Abstract
OBJECTIVES: To establish a nomogram model for the early diagnosis of sepsis in children. METHODS: A total of 76 children with sepsis who were admitted to Sichuan Maternal and Child Health Hospital from January 2018 to June 2021 were retrospectively selected as the sepsis group. After matching for sex and age (±2 years) at a ratio of 1:1:1, 76 children with local infection who were hospitalized during the same period were enrolled as the local infection group, and 76 children with non-infectious diseases were enrolled as the control group. The three groups were compared in terms of laboratory markers and the results of quick Sequential Organ Failure Assessment (qSOFA) and Pediatric Critical Illness Score (PCIS). A multivariate logistic regression analysis was used to investigate the association between the above indicators and sepsis. R4.1.3 software was used to establish and validate the nomogram model for the early diagnosis of sepsis based on the results of the multivariate analysis. A receiver operating characteristic (ROC) curve analysis was used to evaluate the value of the nomogram model, and the Bootstrap method was used to perform the internal validation of the model. RESULTS: The multivariate logistic regression analysis showed that soluble triggering receptor expressed on myeloid cells-1, qSOFA score, PCIS score, C-reactive protein, interleukin-6, and interleukin-10 were independently associated with childhood sepsis (P<0.05). The above indicators were used to establish a nomogram for the early diagnosis of sepsis, with an area under the ROC curve of 0.837 (95%CI: 0.760-0.914), and the calibration curve results showed a mean absolute error of 0.024, suggesting that the performance of this model was basically consistent with that of the ideal model. CONCLUSIONS: The indicators soluble triggering receptor expressed on myeloid cells-1, qSOFA score, PCIS score, C-reactive protein, interleukin-6, and interleukin-10 are independently associated with childhood sepsis, and the nomogram model established based on these indicators has high discriminatory ability and accuracy in the early diagnosis of sepsis in children.