Characteristics and predictors of Long COVID among diagnosed cases of COVID-19

被引:62
作者
Arjun, M. C. [1 ]
Singh, Arvind Kumar [1 ]
Pal, Debkumar [1 ]
Das, Kajal [1 ]
Alekhya, G. [1 ]
Venkateshan, Mahalingam [2 ]
Mishra, Baijayantimala [3 ]
Patro, Binod Kumar [1 ]
Mohapatra, Prasanta Raghab [4 ]
Subba, Sonu Hangma [1 ]
机构
[1] All India Inst Med Sci, Dept Community Med & Family Med, Bhubaneswar, Odisha, India
[2] All India Inst Med Sci, Coll Nursing, Bhubaneswar, Odisha, India
[3] All India Inst Med Sci, Dept Microbiol, Bhubaneswar, Odisha, India
[4] All India Inst Med Sci, Dept Pulm Med & Crit Care, Bhubaneswar, Odisha, India
关键词
D O I
10.1371/journal.pone.0278825
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background Long COVID or long-term symptoms 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 acute COVID-19 cases. We did this study to estimate the incidence and identify the characteristics and predictors of Long COVID among our patients. Methodology We 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 and six months 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. Results We have analyzed 487 and 371 individual data with a median follow-up of 44 days (Inter quartile range (IQR): 39,47) and 223 days (IQR:195,251), respectively. Overall, Long COVID was reported by 29.2% (95% Confidence interval (CI): 25.3%,33.4%) and 9.4% (95% CI: 6.7%,12.9%) of participants at four weeks and six months of follow-up, respectively. Incidence 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) at four weeks of follow-up. At six months, the incidence among mild/moderate (n = 319) was 7.2% (95% CI:4.6%,10.6%) as compared to 23.1% (95% CI:12.5%,36.8%) in severe/critical (n = 52). The most common Long COVID symptom was fatigue. Statistically significant predictors of Long COVID at four weeks of follow-up were-Pre-existing medical conditions (Adjusted Odds ratio (aOR) = 2.00, 95% CI: 1.16,3.44), having a higher 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). Conclusion A 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.
引用
收藏
页数:14
相关论文
共 45 条
[1]   Manifestations and risk factors of post COVID syndrome among COVID-19 patients presented with minimal symptoms - A study from Kerala, India [J].
Anjana, Nalinakumari Kesavan Nair ;
Annie, Twinkle Thomas ;
Siba, Shajahan ;
Meenu, Maheswari Suresh ;
Chintha, Sujatha ;
Anish, Thekkumkara Surendran Nair .
JOURNAL OF FAMILY MEDICINE AND PRIMARY CARE, 2021, 10 (11) :4023-4029
[2]  
[Anonymous], 2022, INDIAN SARS COV 2 GE
[3]  
[Anonymous], 2021, WHO Coronavirus (COVID-19) Dashboard
[4]  
[Anonymous], 2021, POST COVID COND
[5]  
[Anonymous], 2021, MOHFW HOME
[6]  
[Anonymous], 2020, OV COVID 19 RAP GUID
[7]  
[Anonymous], 2020, briefing on COVID-19-March 2020
[8]  
[Anonymous], 2021, GLOBAL COVID 19 CLIN
[9]  
[Anonymous], 2021, Obesity and Overweight
[10]   Post-COVID syndrome in non-hospitalised patients with COVID-19: a longitudinal prospective cohort study [J].
Augustin, Max ;
Schommers, Philipp ;
Stecher, Melanie ;
Dewald, Felix ;
Gieselmann, Lutz ;
Gruell, Henning ;
Horn, Carola ;
Vanshylla, Kanika ;
Di Cristanziano, Veronica ;
Osebold, Luise ;
Roventa, Maria ;
Riaz, Toqeer ;
Tschernoster, Nikolai ;
Altmueller, Janine ;
Rose, Leonard ;
Salomon, Susanne ;
Priesner, Vanessa ;
Luers, Jan Christoffer ;
Albus, Christian ;
Rosenkranz, Stephan ;
Gathof, Birgit ;
Faetkenheuer, Gerd ;
Hallek, Michael ;
Klein, Florian ;
Suarez, Isabelle ;
Lehmann, Clara .
LANCET REGIONAL HEALTH-EUROPE, 2021, 6