Value of Multimodal Ultrasonography Combined with Clinical Indicators in Predicting the Progression of Ischemic Stroke

Li DONG; Rongping NING; Qiongyi XIAO

doi:10.12259/j.issn.2095-610X.S20240325

Volume 45 Issue 3

Mar. 2024

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Article Navigation > Journal of Kunming Medical University > 2024 > 45(3): 166-173

Li DONG, Rongping NING, Qiongyi XIAO. Value of Multimodal Ultrasonography Combined with Clinical Indicators in Predicting the Progression of Ischemic Stroke[J]. Journal of Kunming Medical University, 2024, 45(3): 166-173. doi: 10.12259/j.issn.2095-610X.S20240325

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Li DONG, Rongping NING, Qiongyi XIAO. Value of Multimodal Ultrasonography Combined with Clinical Indicators in Predicting the Progression of Ischemic Stroke[J]. Journal of Kunming Medical University, 2024, 45(3): 166-173. doi: 10.12259/j.issn.2095-610X.S20240325

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Value of Multimodal Ultrasonography Combined with Clinical Indicators in Predicting the Progression of Ischemic Stroke

doi: 10.12259/j.issn.2095-610X.S20240325

1.
Dept. of Ultrasound Medical Imaging
2.
Dept. of Emergency Medicine，The 3rd People’s Hospital of Yunnan Province，Kunming Yunnan 650011，China

Received Date: 2023-12-13
Publish Date: 2024-03-25

Abstract

Abstract

Objective To investigate the clinical value of multimodal ultrasonography combined with clinical indicators in predicting the progression of ischemic stroke （IS）. Methods A total of 134 patients with IS admitted to Third People's Hospital of Yunnan Province from January 2020 to October 2022 were selected as study objects and were divided into progressive ischemic stroke （PIS） group （n=20） and non-progressive ischemic stroke （NPIS） group （n=114） according to the National Institutes of Health Stroke Scale （NIHSS） score. The clinical indicators, multi-modal ultrasonic image manifestations and related parameters of the two groups were counted, the influencing factors of PIS were screened by Logistics, the nomogram model was drawn, and the predictive efficiency of the nomogram model was evaluated by ROC curve and calibration curve. Results There were significant differences in age, baseline nutritional risk index （GNRI） score, baseline homocysteine （Hcy） and baseline uric acid （UA） between the two groups （P < 0.05）. The peak time （TTP）, peak intensity （PI）, the area under the curve （AUC）, carotid plaque enhancement mode, the mean value of maximum elastic modulus （MEmax） and mean value of minimum elastic modulus （MEmin） were compared between the two groups, and the differences were statistically significant （ P < 0.05）. Logistic analysis showed that baseline GNRI score, baseline UA, TTP, PI, AUCTC, carotid plaque enhancement pattern, MEmax and MEmin were the influencing factors of PIS （ P< 0.05）. Based on the above factors, the nomogram model was drawn. ROC curve and calibration curve showed that the model had good prediction efficiency, and the prediction efficiency was in good agreement with the reality. Conclusion The influencing factors of PIS include baseline GNRI score, baseline UA, TTP, PI, AUCTC, carotid plaque enhancement pattern, MEmax, MEmin, and the neagram model based on the above factors has good differentiation and accuracy.
- Multimodal ultrasound image,
- Clinical index,
- Carotid artery plaque,
- Ischemic stroke,
- Neurological impairment,
- Quantitative parameter

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