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A Comprehensive Analysis of Risk Factors and Prediction Model Construction for BPD Premature Infants with EOP |
WANG Li, TAO Songxue, SHEN Wei, et al |
The First Affiliated Hospital of the University of Science and Technology of China / Anhui Provincial Hospital, Anhui Hefei 230001, China |
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Abstract Objective: To analyze the risk factors of encephalopathy of prematurity (EOP) in preterm infants with Bronchopulmonary Dysplasia (BPD) and establish a prediction model. Methods: A total of 153 premature infants with BPD admitted to our hospital from July 2015 to July 2021 were retrospectively analyzed and divided into EOP group (47 cases) and non-EOP group (106 cases). General data and maternal data of the two groups were compared. A logistic regression prediction model was constructed and validated. The predictive performance of the logistic regression model was evaluated by drawing the receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC). Results: The incidence of sepsis, maternal gestational hypertension, Apgar score ≤ 3 at 5 minutes and moderate to severe BPD in EOP group was higher than that in non-EOP group , and the cesarean section rate was lower than that in non-EOP group, and the differences were statistically significant (P<0.05). Multivariate logistic regression analysis showed that sepsis, gestational hypertension and Apgar score ≤ 3 at 5 minutes were independent risk factors for EOP, and cesarean section was a protective factor. The C-index of the EOP nomogram model is 0.915 (95% Cl: 0.861, 0.936), and the area under ROC curve (AUC) is 0.765 (95%CI: 0.683, 0.847). The calibration curve shows that the predicted probability of EOP occurrence by the nomogram model is consistent with the actual probability, and the Hosmer Lemeshow test reveals no statistically significant difference (χ2=2.494, P=0.777), indicating a good fit. Conclusion: Avoiding infections, preventing gestational hypertension during pregnancy, improving Apgar scores, and opting for cesarean delivery are important methods for preventing early-onset pneumonia (EOP) in preterm infants with bronchopulmonary dysplasia (BPD). Establishing a nomogram prediction model based on the aforementioned variables can effectively assess the risk level of EOP in patients.
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