Predictive markers, prediction models and systems for bronchopulmonary dysplasia in premature infants
CN114638398BActive Publication Date: 2025-04-15SUZHOU UNIV
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Patent Information
- Application Number
- CN202210139403.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-02-15
- Publication Date
- 2025-04-15
- Estimated Expiration
- 2042-02-15
AI Technical Summary
Technical Problem
The prior art is difficult to effectively predict the occurrence of bronchial pulmonary dysplasia (BPD) in premature infants, resulting in low diagnostic levels and lack of targeted intervention.
Method used
Logistic regression was used to construct a predictive model of BPD in premature infants by combining six predictors, including eNOS (1d), severe alveolar interstitial syndrome (3d), EUGR, caffeine treatment days, total oxygen inhalation days, and LMR.
Benefits of technology
A sensitivity of 96.7% and a specificity of 100.0% were achieved, which was significantly higher than the existing prediction model, and could effectively predict the occurrence of BPD and provide the possibility of early intervention.
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Abstract
The invention discloses a predictive marker, a predictive model and a system for bronchopulmonary dysplasia in premature infants, and discloses that EUGR, days of caffeine treatment, total days of oxygen inhalation and LMR are independent risk factors for the occurrence of BPD in premature infants. The incidence of severe alveolar interstitial syndrome indicated by lung ultrasound on the third day after birth, the incidence of pleural line changes, alveolar interstitial syndrome, pulmonary consolidation or fragmentation signs indicated by lung ultrasound on the 28th day after birth have a predictive effect on the occurrence of BPD. The serum eNOS level of the BPD group was significantly higher than that of the non-BPD group on the first day after birth, and was positively correlated with the severity of BPD. When the serum eNOS level on the first day after birth was greater than 6.48 ng / ml, the risk of BPD in premature infants increased significantly. The combined regression model constructed by six indicators of serum eNOS (1d) level, severe alveolar interstitial syndrome (3d), EUGR, days of caffeine treatment, total days of oxygen inhalation and LMR can better predict the occurrence of BPD in premature infants.
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