Prediction of neonatal sepsis in Hakka population: PCT time interval analysis and nomogram model incorporating perinatal factors and disease characteristics
Objective This study aimed to develop a predictive model for neonatal sepsis by analyzing procalcitonin (PCT) levels measured across different age-specific time intervals in the Hakka population, while integrating maternal perinatal factors and neonatal disease characteristics.Methods A retrospectiv...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | The Journal of Maternal-Fetal & Neonatal Medicine |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/14767058.2025.2532091 |
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| Summary: | Objective This study aimed to develop a predictive model for neonatal sepsis by analyzing procalcitonin (PCT) levels measured across different age-specific time intervals in the Hakka population, while integrating maternal perinatal factors and neonatal disease characteristics.Methods A retrospective analysis was conducted on 13,884 neonates, encompassing both sepsis and non-sepsis cases, to systematically evaluate the predictive capability of PCT across different time intervals, focusing on the first week of life and beyond (up to [7, 8) days). Logistic regression analysis, incorporating categorized PCT levels, maternal perinatal factors, and neonatal disease characteristics, was utilized to develop a nomogram model for predicting sepsis.Results Elevated PCT levels were significantly associated with an increased risk of neonatal sepsis (OR = 13.59, 95% CI: 9.01–20.50, p < 0.001) during the 2–3 day period. During this period, the area under the curve (AUC) for PCT was 0.853 (95% CI: 0.840–0.866), indicating strong predictive performance. The developed nomogram model achieved an AUC of 0.82 and an accuracy of 0.88 in the training set, effectively distinguishing between high- and low-risk sepsis cases.Conclusion This study confirms the critical role of PCT in the early diagnosis of neonatal sepsis and proposes a time-sensitive predictive model specifically tailored to the Hakka population, offering clinicians a personalized risk assessment tool. Nonetheless, further external validation is required to fully establish the clinical applicability of this model. |
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| ISSN: | 1476-7058 1476-4954 |