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Related Experiment Video

Updated: Jan 9, 2026

The Rabbit Blood-shunt Model for the Study of Acute and Late Sequelae of Subarachnoid Hemorrhage: Technical Aspects

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Published on: October 2, 2014

Predicting Shunt-Dependency After Aneurysmal Subarachnoid Hemorrhage: A Multicenter Validation Study.

Maryam Said^1,2, Christoph Wipplinger^3,4, Andrea Cattaneo³

¹Department of Neurosurgery, Evangelisches Krankenhaus Oldenburg, Carl von Ossietzky University Oldenburg, 26129 Oldenburg, Germany.

Journal of Clinical Medicine

|December 11, 2025

Summary

This study validated risk scores for predicting shunt dependency after aneurysmal subarachnoid hemorrhage (aSAH). The CHESS-Huckman score showed the highest accuracy, aiding early identification of patients needing shunts.

Keywords:

hydrocephalus prediction shunt scores subarachnoid hemorrhage

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Endovascular Perforation Model for Subarachnoid Hemorrhage Combined with Magnetic Resonance Imaging MRI

Endovascular Perforation Model for Subarachnoid Hemorrhage Combined with Magnetic Resonance Imaging MRI

Published on: December 16, 2021

Area of Science:

Neurosurgery
Neurology
Clinical Epidemiology

Background:

Clinical utility of risk scores for shunt dependency post-aneurysmal subarachnoid hemorrhage (aSAH) is limited by scarce validation data.
This study aimed to validate existing post-aSAH shunt risk scores using a multicenter pooled analysis.

Purpose of the Study:

To assess the predictive accuracy of established risk scores (CHESS, CHESS-Huckman, SDASH) for shunt dependency in aSAH patients.
To compare the diagnostic performance of these risk scores through receiver operating characteristic (ROC) curve analysis.

Main Methods:

Pooled analysis of consecutive aSAH cases from two German university hospitals (January 2010 - July 2023).
Calculation of total scores for CHESS, CHESS-Huckman, and SDASH risk models.
Comparison of diagnostic performance using ROC curve analysis and calibration metrics.

Main Results:

813 aSAH patients were included; 26.4% required ventriculoperitoneal shunt placement.
CHESS-Huckman score demonstrated the highest predictive accuracy (AUC: 0.792), followed by SDASH (0.782) and CHESS (0.780).
All scores showed good calibration; CHESS-Huckman performed best. Higher scores correlated with earlier shunting.

Conclusions:

Existing risk scores, particularly CHESS-Huckman, are validated for predicting shunt dependency after aSAH.
Clinical integration of these scores can improve early identification of patients requiring shunting.
This may lead to reduced external ventricular drain weaning times, shorter hospital stays, and fewer CSF infections.