A novel nomogram for the early identification of coinfections in elderly patients with COVID-19

Abstract

Background This study aimed to establish a novel, precise, and practical nomogram for use upon hospital admission to identify coinfections among elderly patients with coronavirus disease 2019 (COVID-19) to provide timely intervention, limit antimicrobial agent overuse and hospitalisation costs, finally reduce unfavourable outcomes. Methods This prospective cohort study included COVID-19 patients consecutively admitted at multicenter medical facilities in a two-stage process. The nomogram was built on the multivariable logistic regression analysis. The performance of the nomogram was assessed for discrimination and calibration using receiver operating characteristic curves, calibration plots, and decision curve analysis (DCA) in rigorous internal and external validation settings. Results Between 7 December 2022 and 1 February 2023, in the first stage of this study, 916 COVID-19 patients were included. The coinfection rates in non-elderly and elderly patients determined to be 16.22% and 26.61%, respectively. Pneumonia caused by other pathogens (85.45%) was the most common coinfection-associated illness in the elderly group. Bacteria were the most common pathogens associated with coinfections in the elderly, especially gram-negative bacteria (48%) of Acinetobacter baumanii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Fungi (38%) were the second most common pathogens isolated from coinfections in elderly patients with COVID-19. The nomogram was developed with the parameters of diabetes comorbidity, previous invasive procedure, and procalcitonin (PCT) level, which together showed areas under the curve of 0.86, 0.82, and 0.83 in the training, internal validation, and external validation cohorts, respectively. The nomogram outperformed both PCT or C-reactive protein level alone in detecting coinfections in elderly patients with COVID-19; in addition, we found the nomogram was specific for the elderly compared to non-elderly group. Calibration plots of the nomogram revealed excellent agreement between the predicted and actual probabilities of coinfection occurrence, and the DCA indicated favourable clinical consistency of nomogram results. Conclusions This novel nomogram will assist in the early identification of coinfections in elderly patients with COVID-19. Trial registration: This study was registered at https://ClinicalTrials.gov, with the registration NCT06321367 (registration Date: 2024-03-20).