Establishment of risk prediction model for nosocomial infection in preterm very low birth weight infants
- Author:
HU Yuanyuan
;
LIU Ya
;
HE Jiao
;
YANG Xuejiao
;
LIU Zhenzhen
- Publication Type:Journal Article
- Keywords:
Preterm very low birth weight infants;
nosocomial infection;
multivariate analysis;
nomogram model
- From:
China Tropical Medicine
2023;23(9):971-
- CountryChina
- Language:Chinese
-
Abstract:
Abstract: Objective To establish a risk prediction model for nosocomial infection in preterm very low birth weight infants, and conduct internal validation. Methods A total of 206 cases of very low birth weight premature infants hospitalized in the Department of Neonatology of Union Hospital Affiliated to Tongji Medical College from January 2018 to June 2020 were included in this study, factors that may affect the nosocomial infection of children were collected, and the infants were divided into two groups according to whether there is nosocomial infection. The influencing factors were compared between the two groups, and multivariate Logistic regression analysis was performed after screening variables with LASSO regression. According to the results of multi factor analysis, the nomogram model was constructed and verified internally. Results A total of 29 of 206 children had nosocomial infection (14.08%), and 33 pathogenic bacteria were detected, including 23 Gram-negative bacteria, 9 Gram-positive bacteria and 1 fungus. The results of multivariate logistic regression analysis based on LASSO regression showed that the risk factors for nosocomial infection of VLBW premature infants were 28-31+6 weeks of gestation, amniotic fluid pollution, mechanical ventilation, indwelling gastric tube, unreasonable use of antibiotics, and hospitalization time ≥ 7 days. The protective factors were Apgar score ≥ 7 points at 1 min and breast feeding accounting for 50% or more (P<0.05). The Area Under Curve (AUC) of ROC curve of nomogram model was 0.946 [95%CI(0.923, 1.000)]. The calibration curve showed that the probability of hospital infection predicted by the model was basically consistent with the actual probability. The decision curve showed that when the probability threshold of nomogram model to predict the risk of nosocomial infection of very low birth weight premature infants was 0-0.85, the net rate of return was greater than 0. Conclusion Preterm infants with extremely low birth weight are at high risk of nosocomial infection, mainly affected by factors such as gestational weeks, hospitalization time, amniotic fluid pollution, etc. The nomogram model constructed by the above factors has high accuracy and discrimination for predicting nosocomial infection in such children.
- Full text:14.Establishment of risk prediction model for nosocomial infection in preterm very low birth weight.pdf
