Constructing a predictive model for the risk of periventricular leukomalacia in very low birth weight premature infants based on Lasso-Logistic regression analysis
Faxiu Duan, LiZhen Ling, Lijuan Liao · 2026
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Description
Faxiu Duan, LiZhen Ling, and Lijuan Liao published this 2026 study building a risk calculator for a white-matter brain injury of premature babies. Periventricular leukomalacia threatens very low birth weight infants, and early warning would help target protection. Records of 248 infants formed the model, with 106 later babies held back to verify it.
Overall about 24 percent of the infants developed the injury. A two-stage regression picked six predictors: the one-minute Apgar score protected, while inflammation markers, lung distress syndrome, sepsis, a lingering heart duct, and womb inflammation each raised risk sharply. Drawn as a nomogram, the model scored well on accuracy checks and decision-curve tests of clinical usefulness. The authors offer it as a bedside aid, pending wider validation.
Catalog record
| CREATOR | Faxiu Duan, LiZhen Ling, Lijuan Liao |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 20 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |