Objective To analyze the influencing factors of unstable ventilation pressure during nasal continuous positive airway pressure (NCPAP) treatment in neonates with hyaline membrane disease (HMD) and construct a nomogram model.

Methods A retrospective analysis was conducted in 157 HMD neonates who underwent NCPAP treatment. The patients were divided into unstable group (n=49) and stable group (n=108) based on the occurrence of unstable ventilation pressure during treatment. Logistic regression analysis was used to identify influencing factors of unstable ventilation pressure during NCPAP treatment in HMD neonates. A nomogram model was constructed using R software, and its predictive performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and the Hosmer-Lemeshow goodness-of-fit test.

Results Unstable ventilation pressure occurred in 49 HMD neonates during NCPAP treatment, with an incidence rate of 31.21% (49/157). Univariate analysis showed that unstable ventilation pressure during NCPAP treatment had no relation to gestational age, gender, birth weight, delivery mode, neonatal Apgar score, catheter distortion, or excessive condensation in the tube (P>0.05). However, NCPAP treatment duration, nasal mucosa damage, secretion blockage in the airway, and restlessness were identified as influencing factors for unstable ventilation pressure during NCPAP treatment in HMD neonates (P < 0.05). Multivariate Logistic regression analysis revealed that NCPAP treatment duration ≥72 h, nasal mucosa damage, secretion blockage in the airway, and restlessness were independent risk factors for unstable ventilation pressure during NCPAP treatment in HMD neonates (P < 0.05). A nomogram model was constructed based on these four independent risk factors. The ROC curve demonstrated good discrimination for the nomogram model, with an area under the curve of 0.801 (95%CI, 0.730 to 0.861). The Hosmer-Lemeshow goodness-of-fit test showed a chi-square value of 3.550 with a P-value of 0.470, and the calibration curve had a slope close to 1, indicating good fit validity for the nomogram prediction model.

Conclusion The nomogram model constructed based on NCPAP treatment duration, nasal mucosa damage, secretion blockage in the airway, and restlessness has good predictive value for the occurrence of unstable ventilation pressure during NCPAP treatment in HMD neonates.