Dataset Information

Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis.

ABSTRACT:

Objective

This study aims to establish the predictive model of carotid plaque formation and carotid plaque location by retrospectively analyzing the clinical data of subjects with carotid plaque formation and normal people, and to provide technical support for screening patients with carotid plaque.

Methods

There were 4300 subjects in the ultrasound department of Maanshan People's Hospital collected from December 2013 to December 2018. We used demographic and biochemical data from 3700 subjects to establish predictive models for carotid plaque and its location. The leave-one-out cross-validated classification, 600 external data validation, and area under the receiver operating characteristic curve (AUC) were used to verify the accuracy, sensitivity, specificity, and application value of the model.

Results

There were significant difference of age (F = - 34.049, p < 0.01), hypertension (χ² = 191.067, p < 0.01), smoking (χ² = 4.762, p < 0.05) and alcohol (χ² = 8.306, p < 0.01), Body mass index (F = 15.322, p < 0.01), High-density lipoprotein (HDL) (F = 13.840, p < 0.01), Lipoprotein a (Lp a) (F = 52.074, p < 0.01), Blood Urea Nitrogen (F = 2.679, p < 0.01) among five groups. Prediction models were built: carotid plaque prediction model (Model CP); Prediction model of left carotid plaque only (Model CP Left); Prediction model of right carotid plaque only (Model CP Right). Prediction model of bilateral carotid plaque (Model CP Both). Model CP (Wilks' lambda = 0.597, p < 0.001, accuracy = 78.50%, sensitivity = 78.07%, specificity = 79.07%, AUC = 0.917). Model CP Left (Wilks' lambda = 0.605, p < 0.001, accuracy = 79.00%, sensitivity = 86.17%, specificity = 72.70%, AUC = 0.880). Model CP Right (Wilks' lambda = 0.555, p < 0.001, accuracy = 83.00%, sensitivity = 81.82%, specificity = 84.44%, AUC = 0.880). Model CP Both (Wilks' lambda = 0.651, p < 0.001, accuracy = 82.30%, sensitivity = 89.50%, specificity = 72.70%, AUC = 0.880).

Conclusion

Demographic characteristics and blood biochemical indexes were used to establish the carotid plaque and its location discriminant models based on Fisher discriminant analysis (FDA), which has high application value in community screening.

SUBMITTER: Hu J

PROVIDER: S-EPMC9377085 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Publications

Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis.

Hu Jian J Su Fan F Ren Xia X Cao Lei L Zhou Yumei Y Fu Yuhan Y Tatenda Grace G Jiang Mingfei M Wu Huan H Wen Yufeng Y

BMC cardiovascular disorders 20220815 1

<h4>Objective</h4>This study aims to establish the predictive model of carotid plaque formation and carotid plaque location by retrospectively analyzing the clinical data of subjects with carotid plaque formation and normal people, and to provide technical support for screening patients with carotid plaque.<h4>Methods</h4>There were 4300 subjects in the ultrasound department of Maanshan People's Hospital collected from December 2013 to December 2018. We used demographic and biochemical data from ...[more]

PMID: 35965318

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Project description:Background and purposeCarotid intraplaque hemorrhage is associated with stroke, plaque thickness, stenosis, ulceration, and adventitial inflammation. Conflicting data exist on whether calcification is a marker of plaque instability, and no data exist on adventitial calcification. Our goal was to determine whether adventitial calcification and soft plaque (a rim sign) help predict carotid intraplaque hemorrhage.Materials and methodsThis was a retrospective cohort study of 96 patients who underwent carotid MRA and CTA within 1 month, from 2009 to 2016. We excluded occlusions (n = 4) and near occlusions (n = 0), leaving 188 carotid arteries. Intraplaque hemorrhage was detected by using MPRAGE. Calcification, adventitial pattern, stenosis, maximum plaque thickness (total, soft, and hard), ulceration, and intraluminal thrombus on CTA were recorded. Atherosclerosis risk factors and medications were recorded. We used mixed-effects multivariable Poisson regression, accounting for 2 vessels per patient. For the final model, backward elimination was used with a threshold of P < .10. Receiver operating characteristic analysis determined intraplaque hemorrhage by using the area under the curve.ResultsOur final model included the rim sign (prevalence ratio = 11.9, P < .001) and maximum soft-plaque thickness (prevalence ratio = 1.2, P = .06). This model had excellent intraplaque hemorrhage prediction (area under the curve = 0.94), outperforming the rim sign, maximum soft-plaque thickness, NASCET stenosis, and ulceration (area under the curve = 0.88, 0.86, 0.77, and 0.63, respectively; P < .001). Addition of the rim sign performed better than each marker alone, including maximum soft-plaque thickness (area under the curve = 0.94 versus 0.86, P < .001), NASCET stenosis (area under the curve = 0.90 versus 0.77, P < .001), and ulceration (area under the curve = 0.90 versus 0.63, P < .001).ConclusionsThe CTA rim sign of adventitial calcification with internal soft plaque is highly predictive of carotid intraplaque hemorrhage.

Project description:BackgroundResearch has shown that carotid intima-media thickness (CIMT) could help to predict carotid plaque (CP) progression in patients with mild carotid stenosis. However, the debate continues as to the value of carotid intima thickness (CIT) in monitoring the development of CP in patients with severe carotid stenosis. This study sought to evaluate the relationships between CIT and the ultrasonic characteristics of CP and to analyze the value of CIT and the ultrasonic parameters of CP in assessing plaque vulnerability in advanced human carotid atherosclerosis.MethodsA total of 55 individuals who underwent carotid endarterectomy (CEA) were included in the study (mean age: 65±7 years; female: 9.1%). CIMT and CIT were examined at the common carotid artery (CCA). Plaque textural features, such as the gray-scale median (GSM), superb microvascular imaging (SMI) level, and total plaque area (TPA), were also identified. A Spearman correlation coefficient analysis was performed to examine the relationship between CIT and the ultrasonic parameters of CP. The CIT of various plaque types was compared. Receiver operating characteristic (ROC) curves were used to analyze the diagnostic values of the ultrasound characteristics to evaluate CP vulnerability.ResultsThe mean CIT of all the participants was 0.382±0.095 mm, the mean CIT of the participants with stable plaques was 0.328±0.031 mm, and the mean CIT of participants with vulnerable plaques was 0.424±0.106 mm (P<0.001). CIT was associated with the SMI level (Spearman's correlation coefficient: r=0.392, P=0.005), TPA (Spearman's correlation coefficient: r=0.337, P=0.012). Patients with thicker CIT had larger lipid cores, higher levels of plaque vulnerability, and more intraplaque hemorrhages (IPHs). The areas under the ROCs (AUCs) with 95% confidence interval (CI) for CIMT, CIT, the SMI level, the GSM, the TPA, and the combined model for identifying vulnerable plaques were 0.673 (0.533-0.793), 0.849 (0.727-0.932), 0.771 (0.629-0.879), 0.669 (0.529-0.790), 0.858 (0.738-0.938), and 0.949 (0.854-0.990), respectively.ConclusionsCIT was associated with both the histology and ultrasonic features of CP. CIT may be helpful in the detection of severe CP development.

Dataset Information

Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis.

Objective

Methods

Results

Conclusion

Publications

Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis.

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