Abstract
OBJECTIVE: To develop and internally validate a model predicting neonatal mortality in infants with neonatal encephalopathy requiring therapeutic hypothermia (TH), using national data.
STUDY DESIGN: Data from 385 infants treated with TH across 19 hospitals (2016-2021) were analysed. Multivariable logistic regression with backward stepwise selection was applied. Discrimination was assessed using the C-statistic, with internal validation by bootstrapping. The THERM (Therapeutic Hypothermia Early Risk Model for Mortality) tool was developed to calculate individualised mortality risk.
RESULTS: Forty-six infants (11.9%) died within 28 days. Four predictors were retained: prelabour Caesarean section, adrenaline use, base excess ≤-22 mmol/L, and seizures during the first day of life. The model demonstrated excellent discrimination [optimism-adjusted C-statistic 0.885 (95% CI: 0.827-0.936)].
CONCLUSIONS: Four routinely collected variables predicted mortality in infants undergoing TH. The THERM tool provides a practical resource for clinicians, enabling personalised risk assessment and supporting parental counselling during the first day of life.
| Original language | English |
|---|---|
| Journal | Journal of Perinatology |
| DOIs | |
| Publication status | E-pub ahead of print - 5 Jan 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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