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Construction and validation of a nomogram model to predict symptomatic intracranial hemorrhage after intravenous thrombolysis in severe white matter lesions

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Abstract

Cerebral white matter lesions (WMLs) increase the risk of bleeding after intravenous thrombolysis (IVT) but are also considered to require IVT. Its risk factors and predictive models are still poorly studied. The aim of this study is to develop a clinically applicable model for post-IVT haemorrhage. It offers the possibility to prevent symptomatic intracranial hemorrhage (sICH) in patients with IVT in severe WMLs. A large single-center observational study conducted a retrospective analysis of IVT in patients with severe WMLs from January 2018 to December 2022. Univariate and multi-factor logistic regression results were used to construct nomogram model, and a series of validations were performed on the model. More than 2,000 patients with IVT were screened for inclusion in this study after cranial magnetic resonance imaging evaluation of 180 patients with severe WMLs, 28 of whom developed sICH. In univariate analysis, history of hypertension (OR 3.505 CI 2.257–4.752, p = 0.049), hyperlipidemia (OR 4.622 CI 3.761- 5.483, p < 0.001), the NIHSS score before IVT (OR 41.250 CI 39.212–43.288, p < 0.001), low-density lipoprotein levels (OR 1.995 CI 1.448–2.543, p = 0.013), cholesterol levels (OR 1.668 CI 1.246–2.090, p = 0.017), platelet count (OR 0.992 CI 0.985–0.999, p = 0.028), systolic blood pressure (OR 1.044 CI 1.022–1.066, p < 0.001), diastolic blood pressure (OR 1.047 CI 1.024–1.070, p < 0.001) were significantly associated with sICH. In a multifactorial analysis, the NIHSS score before IVT (OR 94.743 CI 92.311–97.175, p < 0.001), and diastolic blood pressure (OR 1.051 CI 1.005–1.097, p = 0.033) were considered to be significantly associated with sICH after IVT as risk factors for the occurrence of sICH. The four most significant factors from logistic regression are subsequently fitted to create a predictive model. The accuracy was verified using ROC curves, calibration curves, decision curves, and clinical impact curves, and the model was considered to have high accuracy (AUC 0.932, 95% 0.888–0.976). The NHISS score before IVT and diastolic blood pressure are independent risk factors for sICH after IVT in patients with severe WMLs. The models based on hyperlipidemia, the NIHSS score before IVT, low-density lipoprotein and diastolic blood pressure are highly accurate and can be applied clinically to provide a reliable predictive basis for IVT in patients with severe WMLs.

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All relevant data are described within the paper. Deidentified data can be requested. Data can be requested by all interested researchers, who can be contacted via the corresponding author.

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Funding

The work was supported by the National Natural Science Foundation of China (No.81460199, 82160252 and 82271439), Natural Science Foundation of Jiangxi province (20202BAB206029 and 20224ACB206015), Science and technology project of Jiangxi Health Commission (202110028), and Double thousand talents program of Jiangxi province (jxsq2019101021).

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Authors and Affiliations

  1. Department of Neurology, The First Affiliated Hospital of Nanchang University, Yong Wai Zheng Street 17#, Nanchang, 330006, People’s Republic of China

    Yu Shen, Ying Xiong, LuLu Wang, YiRong Yang & Daojun Hong

  2. Department of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, China

    Qian Cao, YanPing Li & WenWen Xiang

  3. Department of Gerontology, Nanchang First Hospital, Nanchang, China

    Quirui Nie

  4. Department of Neurology, Xiamen Fifth People’s Hospital, Xiamen, China

    BoJi Tang

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  1. Yu Shen
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  2. Ying Xiong
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  3. Qian Cao
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  4. YanPing Li
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  6. LuLu Wang
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  7. Quirui Nie
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  10. Daojun Hong
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Contributions

YS and DH designed this study and wrote the initial draft of this paper. YS, YX and QC contributed to the analysis and interpretation of data and assisted in the preparation of this paper. YS, QC, WX, BT, YX, LW, YY and NQ contributed to data collection and interpretation of this paper. All of the authors approved the final version of this paper and agree to be accountable for all aspects of this paper. DH is the guarantor.

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Correspondence to Daojun Hong.

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The authors have declared no conflicts of interest.

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The research was approved by ethics committee of the second affiliated hospital of Nanchang University (No. [2016] 096).

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Shen, Y., Xiong, Y., Cao, Q. et al. Construction and validation of a nomogram model to predict symptomatic intracranial hemorrhage after intravenous thrombolysis in severe white matter lesions. J Thromb Thrombolysis 56, 111–120 (2023). https://doi.org/10.1007/s11239-023-02828-4

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  • DOI: https://doi.org/10.1007/s11239-023-02828-4

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