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Factors Associated With Long COVID Symptoms in an Online Cohort Study.
Durstenfeld, Matthew S; Peluso, Michael J; Peyser, Noah D; Lin, Feng; Knight, Sara J; Djibo, Audrey; Khatib, Rasha; Kitzman, Heather; O'Brien, Emily; Williams, Natasha; Isasi, Carmen; Kornak, John; Carton, Thomas W; Olgin, Jeffrey E; Pletcher, Mark J; Marcus, Gregory M; Beatty, Alexis L.
  • Durstenfeld MS; Division of Cardiology at ZSFG, and Department of Medicine, University of California, San Francisco, San Francisco, California, USA.
  • Peluso MJ; Division of HIV, Infectious Disease, Global Medicine, University of California, San Francisco, San Francisco, California, USA.
  • Peyser ND; Division of Cardiology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA.
  • Lin F; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA.
  • Knight SJ; Division of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, USA.
  • Djibo A; CVS Health Clinical Trial Services, Blue Bell, Pennsylvania, USA.
  • Khatib R; Advocate Aurora Research Institute, Milwaukee, Wisconsin, USA.
  • Kitzman H; Baylor Scott and White Health and Wellness Center, Dallas, Texas, USA.
  • O'Brien E; Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA.
  • Williams N; Institute for Excellence in Health Equity, Center for Healthful Behavior Change, NYU Grossman School of Medicine, New York, New York, USA.
  • Isasi C; Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, New York, USA.
  • Kornak J; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA.
  • Carton TW; Louisiana Public Health Institute, New Orleans, Louisiana, USA.
  • Olgin JE; Division of Cardiology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA.
  • Pletcher MJ; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA.
  • Marcus GM; Division of Cardiology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA.
  • Beatty AL; Division of Cardiology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA.
Open Forum Infect Dis ; 10(2): ofad047, 2023 Feb.
Article in English | MEDLINE | ID: covidwho-2257795
ABSTRACT

Background:

Few prospective studies of Long COVID risk factors have been conducted. The purpose of this study was to determine whether sociodemographic factors, lifestyle, or medical history preceding COVID-19 or characteristics of acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are associated with Long COVID.

Methods:

In March 26, 2020, the COVID-19 Citizen Science study, an online cohort study, began enrolling participants with longitudinal assessment of symptoms before, during, and after SARS-CoV-2 infection. Adult participants who reported a positive SARS-CoV-2 test result before April 4, 2022 were surveyed for Long COVID symptoms. The primary outcome was at least 1 prevalent Long COVID symptom greater than 1 month after acute infection. Exposures of interest included age, sex, race/ethnicity, education, employment, socioeconomic status/financial insecurity, self-reported medical history, vaccination status, variant wave, number of acute symptoms, pre-COVID depression, anxiety, alcohol and drug use, sleep, and exercise.

Results:

Of 13 305 participants who reported a SARS-CoV-2 positive test, 1480 (11.1%) responded. Respondents' mean age was 53 and 1017 (69%) were female. Four hundred seventy-six (32.2%) participants reported Long COVID symptoms at a median 360 days after infection. In multivariable models, number of acute symptoms (odds ratio [OR], 1.30 per symptom; 95% confidence interval [CI], 1.20-1.40), lower socioeconomic status/financial insecurity (OR, 1.62; 95% CI, 1.02-2.63), preinfection depression (OR, 1.08; 95% CI, 1.01-1.16), and earlier variants (OR = 0.37 for Omicron compared with ancestral strain; 95% CI, 0.15-0.90) were associated with Long COVID symptoms.

Conclusions:

Variant wave, severity of acute infection, lower socioeconomic status, and pre-existing depression are associated with Long COVID symptoms.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Topics: Long Covid / Vaccines / Variants Language: English Journal: Open Forum Infect Dis Year: 2023 Document Type: Article Affiliation country: Ofid

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Topics: Long Covid / Vaccines / Variants Language: English Journal: Open Forum Infect Dis Year: 2023 Document Type: Article Affiliation country: Ofid