Key result
A predictive scoring system identified unstable carotid plaques in individuals at high risk of stroke with an AUC of 0.738 in the derivation set and 0.737 in the validation set.
Why the study?
Existing asymptomatic carotid stenosis models rarely focus on individuals with lower levels of stenosis or unstable plaques who might benefit from early interventions.
Can a predictive scoring system identify unstable carotid plaques in individuals with high risk of stroke?
Observational (n=2,841)
Yes
Can a predictive scoring system identify unstable carotid plaques in individuals with high risk of stroke?
Effect estimate: AUC 0.738
A newly developed predictive scoring system can help identify individuals at high risk of stroke who are likely to have unstable carotid plaques, guiding the targeted use of carotid ultrasonography for primary prevention.
May help select high-risk patients for carotid ultrasonography; leaves open prospective validation before clinical adoption.
Background : Several models have been developed to predict asymptomatic carotid stenosis (ACS), however these models did not pay much attention to people with lower level of stenosis (＜50% or carotid plaques, especially instable carotid plaques) who might benefit from early interventions. Here, we developed a new model to predict unstable carotid plaques through systematic screening in population with high risk of stroke. Methods : Community residents who participated the China National Stroke Screening and Prevention Project (CNSSPP) were screened for their stroke risks. A total of 2841 individuals with high risk of stroke were enrolled in this study, 266 (9.4%) of them were found unstable carotid plaques. A total of 19 risk factors were included in this study. Subjects were randomly distributed into Derivation Set group or Validation Set group. According to their carotid ultrasonography records, subjects in derivation set group were further categorized into unstable plaque group or stable plaque group. Results : 174 cases and 1720 cases from Derivation Set group were categorized into unstable plaque group and stable plaque group respectively. The independent risk factors for carotid unstable plaque were: male (OR 1.966, 95%CI 1.406-2.749)，older age (50-59, OR 6.012, 95%CI 1.410-25.629; 60-69, OR 13.915, 95%CI 3.381-57.267;≥70, OR 31.267, 95%CI 7.472-130.83) , married(OR 1.780, 95%CI 1.186-2.672)，LDL-C(OR 2.015, 95%CI 1.443-2.814), and HDL-C(OR 2.130, 95%CI 1.360-3.338). A predictive scoring system was generated, ranging from 0-10. The cut-off value of this predictive scoring system is 6.5. The AUC value for derivation and validation set group were 0.738 and 0.737 respectively. Conclusions ：For those individuals with high risk of stroke, we developed a new model which could identify those who have a higher chance to have unstable carotid plaques. When an individual’s predictive model score exceeds 6.5, the probability of having carotid unstable plaques is high, and carotid ultrasonography should be conducted accordingly. This model could be helpful in the primary prevention of stroke.
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Yin et al. (2020) conducted an observational in High risk of stroke (n=2,841). Predictive scoring system was evaluated on Unstable carotid plaques (AUC 0.738). A predictive scoring system identified unstable carotid plaques in individuals at high risk of stroke with an AUC of 0.738 in the derivation set and 0.737 in the validation set.
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