A novel risk score to predict deep vein thrombosis after spontaneous intracerebral hemorrhage

Ruijun Ji; Linlin Wang; Xinyu Liu; Yanfang Liu; Dandan Wang; Wenjuan Wang; Runhua Zhang; Ruixuan Jiang; Jiaokun Jia; Hao Feng; Zeyu Ding; Yi Ju; Jingjing Lu; Gaifen Liu; Yongjun Wang; Xingquan Zhao; Beijing Registration of Intracerebral Hemorrhage investigators

doi:10.3389/fneur.2022.930500

A novel risk score to predict deep vein thrombosis after spontaneous intracerebral hemorrhage

Front Neurol. 2022 Oct 28:13:930500. doi: 10.3389/fneur.2022.930500. eCollection 2022.

Authors

Ruijun Ji^{1

2

3

4

5}, Linlin Wang¹, Xinyu Liu¹, Yanfang Liu^{1

2}, Dandan Wang^{1

2}, Wenjuan Wang^{1

2}, Runhua Zhang^{1

2}, Ruixuan Jiang^{1

2}, Jiaokun Jia^{1

2}, Hao Feng^{1

2}, Zeyu Ding^{1

2}, Yi Ju^{1

2}, Jingjing Lu^{1

2}, Gaifen Liu^{1

2}, Yongjun Wang^{1

2

3

4

5}, Xingquan Zhao^{1

2

3

4

5}; Beijing Registration of Intracerebral Hemorrhage investigators

Affiliations

¹ Department of Neurology, Tiantan Hospital, Capital Medical University, Beijing, China.
² China National Clinical Research Center for Neurological Diseases, Beijing, China.
³ Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.
⁴ Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China.
⁵ Beijing Key Laboratory of Brain Function Reconstruction, Beijing, China.

Abstract

Background and purpose: Studies showed that patients with hemorrhagic stroke are at a higher risk of developing deep vein thrombosis (DVT) than those with ischemic stroke. We aimed to develop a risk score (intracerebral hemorrhage-associated deep vein thrombosis score, ICH-DVT) for predicting in-hospital DVT after ICH.

Methods: The ICH-DVT was developed based on the Beijing Registration of Intracerebral Hemorrhage, in which eligible patients were randomly divided into derivation (60%) and internal validation cohorts (40%). External validation was performed using the iMCAS study (In-hospital Medical Complication after Acute Stroke). Independent predictors of in-hospital DVT after ICH were obtained using multivariable logistic regression, and β-coefficients were used to generate a scoring system of the ICH-DVT. The area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess model discrimination and calibration, respectively.

Results: The overall in-hospital DVT after ICH was 6.3%, 6.0%, and 5.7% in the derivation (n = 1,309), internal validation (n = 655), and external validation (n = 314) cohorts, respectively. A 31-point ICH-DVT was developed from the set of independent predictors including age, hematoma volume, subarachnoid extension, pneumonia, gastrointestinal bleeding, and length of hospitalization. The ICH-DVT showed good discrimination (AUROC) in the derivation (0.81; 95%CI = 0.79-0.83), internal validation (0.83, 95%CI = 0.80-0.86), and external validation (0.88; 95%CI = 0.84-0.92) cohorts. The ICH-DVT was well calibrated (Hosmer-Lemeshow test) in the derivation (P = 0.53), internal validation (P = 0.38), and external validation (P = 0.06) cohorts.

Conclusion: The ICH-DVT is a valid grading scale for predicting in-hospital DVT after ICH. Further studies on the effect of the ICH-DVT on clinical outcomes after ICH are warranted.

Keywords: calibration; deep vein thrombosis; discrimination; intracerebral hemorrhage; risk model.