Use of serum KL-6 and chest radiographic severity grade to predict 28-day mortality in COVID-19 patients with pneumonia: a retrospective cohort study

Background: Coronavirus disease 2019 (COVID-19) has had a global social and economic impact. An easy assessment procedure to handily identify the mortality risk of inpatients is urgently needed in clinical practice. Therefore, the aim of this study was to develop a simple nomogram model to categorize patients who might have a poor short-term outcome. Methods: A retrospective cohort study of 189 COVID-19 patients was performed at Shanghai Ren Ji Hospital from December 12, 2022 to February 28, 2023. Chest radiography and biomarkers, including KL-6 were assessed. Predictive factors of 28-day mortality were selected by a Cox regression model. A nomogram was developed based on selected variables. The predictive performance of the derived nomogram was evaluated by calibration curve and decision curve. Results: In total, 173 patients were enrolled in this study. The 28-day mortality event occurred in 41 inpatients (23.7%). Serum KL-6 and radiological severity grade (RSG) were selected as the final prognostic factors. A nomogram model was developed based on 120 patients and validated in 53 patients. The calibration curve and decision curve suggested that the nomogram model was clinically useful. The AUCs for serum KL-6, RSG, and the combined score in the development group and validation group were 0.885 (95% CI: 0.804-0.952), 0.818 (95% CI: 0.711-0.899), 0.869 (95% CI: 0.776-0.942) and 0.932 (95% CI: 0.862-0.997), respectively. Conclusions: Our results suggested that the nomogram based on KL-6 and RSG is a useful model to predict 28-day mortality in COVID-19 patients. A high combined score might indicate a poor outcome in COVID-19 patients with pneumonia.