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The post-acute sequelae of SARS-CoV-2 (PASC) pose a threat to patients' health-related quality of life (HRQOL). Here, the impact of COVID-19 on HRQOL and the clinical factors associated with impaired HRQOL were examined. Discharged COVID-19 patients were assessed at 3 and 6 months after disease onset. The patients completed a medical examination and the SF-36 questionnaire at these two time points and underwent pulmonary function testing at 6 months after disease onset. All had undergone computed tomography (CT) imaging upon hospital admission. Of the 74 included patients, 38% reported respiratory symptoms at 3 months, and 26% reported respiratory symptoms at 6 months after disease onset. The aggregated SF-36 scores declined in the role/social component summary (RCS), a category related to social activity. Patients with lower RCS tended to have respiratory sequelae or a relatively lower forced vital capacity. The CT score that reflected the extent of COVID-19 pneumonia was inversely correlated with the RCS score (3 months, p = 0.0024; 6 months, p = 0.0464). A high CT score (≥10 points) predicted a low RCS score at 6 months (p = 0.013). This study highlights the impairment of RCS and its associations with respiratory sequelae. The study also emphasizes the importance of radiological findings in predicting long-term HRQOL outcomes after COVID-19. [ABSTRACT FROM AUTHOR]

Background: Post-Acute Sequelae of COVID-19 (PASC) have emerged as a global public health and healthcare challenge. This study aimed to uncover predictive factors for PASC from multi-modal data to develop a predictive model for PASC diagnoses. Methods: We analyzed electronic health records from 92,301 COVID-19 patients, covering medical phenotypes, medications, and lab results. We used a Super Learner-based prediction approach to identify predictive factors. We integrated the model outputs into individual and composite risk scores and evaluated their predictive performance. Results: Our analysis identified several factors predictive of diagnoses of PASC, including being overweight/obese and the use of HMG CoA reductase inhibitors prior to COVID-19 infection, and respiratory system symptoms during COVID-19 infection. We developed a composite risk score with a moderate discriminatory ability for PASC (covariate-adjusted AUC (95% confidence interval): 0.66 (0.63, 0.69)) by combining the risk scores based on phenotype and medication records. The combined risk score could identify 10% of individuals with a 2.2-fold increased risk for PASC. Conclusions: We identified several factors predictive of diagnoses of PASC and integrated the information into a composite risk score for PASC prediction, which could contribute to the identification of individuals at higher risk for PASC and inform preventive efforts. [ABSTRACT FROM AUTHOR]