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1.
JCI Insight ; 7(13)2022 07 08.
Article in English | MEDLINE | ID: covidwho-1932894

ABSTRACT

BACKGROUNDProlonged symptoms after SARS-CoV-2 infection are well documented. However, which factors influence development of long-term symptoms, how symptoms vary across ethnic groups, and whether long-term symptoms correlate with biomarkers are points that remain elusive.METHODSAdult SARS-CoV-2 reverse transcription PCR-positive (RT-PCR-positive) patients were recruited at Stanford from March 2020 to February 2021. Study participants were seen for in-person visits at diagnosis and every 1-3 months for up to 1 year after diagnosis; they completed symptom surveys and underwent blood draws and nasal swab collections at each visit.RESULTSOur cohort (n = 617) ranged from asymptomatic to critical COVID-19 infections. In total, 40% of participants reported at least 1 symptom associated with COVID-19 six months after diagnosis. Median time from diagnosis to first resolution of all symptoms was 44 days; median time from diagnosis to sustained symptom resolution with no recurring symptoms for 1 month or longer was 214 days. Anti-nucleocapsid IgG level in the first week after positive RT-PCR test and history of lung disease were associated with time to sustained symptom resolution. COVID-19 disease severity, ethnicity, age, sex, and remdesivir use did not affect time to sustained symptom resolution.CONCLUSIONWe found that all disease severities had a similar risk of developing post-COVID-19 syndrome in an ethnically diverse population. Comorbid lung disease and lower levels of initial IgG response to SARS-CoV-2 nucleocapsid antigen were associated with longer symptom duration.TRIAL REGISTRATIONClinicalTrials.gov, NCT04373148.FUNDINGNIH UL1TR003142 CTSA grant, NIH U54CA260517 grant, NIEHS R21 ES03304901, Sean N Parker Center for Allergy and Asthma Research at Stanford University, Chan Zuckerberg Biohub, Chan Zuckerberg Initiative, Sunshine Foundation, Crown Foundation, and Parker Foundation.


Subject(s)
COVID-19 , COVID-19/complications , Humans , Immunoglobulin G , SARS-CoV-2 , Post-Acute COVID-19 Syndrome
2.
Diabetes ; 71, 2022.
Article in English | ProQuest Central | ID: covidwho-1923977

ABSTRACT

Background: Obesity and diabetes are known risk factors for severe acute COVID-19. About half of individuals with obesity have insulin resistance (IR) , which may potentiate severe acute disease and/or predispose to long COVID. Methods: We identified 596 adults from Stanford hospital or clinics confirmed COVID-19+ by rtPCR and categorized according to severity of illness based on the NIH categories1. Pre-COVID predictors including BMI, fasting plasma glucose (FPG) , and triglyceride/HDL-cholesterol ratio (TG/HDL) as a surrogate2 for IR were ed from the EMR using the Stanford Research Repository Tools software. Follow-up surveys were administered via REDCap 2-4x in the first month and 1x per month for 1 year thereafter to assess symptom type and duration. Long COVID was defined as symptom duration > 30 days. Metabolic predictors of acute COVID-severity (BMI, FPG, TG/HDL) were evaluated via multiple linear regression adjusted for sex, age, ethnicity, and other metabolic predictors. A logistic regression to predict long COVID included all metabolic predictors along with age, sex, and ethnicity. Models were repeated with a stepwise approach to increase statistical power given the smaller number of participants with complete data. Results: Participants were 51±18 years of age, 49% female, and 62% racial and ethnic minorities. Mean BMI was 29.5±7.9 kg/m2. NIH illness severity was 7.9% asymptomatic, 37.2% mild, 25.9% moderate, 15.1% severe, and 13.9% critical. Diabetes, lung disease, and hypertension prevalence were 27%, 18%, and 34%, respectively. Mean follow-up was 94±99 and incidence of long COVID was 47.1%. BMI, FPG, and TG/HDL were independently associated with acute COVID-severity in the cohort as a whole (r=0.187, P<0.001;r=0.180, P=0.002;r=0.180, P=0.009) , while only TG/HDL was associated with long COVID (r=0.173, p=0.013) . Conclusions: Findings suggest that IR, independent of sex, age, ethnicity, obesity and hyperglycemia, confers increased risk for both severe acute COVID-and long COVID.

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