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Prevalence, characteristics, and predictors of Long COVID among diagnosed cases of COVID-19
Arjun M C; Arvind Kumar Singh; Debkumar Pal; Kajal Das; Alekhya Gajjala; Mahalingam Venkateshan; Baijayantimala Mishra; Binod Kumar Patro; Prasanta Raghab Mohapatra; Sonu Hangma Subba.
Afiliação
  • Arjun M C; All India Institute of Medical Sciences (AIIMS), Bhubaneswar
  • Arvind Kumar Singh; All India Institute of Medical Sciences,Bhubaneswar
  • Debkumar Pal; All India Institute of Medical Sciences, Bhubaneswar
  • Kajal Das; All India Institute of Medical Sciences, Bhubaneswar
  • Alekhya Gajjala; All India Institute of Medical Sciences, Bhubaneswar
  • Mahalingam Venkateshan; All India Institute of Medical Sciences, Bhubaneswar
  • Baijayantimala Mishra; All India Institute of Medical Sciences, Bhubaneswar
  • Binod Kumar Patro; All India Institute of Medical Sciences, Bhubaneswar
  • Prasanta Raghab Mohapatra; All India Institute of Medical Sciences, Bhubaneswar
  • Sonu Hangma Subba; All India Institute of Medical Sciences, Bhubaneswar
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21268536
ABSTRACT
BackgroundLong COVID or long-term complication after COVID-19 has the ability to affect health and quality of life. Knowledge about the burden and predictors could aid in their prevention and management. Most of the studies are from high-income countries and focus on severe cases. We did this study to estimate the prevalence and identify the characteristics and predictors of Long COVID among our patients. MethodologyWe recruited adult ([≥]18 years) patients who were diagnosed as Reverse Transcription Polymerase Chain Reaction (RTPCR) confirmed SARS-COV-2 infection and were either hospitalized or tested on outpatient basis. Eligible participants were followed up telephonically after four weeks of diagnosis of SARS-COV-2 infection to collect data on sociodemographic, clinical history, vaccination history, Cycle threshold (Ct) values during diagnosis and other variables. Characteristics of Long COVID were elicited, and multivariable logistic regression was done to find the predictors of Long COVID. ResultsWe have analyzed 487 individual data with a median follow-up of 44 days (Inter quartile range (IQR) 39,47). Overall, Long COVID was reported by 29.2% (95% Confidence interval (CI) 25.3%,33.4%) participants. Prevalence of Long COVID among patients with mild/moderate disease (n = 415) was 23.4% (95% CI 19.5%,27.7%) as compared to 62.5% (95% CI 50.7%,73%) in severe/critical cases(n=72). The most common Long COVID symptom was fatigue (64.8%) followed by cough (32.4%). Statistically significant predictors of Long COVID were - Pre-existing medical conditions (Adjusted Odds ratio (aOR)=2.00, 95% CI 1.16,3.44), having a more significant number of symptoms during acute phase of COVID-19 disease (aOR=11.24, 95% CI 4.00,31.51), two doses of COVID-19 vaccination (aOR=2.32, 95% CI 1.17,4.58), the severity of illness (aOR=5.71, 95% CI 3.00,10.89) and being admitted to hospital (Odds ratio (OR)=3.89, 95% CI 2.49,6.08). ConclusionA considerable proportion of COVID-19 cases reported Long COVID symptoms. More research is needed in Long COVID to objectively assess the symptoms and find the biological and radiological markers.
Licença
cc_by_nc_nd
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Cohort_studies / Estudo observacional / Estudo prognóstico Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Cohort_studies / Estudo observacional / Estudo prognóstico Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
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