Machine learning identifies risk factors associated with long-term sick leave following COVID-19 in Danish population
Description
CONCLUSIONS: Our study supports significant individual-level heterogeneity in the effect of SARS-CoV-2 infection on long-term sick-leave, with age, sex, high BMI, and depression identified as key factors. Efforts to curb the PCC burden should
