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. 2025 Sep 11:12:1606892.
doi: 10.3389/fmed.2025.1606892. eCollection 2025.

Diagnostic prediction of neonatal hyperbilirubinemia combined with germinal matrix-intraventricular hemorrhage based on cranial ultrasound hemodynamics: a retrospective case-control study

Zhaolan Ye #  1   2   3 , Xiang Chen #  1   2   3 , Daoming Wu  1   2   3 , Jiantao Lin  1   2   3 , Lihua Zhang  1   2   3
Affiliations

Diagnostic prediction of neonatal hyperbilirubinemia combined with germinal matrix-intraventricular hemorrhage based on cranial ultrasound hemodynamics: a retrospective case-control study

Zhaolan Ye et al. Front Med (Lausanne). .

Abstract

Objective: To study the diagnostic prediction of cranial ultrasound hemodynamics in children with neonatal hyperbilirubinemia combined with germinal matrix-intraventricular hemorrhage (GMH-IVH).

Methods: We included 148 hyperbilirubinemic neonates who underwent cranial ultrasound to obtain hemodynamic parameter indexes, and constructed a nomogram visual prediction model through unifactorial and multifactorial analyses to study the role of cranial ultrasound hemodynamic parameters in the diagnostic prediction of neonatal hyperbilirubinemia combined with GMH-IVH.

Results: A total of 148 patients eligible for enrollment were included in this study, of which 40 children developed GMH-IVH, with an incidence rate of 27.03%. Multifactorial logistic stepwise regression analysis showed that mothers suffering from gestational hypertension, total bilirubin ≥15 mg/dl, anterior cerebral artery third day to first day resistance index ratio of ≥1, and middle cerebral artery third day to first day resistance index ratio of ≥1 were the independent risk factors for the development of GMH-IVH in neonatal hyperbilirubinemic infants (P < 0.05); and ROC analysis showed that the area under the ROC curve (AUC) of the prediction model was 0.821 (95% CI: 0.746-0.897, P < 0.001), indicating good predictive efficacy of the model (discrimination), and the Hosmer-Lemeshow test (χ2 = 7.779, P = 0.255) and the calibration curve showed that the model had a good goodness-of-fit (calibration). The predictive model was visualized by plotting nomogram.

Conclusion: Craniocerebral ultrasound hemodynamics-related parameters combined with clinical features to construct a predictive model for early and effective prediction of the occurrence and prognosis of GMH-IVH in neonates with hyperbilirubinemia.

Keywords: cranial ultrasound hemodynamics; germinal matrix-intraventricular hemorrhage; neonatal hyperbilirubinemia; nomogram; prediction.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Forest plot illustrating odds ratios (OR) with 95% confidence intervals (CI) for various variables. Variables include mothers with gestational hypertension (OR: 3.82, 95% CI: 1.1-13.32, p = 0.035), TBIL ≥ 15mg/dL (OR: 2.73, 95% CI: 1.07-6.98, p = 0.036), ACA_RId3/RId1≥1 (OR: 3.37, 95% CI: 1.33-8.53, p = 0.010), and MCA_RId3/RId1≥1 (OR: 3.23, 95% CI: 1.26-8.27, p = 0.015). Green squares represent the OR values, and horizontal lines indicate the confidence intervals.
FIGURE 1
Forest plot of multivariate analysis for GMH-IVH.
Receiver Operating Characteristic (ROC) curve with sensitivity on the y-axis and specificity on the x-axis. The red dashed curve shows performance with an Area Under the Curve (AUC) of 0.821 and a 95% confidence interval of 0.746 to 0.897. A diagonal gray dashed line represents random performance.
FIGURE 2
ROC curve of the GMH-IVH prediction model.
Calibration plot showing actual versus predicted probabilities. The X-axis represents predicted probability, and the Y-axis represents actual probability. The plot includes three lines: a gray ideal line for perfect calibration, a solid line for logistic calibration, and a dotted line for nonparametric calibration. The logistic calibration line closely follows the ideal line, indicating good model performance.
FIGURE 3
Calibration curve of the GMH-IVH prediction model.
Chart presenting a point system for diagnosing the likelihood of GMH-IVH. It includes factors like gestational hypertension, TBIL levels over 15 mg/dl, ACA_RId3/RId1, and MCA_RId3/RId1 ratios greater than 1. Each factor is associated with points and affects the diagnostic probability. The horizontal axis shows points ranging from zero to four hundred and diagnostic possibilities from zero to 0.9.
FIGURE 4
Nomogram for the diagnostic probability of GMH-IVH.
See this image and copyright information in PMC

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