.2%) patients with long-COVID and 97 (61.8%) without. Baseline demographic, laboratory and chest CT parameters were similar in both groups, except for age, chronic lung disease and chest CT severity score (46.9 ± 15.1 years vs 52.6 ± 15.9 years, p = 0.03; 11.7% vs 3.1%, p = 0.03 and 10.3 ± 9.6 vs 6.5 ± 7.6, p = 0.02, respectively). In multivariable model, chest CT severity score (OR: 1.059, 95% CI: 1.002-1.119, p = 0.04) and age (OR: 0.953, 95% CI: 0.928-0.979, p < 0.001) were independently associated with long-COVID. Conclusions: Chest CT severity score and age were independently associated with long-COVID and may be used to predict the future risk of long-COVID. https://jidc.org/index.php/journal/article/view/18276long-COVIDpost-COVIDchest CTpneumonia chest CT severity score |
| spellingShingle | Merve Erkan Age and chest computed tomography severity score are predictors of long-COVID Journal of Infection in Developing Countries long-COVID post-COVID chest CT pneumonia chest CT severity score |
| title | Age and chest computed tomography severity score are predictors of long-COVID |
| title_full | Age and chest computed tomography severity score are predictors of long-COVID |
| title_fullStr | Age and chest computed tomography severity score are predictors of long-COVID |
| title_full_unstemmed | Age and chest computed tomography severity score are predictors of long-COVID |
| title_short | Age and chest computed tomography severity score are predictors of long-COVID |
| title_sort | age and chest computed tomography severity score are predictors of long covid |
| topic | long-COVID post-COVID chest CT pneumonia chest CT severity score |
| url | https://jidc.org/index.php/journal/article/view/18276 |
| work_keys_str_mv | AT merveerkan ageandchestcomputedtomographyseverityscorearepredictorsoflongcovid |