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A 90-Day Prognostic Model Based on the Early Brain Injury Indicators after Aneurysmal Subarachnoid Hemorrhage: the TAPS Score

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Abstract

This study aimed to establish a new scoring model based on the early brain injury (EBI) indicators to predict the 90-day functional outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH). We retrospectively enrolled 825 patients and prospectively enrolled 108 patients with aSAH who underwent surgical clipping or endovascular coiling (derivation cohort = 640; validation cohort = 185; prospective cohort = 108) in our institute. We established a logistic regression model based on independent risk factors associated with 90-day unfavorable outcomes. The discrimination of the prognostic model was assessed by the area under the curve in a receiver operating characteristic curve analysis. The Hosmer–Lemeshow goodness-of-fit test and a calibration plot were used to evaluate the calibration of the prediction model. The developed scoring model named “TAPS” (total score, 0–7 points) included the following admission variables: age > 55 years old, WFNS grade of 4–5, mFS grade of 3–4, Graeb score of 5–12, white blood cell count > 11.28 × 109/L, and surgical clipping. The model showed good discrimination with the area under the curve in the derivation, validation, and prospective cohorts which were 0.816 (p < 0.001, 95%CI = 0.77–0.86), 0.810 (p < 0.001, 95%CI = 0.73–0.90), and 0.803 (p < 0.001, 95%CI = 0.70–0.91), respectively. The model also demonstrated good calibration (Hosmer–Lemeshow goodness-of-fit test: X2 = 1.75, df = 8, p = 0.988). Compared with other predictive models, TAPS is an easy handle tool for predicting the 90-day unfavorable outcomes of aSAH patients, which can help clinicians better understand the concept of EBI and quickly identify those patients at risk of poor prognosis, providing more positive treatment strategies. Trial registration: NCT04785976. Registered 5 March 2021-retrospectively registered, http://www.clinicaltrials.gov.

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Data Availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

We acknowledge the contribution of all staff who participated in the present study.

Funding

This study was supported by the National Key Research and Development Program of China (Grant Nos. 2021YFC2501101 and 2020YFC2004701) and the National Natural Science Foundation of China (Grant Nos. 82071296, 81671129, and 81471210).

Author information

Authors and Affiliations

  1. Department of Neurosurgery, Fengtai District, Beijing Tiantan Hospital, Capital Medical University, No. 119 South Fourth Ring West Road, Beijing, 100070, China

    Runting Li, Fa Lin, Yu Chen, Junlin Lu, Heze Han, Li Ma, Yahui Zhao, Debin Yan, Ruinan Li, Jun Yang, Shihao He, Zhipeng Li, Haibin Zhang, Kexin Yuan, Ke Wang, Qiang Hao, Xun Ye, Hao Wang, Shuo Wang, Xiaolin Chen & Yuanli Zhao

  2. Department of Critical Care Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

    Hongliang Li, Linlin Zhang, Guangzhi Shi & Jianxin Zhou

  3. Department of Neurosurgery, Peking University International Hospital, Beijing, China

    Yang Zhao, Yukun Zhang & Yuanli Zhao

  4. Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

    Youxiang Li

  5. China National Clinical Research Center for Neurological Diseases, Beijing, China

    Shuo Wang & Yuanli Zhao

  6. Stroke Center, Beijing Institute for Brain Disorders, Beijing, China

    Shuo Wang, Xiaolin Chen & Yuanli Zhao

  7. Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China

    Shuo Wang, Xiaolin Chen & Yuanli Zhao

Authors
  1. Runting Li
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  2. Fa Lin
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  3. Yu Chen
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  4. Junlin Lu
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  6. Li Ma
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  8. Debin Yan
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  9. Ruinan Li
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  10. Jun Yang
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  11. Shihao He
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  12. Zhipeng Li
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  15. Ke Wang
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  16. Qiang Hao
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  17. Xun Ye
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  18. Hao Wang
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  19. Hongliang Li
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  20. Linlin Zhang
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  21. Guangzhi Shi
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  22. Jianxin Zhou
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  23. Yang Zhao
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  24. Yukun Zhang
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  25. Youxiang Li
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  27. Xiaolin Chen
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  28. Yuanli Zhao
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Contributions

Runting Li: conceptualization (equal); data curation (lead); formal analysis (lead); investigation (lead); methodology (equal); project administration (equal); software (lead); validation (lead); visualization (lead); writing original draft (lead); and writing review and editing (equal). Fa Lin: data curation (equal); methodology (equal); and software (equal). Yu Chen: data curation (equal); methodology (equal); and software (equal). Junlin Lu: data curation (equal); methodology (equal); and software (equal). Heze Han: data curation (equal); methodology (equal); and software (equal). Li Ma: data curation (equal). Yahui Zhao: data curation (equal). Debin Yan: data curation (equal). Ruinan Li: data curation (equal). Jun Yang: data curation (equal). Shihao He: data curation (equal). Zhipeng Li: data curation (equal). Haibin Zhang: data curation (equal). Kexin Yuan: data curation (equal). Ke Wang: data curation (equal). Qiang Hao: data curation (equal) and supervision (equal). Xun Ye: data curation (equal) and supervision (equal). Hao Wang: data curation (equal) and supervision (equal). Hongliang Li: data curation (equal) and supervision (equal). Linlin Zhang: data curation (equal) and supervision (equal). Guangzhi Shi: data curation (equal) and supervision (equal). Jianxin Zhou: data curation (equal) and supervision (equal). Yang Zhao: data curation (equal); resources (equal); and supervision (equal). Yukun Zhang: data curation (equal); resources (equal); and supervision (equal). Youxiang Li: data curation (equal); resources (equal); and supervision (equal). Shuo Wang: conceptualization (equal); funding acquisition (equal); resources (equal); supervision (equal); and writing review and editing (equal). Xiaolin Chen: conceptualization (equal); funding acquisition (equal); resources (equal); supervision (equal); and writing review and editing (equal). Yuanli Zhao: conceptualization (equal); resources (equal); supervision (equal); and writing review and editing (equal).

Corresponding author

Correspondence to Xiaolin Chen.

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Ethics Approval and Consent to Participate

This study was approved by the Institutional Review Board of the Beijing Tiantan Hospital (KY 2021–008-01). Informed consent was obtained from all individual participants or their authorized representatives included in the study. All the analyses were performed in accordance with the Declaration of Helsinki and the local ethics policies.

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The authors declare no competing interests.

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Li, R., Lin, F., Chen, Y. et al. A 90-Day Prognostic Model Based on the Early Brain Injury Indicators after Aneurysmal Subarachnoid Hemorrhage: the TAPS Score. Transl. Stroke Res. 14, 200–210 (2023). https://doi.org/10.1007/s12975-022-01033-4

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