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COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler: Looking for Clarity in the Haze of the Pandemic.
Huang, Yong; Pinto, Melissa D; Borelli, Jessica L; Mehrabadi, Milad Asgari; Abrihim, Heather; Dutt, Nikil; Lambert, Natalie; Nurmi, Erika L; Chakraborty, Rana; Rahmani, Amir M; Downs, Charles A.
Afiliação
  • Huang Y; Department of Computer Science, Donald Bern School of Information and Computer Science, University of California Irvine, Irvine, California.
  • Pinto MD; Sue & Bill Gross School of Nursing, University of California Irvine, Irvine, California.
  • Borelli JL; Department of Psychological Science, School of Social Ecology, University of California Irvine, Irvine, California.
  • Mehrabadi MA; Department of Computer Science, Donald Bern School of Information and Computer Science, University of California Irvine, Irvine, California.
  • Abrihim H; Sue & Bill Gross School of Nursing, University of California Irvine, Irvine, California.
  • Dutt N; Department of Computer Science, Donald Bern School of Information and Computer Science, University of California Irvine, Irvine, California.
  • Lambert N; School of Medicine, Indiana University, Indianapolis, Indiana.
  • Nurmi EL; Department of Psychiatry and Biobehavioral Science, UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, California.
  • Chakraborty R; Department of Pediatrics and Adolescent Medicine, Division of Infectious Disease, Mayo Clinic, Rochester, Minnesota.
  • Rahmani AM; Department of Computer Science, Donald Bern School of Information and Computer Science, University of California Irvine, Irvine, California.
  • Downs CA; Sue & Bill Gross School of Nursing, University of California Irvine, Irvine, California.
medRxiv ; 2021 Mar 05.
Article em En | MEDLINE | ID: mdl-33688670
Emerging data suggest that the effects of infection with SARS-CoV-2 are far reaching extending beyond those with severe acute disease. Specifically, the presence of persistent symptoms after apparent resolution from COVID-19 have frequently been reported throughout the pandemic by individuals labeled as "long-haulers". The purpose of this study was to assess for symptoms at days 0-10 and 61+ among subjects with PCR-confirmed SARS-CoV-2 infection. The University of California COvid Research Data Set (UC CORDS) was used to identify 1407 records that met inclusion criteria. Symptoms attributable to COVID-19 were extracted from the electronic health record. Symptoms reported over the previous year prior to COVID-19 were excluded, using nonnegative matrix factorization (NMF) followed by graph lasso to assess relationships between symptoms. A model was developed predictive for becoming a long-hauler based on symptoms. 27% reported persistent symptoms after 60 days. Women were more likely to become long-haulers, and all age groups were represented with those aged 50 ± 20 years comprising 72% of cases. Presenting symptoms included palpitations, chronic rhinitis, dysgeusia, chills, insomnia, hyperhidrosis, anxiety, sore throat, and headache among others. We identified 5 symptom clusters at day 61+: chest pain-cough, dyspnea-cough, anxiety-tachycardia, abdominal pain-nausea, and low back pain-joint pain. Long-haulers represent a very significant public health concern, and there are no guidelines to address their diagnosis and management. Additional studies are urgently needed that focus on the physical, mental, and emotional impact of long-term COVID-19 survivors who become long-haulers.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: MedRxiv Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: MedRxiv Ano de publicação: 2021 Tipo de documento: Article