Demystifying the Risk of Long COVID-19: Clinical, Psychological, and Lung Imaging Abnormalities

Objective: The objective of this study was to analyse clinical symptoms, quality of life, chest X-rays, and factors associated with post-COVID-19 symptoms. Methods: This prospective cohort study involved hospitalised COVID-19 patients who were followed up until 3 months after discharge. Clinical symptoms, examinations, imaging, etc., were evaluated during admission and 3 months after. Quality of life (QOL) was assessed using the SF-36 questionnaire. Results: About 76 adult COVID-19 hospitalised patients were followed up during treatment for up to 3 months. Mortality rate was 30.26%. About 69.81% of patients experienced residual symptoms consisting of 54.71% acute-post-COVID-19, 9.4% ongoing-post-COVID-19, and 5.6% long- COVID-19. The most common residual symptoms were fatigue, dyspnea, myalgia, cough, weakness, anxiety, and headache. Brixia score was higher in deceased and residual symptom groups compared to the no residual symptom group. QOL of post-COVID-19 patients decreased in all domains and was lower in long-COVID-19. Social functioning and pain were domains that differed significantly in all residual symptom groups. Bivariate analysis found that age >50 years (OR=3.472), history of mechanical ventilator use (OR=0.644), and RR ≥ 28 times/minute (OR=3.529) were factors associated with the occurrence of post-COVID-19 syndrome. All degrees of severity during COVID-19 contributed to the occurrence of post-COVID-19 syndrome. Conclusion: Almost 70% of hospitalised post-COVID-19 patients with various severities will experience residual symptoms with decreased quality of life. Several influencing factors are age >50, history of ventilator use, RR ≥28x/minute, and extent of lung abnormalities.

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Journal
Coronaviruses
Published
2025-02-26
DOI
https://doi.org/10.2174/0126667975343313250217065013
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Demystifying the Risk of Long COVID-19: Clinical, Psychological, and Lung Imaging Abnormalities

Anggraini Dwi Sensusiati, Arina Dery Puspitasari, Izzatul Fithriyah, Jusak Nugraha et al.
Coronaviruses
Radiomics and Machine Learning in Medical Imaging
article

Demystifying the Risk of Long COVID-19: Clinical, Psychological, and Lung Imaging Abnormalities

Anggraini Dwi Sensusiati, Arina Dery Puspitasari, Izzatul Fithriyah, Jusak Nugraha, Alfian Nur Rosyid, Muhammad Amin
article en

Abstract

Objective: The objective of this study was to analyse clinical symptoms, quality of life, chest X-rays, and factors associated with post-COVID-19 symptoms. Methods: This prospective cohort study involved hospitalised COVID-19 patients who were followed up until 3 months after discharge. Clinical symptoms, examinations, imaging, etc., were evaluated during admission and 3 months after. Quality of life (QOL) was assessed using the SF-36 questionnaire. Results: About 76 adult COVID-19 hospitalised patients were followed up during treatment for up to 3 months. Mortality rate was 30.26%. About 69.81% of patients experienced residual symptoms consisting of 54.71% acute-post-COVID-19, 9.4% ongoing-post-COVID-19, and 5.6% long- COVID-19. The most common residual symptoms were fatigue, dyspnea, myalgia, cough, weakness, anxiety, and headache. Brixia score was higher in deceased and residual symptom groups compared to the no residual symptom group. QOL of post-COVID-19 patients decreased in all domains and was lower in long-COVID-19. Social functioning and pain were domains that differed significantly in all residual symptom groups. Bivariate analysis found that age >50 years (OR=3.472), history of mechanical ventilator use (OR=0.644), and RR ≥ 28 times/minute (OR=3.529) were factors associated with the occurrence of post-COVID-19 syndrome. All degrees of severity during COVID-19 contributed to the occurrence of post-COVID-19 syndrome. Conclusion: Almost 70% of hospitalised post-COVID-19 patients with various severities will experience residual symptoms with decreased quality of life. Several influencing factors are age >50, history of ventilator use, RR ≥28x/minute, and extent of lung abnormalities.

CoronavirusesVol. 06
Universitas Airlangga (ID), Indonesian Pediatric Society (ID)
Openalex Percentile: Top 95%
Radiomics and Machine Learning in Medical Imaging
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