Post-COVID-19 Symptom Burden: What is Long-COVID and How Should We Manage It?

Lung. 2021 Apr;199(2):113-119. doi: 10.1007/s00408-021-00423-z. Epub 2021 Feb 11.

Abstract

The enduring impact of COVID-19 on patients has been examined in recent studies, leading to the description of Long-COVID. We report the lasting symptom burden of COVID-19 patients from the first wave of the pandemic. All patients with COVID-19 pneumonia discharged from a large teaching hospital trust were offered follow-up. We assessed symptom burden at follow-up using a standardised data collection technique during virtual outpatient clinic appointments. Eighty-six percent of patients reported at least one residual symptom at follow-up. No patients had persistent radiographic abnormalities. The presence of symptoms at follow-up was not associated with the severity of the acute COVID-19 illness. Females were significantly more likely to report residual symptoms including anxiety (p = 0.001), fatigue (p = 0.004), and myalgia (p = 0.022). The presence of long-lasting symptoms is common in COVID-19 patients. We suggest that the phenomenon of Long-COVID may not be directly attributable to the effect of SARS-CoV-2, and believe the biopsychosocial effects of COVID-19 may play a greater role in its aetiology.

Keywords: COVID-19; Long-COVID; Symptom burden.

MeSH terms

  • Aftercare* / methods
  • Aftercare* / statistics & numerical data
  • Anxiety* / diagnosis
  • Anxiety* / etiology
  • COVID-19 / complications*
  • COVID-19 / diagnosis
  • COVID-19 / epidemiology
  • COVID-19 / physiopathology
  • COVID-19 / psychology
  • COVID-19 / therapy
  • Cost of Illness*
  • Fatigue* / diagnosis
  • Fatigue* / etiology
  • Female
  • Humans
  • Male
  • Middle Aged
  • Models, Biopsychosocial
  • Myalgia / diagnosis
  • Myalgia / etiology
  • Patient Discharge
  • Post-Acute COVID-19 Syndrome
  • SARS-CoV-2 / isolation & purification
  • SARS-CoV-2 / pathogenicity
  • Sex Factors
  • Symptom Assessment / methods
  • Symptom Assessment / statistics & numerical data
  • Telemedicine / methods
  • United Kingdom / epidemiology