Early prediction of long COVID-19 syndrome persistence at 12 months after hospitalisation: a prospective observational study from Ukraine

Objective To identify the early predictors of a self-reported persistence of long COVID syndrome (LCS) at 12 months after hospitalisation and to propose the prognostic model of its development. Design A combined cross-sectional and prospective observational study. Setting A tertiary care hospital. Participants 221 patients hospitalised for COVID-19 who have undergone comprehensive clinical, sonographic and survey-based evaluation predischarge and at 1 month with subsequent 12-month follow-up. The final cohort included 166 patients who had completed the final visit at 12 months. Main outcome measure A self-reported persistence of LCS at 12 months after discharge. Results Self-reported LCS was detected in 76% of participants at 3 months and in 43% at 12 months after discharge. Patients who reported incomplete recovery at 1 year were characterised by a higher burden of comorbidities (Charlson index of 0.69 +/- 0.96 vs 0.31 +/- 0.51, p=0.001) and residual pulmonary consolidations (1.56 +/- 1.78 vs 0.98 +/- 1.56, p=0.034), worse blood pressure (BP) control (systolic BP of 138.1 +/- 16.2 vs 132.2 +/- 15.8 mm Hg, p=0.041), renal (estimated glomerular filtration rate of 59.5 +/- 14.7 vs 69.8 +/- 20.7 mL/min/1.73 m(2), p=0.007) and endothelial function (flow-mediated dilation of the brachial artery of 10.4 +/- 5.4 vs 12.4 +/- 5.6%, p=0.048), higher in-hospital levels of liver enzymes (alanine aminotransferase (ALT) of 76.3 +/- 60.8 vs 46.3 +/- 25.3 IU/L, p=0.002) and erythrocyte sedimentation rate (ESR) (34.3 +/- 12.1 vs 28.3 +/- 12.6 mm/h, p=0.008), slightly higher indices of ventricular longitudinal function (left ventricular (LV) global longitudinal strain (GLS) of 18.0 +/- 2.4 vs 17.0 +/- 2.3%, p=0011) and higher levels of Hospital Anxiety and Depression Scale anxiety (7.3 +/- 4.2 vs 5.6 +/- 3.8, p=0.011) and depression scores (6.4 +/- 3.9 vs 4.9 +/- 4.3, p=0.022) and EFTER-COVID study physical symptoms score (12.3 +/- 3.8 vs 9.2 +/- 4.2, p<0.001). At 1 month postdischarge, the persisting differences included marginally higher LV GLS, mitral E/e' ratio and significantly higher levels of both resting and exertional physical symptoms versus patients who reported complete recovery. Logistic regression and machine learning-based binary classification models have been developed to predict the persistence of LCS symptoms at 12 months after discharge. Conclusions Compared with post-COVID-19 patients who have completely recovered by 12 months after hospital discharge, those who have subsequently developed 'very long' COVID were characterised by a variety of more pronounced residual predischarge abnormalities that had mostly subsided by 1 month, except for steady differences in the physical symptoms levels. A simple artificial neural networks-based binary classification model using peak ESR, creatinine, ALT and weight loss during the acute phase, predischarge 6-minute walk distance and complex survey-based symptoms assessment as inputs has shown a 92% accuracy with an area under receiver-operator characteristic curve 0.931 in prediction of LCS symptoms persistence at 12 months.