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Hematology

Prediction Score for Clinical Outcome of Chinese Patients with Cerebral Venous Thrombosis

, , , &
Pages 4099-4107 | Received 16 Jun 2023, Accepted 04 Sep 2023, Published online: 11 Sep 2023

Figures & data

Table 1 The Detailed Data of Reported Prognostic Markers in Chinese CVT Patients

Table 2 Univariate Logistic Regression Between Reported Prognostic Markers at Baseline and the Clinical Outcome at the 6-Month Follow-Up in Chinese CVT Patients

Figure 1 Analysis of the ROC curve to determine cut-off values. The ROC analysis was utilized to identify the cut-off values for age (A), DBP (B), CRP (C), NLR (D), and NSE (E).

Figure 1 Analysis of the ROC curve to determine cut-off values. The ROC analysis was utilized to identify the cut-off values for age (A), DBP (B), CRP (C), NLR (D), and NSE (E).

Table 3 Multivariate Logistic Regression Between Identified Prognostic Markers at Baseline and the Clinical Outcome at the 6-Month Follow-Up in Chinese CVT Patients

Table 4 Determination of CVT Outcome Score for Chinese Patients

Figure 2 Validation of the CVT outcome score. (A) The CVT outcome score at baseline exhibited a positive correlation with mRS at a 6-month follow-up period. (B) A CVT outcome score of 3.5 was identified as a cut-off value to predict the clinical outcome of CVT. (C) Patients with a CVT risk score greater than 3 displayed a significantly higher mRS score compared to those with scores less than or equal to 3. *P<0.05.

Figure 2 Validation of the CVT outcome score. (A) The CVT outcome score at baseline exhibited a positive correlation with mRS at a 6-month follow-up period. (B) A CVT outcome score of 3.5 was identified as a cut-off value to predict the clinical outcome of CVT. (C) Patients with a CVT risk score greater than 3 displayed a significantly higher mRS score compared to those with scores less than or equal to 3. *P<0.05.