Post COVID-19 condition diagnosis among older people: findings from Swedish national register data.

INTRODUCTION: Post COVID-19 condition (PCC) denotes the persistence of symptoms following Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection. PCC poses a large disease burden worldwide. We aimed to explore the epidemiological characteristics of clinically diagnosed PCC among older people aged ≥65 years in Sweden and to establish a machine learning tool to predict PCC risk. METHODS: This nationwide register-based study employed a cross-sectional design. Prevalence of PCC diagnosis recorded in hospital and specialized outpatient care settings among older people aged ≥65 years in Sweden was calculated. Logistic regression models were employed to assess the associations between various factors and PCC diagnosed in hospital and specialized outpatient care. A prediction model based on extreme gradient boosting was constructed based on selected features. RESULTS: Of 236,943 older people aged ≥65 years who were diagnosed with COVID-19, 2.5% of them were diagnosed with PCC in hospital or specialized outpatient care. The odds of PCC diagnosed in hospital and specialized outpatient care in women were lower (OR = 0.78, 95% CI: 0.73-0.82). The odds decreased for each additional year of age (OR = 0.98, 95% CI: 0.98-0.98). Higher odds of PCC were found in people with higher Charlson Comorbidity Index and who used more types of medication. The odds of PCC were the lowest for infections during Omicron-predominant period (OR = 0.09, 95% CI: 0.08-0.10). The predicted PCC risk was generally higher among individuals aged 65-74 years with higher comorbidity burden, more types of medication use, and during early variant-dominant periods. CONCLUSION: In summary, the prevalence of PCC diagnosis among older people in Sweden was relatively low when restricted to hospital and specialized outpatient care. A higher burden of comorbidities and more types of medication use were associated with increased odds of PCC diagnosed in hospital and specialized outpatient care. Register-based predictive models may help identify older people at higher risk of PCC.