Henan Province Engineering Research Center of Diagnosis and Treatment of Pediatric Infection and Critical Care, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, 450052, China.
Eur J Clin Microbiol Infect Dis. 2024 Sep;43(9):1795-1805. doi: 10.1007/s10096-024-04898-5. Epub 2024 Jul 13.
Development of a nomogram model for predicting the magnitude of risk of transferring hospitalized children with influenza to the ICU.
In a single-center retrospective study, 318 children with influenza who were hospitalized in our hospital from January 2018 to August 2023 were collected as study subjects. Children with influenza were randomly assigned to the training set and validation set in a ratio of 4:1. In the training set, risk factors were identified using univariate and multivariate logistic regression analyses, and a nomogram model was created on this basis. The validation set was used to evaluate the predictive power of the model.
Multifactorial logistic regression analysis revealed six independent risk factors for transfer to the ICU in hospitalized children with influenza, including elevated peripheral white blood cell counts, elevated large platelet ratios, reduced mean platelet width, reduced complement C3, elevated serum globulin levels, and reduced total immunoglobulin M levels. Using these six metrics as predictors to construct a nomogram graphical model, the C-index was 0.970 (95% Cl: 0.953-0.988). The areas under the curve for the training and validation sets were 0.966 (95%Cl 0.947-0.985) and 0.919 (95%Cl 0.851-0.986), respectively.
A nomogram for predicting the risk of transferring to the ICU for children with influenza was developed and validated, which demonstrates good calibration and clinical benefits.
开发一种列线图模型，用于预测因流感住院的患儿转入 ICU 的风险程度。
采用单中心回顾性研究，收集 2018 年 1 月至 2023 年 8 月期间在我院因流感住院的 318 例患儿作为研究对象。患儿按 4:1 的比例随机分配至训练集和验证集。在训练集中，采用单因素和多因素逻辑回归分析确定危险因素，并在此基础上建立列线图模型。验证集用于评估模型的预测能力。
多因素逻辑回归分析显示，流感住院患儿转入 ICU 的 6 个独立危险因素，包括外周血白细胞计数升高、大血小板比率升高、平均血小板宽度降低、补体 C3 降低、血清球蛋白水平升高和总免疫球蛋白 M 水平降低。使用这 6 个指标作为预测因子构建列线图图形模型，C 指数为 0.970（95%Cl：0.953-0.988）。训练集和验证集的曲线下面积分别为 0.966（95%Cl 0.947-0.985）和 0.919（95%Cl 0.851-0.986）。
开发并验证了一种预测流感患儿转入 ICU 风险的列线图模型，该模型具有良好的校准度和临床获益。
