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A nomogram risk prediction model for poor outcome of primary brainstem hemorrhage based on clinical data and radiographic features

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Abstract

Objective

Primary brainstem hemorrhage (PBSH) is a devastating acute neurological disorder with a poor prognosis. This study aimed to identify risk factors associated with poor outcomes in PBSH patients and develop a novel nomogram for predicting prognosis, with external validation.

Methods

A total of 379 patients with PBSH were included in the training cohort. The primary outcome of interest was a modified Rankin Scale score (mRS) of 4–6 at 90 days post-onset. Multivariable logistic regression was used to construct a nomogram based on relevant variables. Model performance was tested in the training cohort and externally validated for discriminatory ability, calibration, and clinical utility at a separate institution. The nomogram was also compared to the ICH score in terms of predictive ability.

Results

The poor outcome rate at 90 days was 57.26% (217/379) in the training cohort and 61.27% (106/173) in the validation cohort. Multivariable logistic regression analysis identified age, Glasgow Coma Scale (GCS) score, and hematoma size as significant risk factors for poor outcomes. Nomograms based on these variables demonstrated good discrimination, with an area under the curve (AUC) of 0.855 and 0.836 in the training and validation cohorts, respectively. Furthermore, the nomogram showed superior predictive value to the ICH score for the 90-day outcome in both cohorts.

Conclusion

This study developed and externally validated a nomogram risk prediction model for predicting poor outcomes at 90 days in patients with PBSH, using age, GCS score, and hematoma size as predictors. The nomogram demonstrated good discrimination, calibration, and clinical validity, serving as a valuable assessment and decision-making tool.

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Data Availability

Data is available on reasonable request.

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Funding

This study was supported by the Wuxi City Social Development Science and Technology Demonstration Project (No. N20201008).

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Author notes

  1. Yingying Ding and Yawen Xu have contributed equally to this work.

Authors and Affiliations

  1. Department of Neurosurgery, Wuxi Clinical College of Anhui Medical University, The 904Th Hospital of PLA), Wuxi, 214044, Jiangsu Province, China

    Yingying Ding, Yuhai Wang & Jirong Dong

  2. Department of Emergency Medicine, Wuxi Clinical College of Anhui Medical University, The 904Th Hospital of PLA), Wuxi, 214044, Jiangsu Province, China

    Yawen Xu

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  1. Yingying Ding
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Contributions

All authors take responsibility for the integrity and the accuracy of this manuscript. YD: study concept and design, data collection, data analysis, writing the manuscript. YX: participated in the study design, data collection. YW: participated in the study design, revised. JD: participated in the study design, revised.

Corresponding author

Correspondence to Jirong Dong.

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This study was approved by the Hospital Ethics Committee. Due to the retrospective character of this study, the requirement of informed consent was waived.

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Ding, Y., Xu, Y., Wang, Y. et al. A nomogram risk prediction model for poor outcome of primary brainstem hemorrhage based on clinical data and radiographic features. Neurol Sci 44, 3967–3978 (2023). https://doi.org/10.1007/s10072-023-06866-x

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  • DOI: https://doi.org/10.1007/s10072-023-06866-x

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