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Objective <p>The aim of this study was to explore the independent risk factors for delayed posthemorrhagic hydrocephalus (DPH) in patients with intraventricular hemorrhage (IVH) and to construct and validate a nomogram prediction model for forecasting DPH occurrence, as well as assessing its clinical applicability.</p> Methods <p>A retrospective analysis was performed on the clinical data of 179 patients with spontaneous IVH admitted to the Department of Neurosurgery at Nanchong Central Hospital between June 2020 and June 2025. Patients were categorized into two groups on the basis of the presence or absence of DPH: the DPH group (<i>n</i> = 72) and the non-DPH group (<i>n</i> = 107). Univariate analysis was performed to identify relevant factors, followed by multivariate logistic regression to determine independent risk factors and construct a nomogram prediction model. The model’s discrimination, calibration and clinical applicability were assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).</p> Results <p>Among 179 patients, 72 (40.2%) developed DPH. Lower Glasgow Coma Scale (GCS) score at admission, higher Graeb score at admission, use of external ventricular drainage (EVD), absence of lumbar cistern drainage (LCD), and intracranial infection were associated with DPH following IVH in multivariate analysis. The model demonstrated an apparent area under the curve (AUC) of 0.879 [95% confidence interval (CI): 0.835–0.924], with a sensitivity of 0.847 and specificity of 0.861. The bootstrap-corrected calibration slope was 0.831 (95% CI: 0.323–1.268), and the Brier score was 0.143. Decision curve analysis suggested potential clinical utility across a range of threshold probabilities.</p> Conclusions <p>This study presents a preliminary, internally validated prediction model for DPH following IVH. While the model shows promising performance within the development cohort, its findings should be interpreted cautiously given the retrospective single-center design and limited sample size. Further external validation and prospective studies are required before clinical application.</p>

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Development and Internal Validation of a Preliminary Risk Prediction Model for Delayed Posthemorrhagic Hydrocephalus in Patients with Intraventricular Hemorrhage

  • 期刊论文

  • 发表日期：

    2026年6月15日

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  • Bo Luo,
  • Heng Dong,
  • Qiuguo He,
  • Haibo Ren,
  • Long Zhao,
  • Xiaoping Tang

摘要

Objective

The aim of this study was to explore the independent risk factors for delayed posthemorrhagic hydrocephalus (DPH) in patients with intraventricular hemorrhage (IVH) and to construct and validate a nomogram prediction model for forecasting DPH occurrence, as well as assessing its clinical applicability.

Methods

A retrospective analysis was performed on the clinical data of 179 patients with spontaneous IVH admitted to the Department of Neurosurgery at Nanchong Central Hospital between June 2020 and June 2025. Patients were categorized into two groups on the basis of the presence or absence of DPH: the DPH group (n = 72) and the non-DPH group (n = 107). Univariate analysis was performed to identify relevant factors, followed by multivariate logistic regression to determine independent risk factors and construct a nomogram prediction model. The model’s discrimination, calibration and clinical applicability were assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

Results

Among 179 patients, 72 (40.2%) developed DPH. Lower Glasgow Coma Scale (GCS) score at admission, higher Graeb score at admission, use of external ventricular drainage (EVD), absence of lumbar cistern drainage (LCD), and intracranial infection were associated with DPH following IVH in multivariate analysis. The model demonstrated an apparent area under the curve (AUC) of 0.879 [95% confidence interval (CI): 0.835–0.924], with a sensitivity of 0.847 and specificity of 0.861. The bootstrap-corrected calibration slope was 0.831 (95% CI: 0.323–1.268), and the Brier score was 0.143. Decision curve analysis suggested potential clinical utility across a range of threshold probabilities.

Conclusions

This study presents a preliminary, internally validated prediction model for DPH following IVH. While the model shows promising performance within the development cohort, its findings should be interpreted cautiously given the retrospective single-center design and limited sample size. Further external validation and prospective studies are required before clinical application.