Characterization and predictive risk scoring of long COVID in a south indian cohort after breakthrough COVID infection; a prospective single centre study.

Autor: Nair P; Department of Radiation Oncology, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India., Nair CV; Division of Infectious Diseases, Department of General Medicine, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India., Kulirankal KG; Division of Infectious Diseases, Department of General Medicine, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India., Corley EM; Department of Internal Medicine, Weill Cornell, New York, USA., Edathadathil F; Department of Infection Control and Epidemiology, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India., Gutjahr G; Center for Research in Analytics and Technologies for Education (CREATE), Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, Kerala, India., Moni M; Division of Infectious Diseases, Department of General Medicine, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India., Sathyapalan DT; Division of Infectious Diseases, Department of General Medicine, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India. diputsmck@gmail.com.; Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidhyapeetham, Kochi, 682041, Kerala, India. diputsmck@gmail.com.
Jazyk: angličtina
Zdroj: BMC infectious diseases [BMC Infect Dis] 2023 Oct 09; Vol. 23 (1), pp. 670. Date of Electronic Publication: 2023 Oct 09.
DOI: 10.1186/s12879-023-08600-6
Abstrakt: Background: With the World Health Organization (WHO) declaring an end to the COVID-19 pandemic, the focus has shifted to understanding and managing long-term post-infectious complications. "Long COVID," characterized by persistent or new onset symptoms extending beyond the initial phase of infection, is one such complication. This study aims to describe the incidence, clinical features and risk profile of long COVID among individuals in a South Indian cohort who experienced post-ChAdOx1 n-Cov-2 vaccine breakthrough infections.
Methods: A single-centre hospital-based prospective observational study was conducted from October to December 2021. The study population comprised adult patients (> 18 years) with a confirmed COVID-19 diagnosis who had received at least a single dose of vaccination. Data was collected using a specially tailored questionnaire at week 2, week 6, and week 12 post-negative COVID-19 test. A propensity score based predictive scoring system was developed to assess the risk of long COVID.
Results: Among the 414 patients followed up in the study, 164 (39.6%) reported long COVID symptoms persisting beyond 6 week's post-infection. The presence of long COVID was significantly higher among patients above 65 years of age, and those with comorbidities such as Type II Diabetes Mellitus, hypertension, dyslipidemia, coronary artery disease, asthma, and cancer. Using backwards selection, a reduced model was developed, identifying age (OR 1.053, 95% CI 0.097-1.07, p < 0.001), hypertension (OR 2.59, 95% CI 1.46-4.59, p = 0.001), and bronchial asthma (OR 3.7176, 95% CI 1.24-11.12, p = 0.018) as significant predictors of long COVID incidence. A significant positive correlation was observed between the symptomatic burden and the number of individual comorbidities.
Conclusions: The significant presence of long COVID at 12 weeks among non-hospitalised patients underscores the importance of post-recovery follow-up to assess for the presence of long COVID. The predictive risk score proposed in this study may help identify individuals at risk of developing long COVID. Further research is needed to understand the impact of long COVID on patients' quality of life and the potential role of tailored rehabilitation programs in improving patient outcomes.
(© 2023. BioMed Central Ltd., part of Springer Nature.)
Databáze: MEDLINE
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