Bimodal ultrasound assessment of cerebral hemodynamics in preterm infants stratified by maternal immunotherapy: implications for early prediction of intraventricular hemorrhage - Summary - MDSpire

Bimodal ultrasound assessment of cerebral hemodynamics in preterm infants stratified by maternal immunotherapy: implications for early prediction of intraventricular hemorrhage

  • By

  • Na Wu

  • Rui Cao

  • July 14, 2026

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Objective:

To evaluate the clinical value of bedside bimodal ultrasound in assessing early cerebral circulation in preterm infants and examine associations with maternal recurrent spontaneous abortion (RSA) and neonatal cerebral hemodynamic trajectories.

Approach:
  • Study Design: Single-center prospective cohort study involving 120 preterm infants born to mothers with recurrent spontaneous abortion (RSA), stratified by maternal immunotherapy status.
  • Methods: Bedside bimodal ultrasound (transcranial Doppler and optic nerve sheath diameter measurement) was performed on postnatal days 1, 3, 5, and 7. Generalized estimating equations and multivariable logistic regression were used for analysis, with internal validation performed using bootstrap resampling.
Key Findings:
  • PI-CV and ONSD decreased during the first postnatal week in both groups (P < 0.001).
  • Significant time effects and group × time interactions for PI-CV and ONSD were observed.
  • Maternal immunotherapy was associated with faster declines in PI-CV and ONSD.
  • ONSDmax and PI-CV at 24 hours were associated with clinically significant IVH after clinical adjustment.
  • The bimodal model had an AUC of 0.759, while the expanded explanatory model had an AUC of 0.817.
Interpretation:

Bedside bimodal ultrasound is a feasible noninvasive approach for assessing early cerebral hemodynamics in preterm infants, with potential for improving early IVH risk stratification.

Limitations:
  • Observational design and associational regression models do not establish a direct protective effect of maternal immunotherapy on IVH risk.
  • No random training/validation/test split and no class-balancing procedure were used in the dataset, which may affect the generalizability of the findings.
Conclusion:

The combination of ONSDmax and PI-CV may provide insights for early IVH risk stratification, but external validation and longer-term outcome studies are necessary before clinical implementation.

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