The Journal of international medical research · 2023
Development of a nomogram for severe influenza in previously healthy children: a retrospective cohort study.
ОбзорСтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Huang Wenyun, Niu Wensi, Chen Hongmei, Jiang Wujun, Fu Yanbing, Li Xiuxiu, Li Minglei, Hua Jun, Hu Chunxia
Аннотация
OBJECTIVE: We aimed to develop a nomogram to predict the risk of severe influenza in previously healthy children.
METHODS: In this retrospective cohort study, we reviewed the clinical data of 1135 previously healthy children infected with influenza who were hospitalized in the Children's Hospital of Soochow University between 1 January 2017 and 30 June 2021. Children were randomly assigned in a 7:3 ratio to a training or validation cohort. In the training cohort, univariate and multivariate logistic regression analyses were used to identify risk factors, and a nomogram was established. The validation cohort was used to evaluate the predictive ability of the model.
RESULT: Wheezing rales, neutrophils, procalcitonin > 0.25 ng/mL, Mycoplasma pneumoniae infection, fever, and albumin were selected as predictors. The areas under the curve were 0.725 (95% CI: 0.686-0.765) and 0.721 (95% CI: 0.659-0.784) for the training and validation cohorts, respectively. The calibration curve showed that the nomogram was well calibrated.
CONCLUSION: The nomogram may predict the risk of severe influenza in previously healthy children.
METHODS: In this retrospective cohort study, we reviewed the clinical data of 1135 previously healthy children infected with influenza who were hospitalized in the Children's Hospital of Soochow University between 1 January 2017 and 30 June 2021. Children were randomly assigned in a 7:3 ratio to a training or validation cohort. In the training cohort, univariate and multivariate logistic regression analyses were used to identify risk factors, and a nomogram was established. The validation cohort was used to evaluate the predictive ability of the model.
RESULT: Wheezing rales, neutrophils, procalcitonin > 0.25 ng/mL, Mycoplasma pneumoniae infection, fever, and albumin were selected as predictors. The areas under the curve were 0.725 (95% CI: 0.686-0.765) and 0.721 (95% CI: 0.659-0.784) for the training and validation cohorts, respectively. The calibration curve showed that the nomogram was well calibrated.
CONCLUSION: The nomogram may predict the risk of severe influenza in previously healthy children.