Development and validation of a predictive model for white matter lesions in young- and middle-aged people

Background

White matter lesion (WML) is an age-related disorder associated with stroke and cognitive impairment. This study aimed to investigate the risk factors and build a predictive model of WML in young- and middle-aged people.

Methods

We performed a second analysis of the data from the Dryad Digital Repository. We selected those people who are <60 years old and randomly divided them into the training group and the validation group. We investigated the risk factors of WML in the training group with logistic regression analysis and built a prediction nomogram based on multivariate logistic regression analysis; finally, the performance of the prediction nomogram was evaluated for discrimination, accuracy, and clinical utility.

Results

There were 308 people in the training group and 723 people in the validation group. Multivariate regression analysis showed that the age (OR = 1.49, 95% CI: 1.31-1.70), diastolic blood pressure (OR = 1.02, 95% CI: 1.00-1.03), carotid plaque score (OR = 1.31, 95% CI: 1.14-1.50), female gender (OR = 2.27, 95% CI: 1.56-3.30), and metabolic syndrome (OR = 2.12, 95% CI: 1.22-3.70) were significantly associated with white matter lesions. The area under the curve value (AUC) of the receiver operating curve (ROC) was 0.734 for the training group and 0.642 for the validation group. The calibration curve and clinical impact curve showed that the prediction nomogram has good accuracy and clinical application value.

Conclusion

Age, diastolic blood pressure, carotid plaque score, female gender, and metabolic syndrome were risk factors in young- and middle-aged people <60 years old with WML, and the nomogram based on these risk factors showed good discrimination, accuracy, and clinical utility.

Validity and Reliability of Point-of-Care Ultrasound for Detecting Moderate- or High-Grade Carotid Atherosclerosis in an Outpatient Department

The prevalence of carotid stenosis is considerably higher in asymptomatic individuals with multiple risk factors than in the general population. We investigated the validity and reliability of carotid point-of-care ultrasound (POCUS) for rapid carotid atherosclerosis screening. We prospectively enrolled asymptomatic individuals with carotid risk scores of ≥7 who underwent outpatient carotid POCUS and laboratory carotid sonography. Their simplified carotid plaque scores (sCPSs) and Handa's carotid plaque scores (hCPSs) were compared. Of 60 patients (median age, 81.9 years), 50% were diagnosed as having moderate- or high-grade carotid atherosclerosis. The overestimation and underestimation of outpatient sCPSs were more likely in patients with low and high laboratory-derived sCPSs, respectively. Bland-Altman plots indicated that the mean differences between the participants' outpatients and laboratory sCPSs were within two standard deviations of their laboratory sCPSs. A Spearman's rank correlation coefficient revealed a strong positive linear correlation between outpatient and laboratory sCPSs (r = 0.956, p < 0.001). An intraclass correlation coefficient analysis indicated excellent reliability between the two methods (0.954). Both carotid risk score and sCPS were positively and linearly correlated with laboratory hCPS. Our findings indicate that POCUS has satisfactory agreement, strong correlation, and excellent reliability with laboratory carotid sonography, making it suitable for rapid screening of carotid atherosclerosis in high-risk patients.

Predictive Value of Noninvasive Peripheral Atherosclerosis Measurement for Coronary Artery Disease in Patients with Long T2DM Duration

Objective

This study aimed to compare the predictive value of carotid or femoral artery ultrasound for coronary artery disease (CAD) in type 2 Diabetes mellitus (T2DM) patients free from known CAD, and to assess the relationship with the severity of coronary artery stenosis.

Methods

Cross-sectional study in adults with a T2DM duration of at least 5 years and without established CAD. Carotid plaque score (CPS) and Gensini score were used to measure the severity of carotid and coronary artery stenosis, respectively, and patients were divided into no or mild group, moderate group, and severe group according to the tertile of the score. Univariate and multivariate logistic regression analysis was used to explore the possible risk factors for CAD. Receiver operating characteristic (ROC) curves were created to determine the most accurate assessment for detecting significant CAD (≥50% stenosis).

Results

245 patients (137 male) aged 68.21±9.5 years (range: 36-95 years), with T2DM duration 12.04± 6.17 years (range: 5-34 years), and without CVD were included. CAD was diagnosed in 165 patients (67.3%). Multiple regression analysis showed that CPS, femoral plaque, and smoking were independently and positively correlated with CAD. CPS yielded the highest area under the curve for detecting significant coronary disease (AUC=0.7323). In contrast, the area under the curve of femoral artery plaque and carotid intima-media thickness was lower than 0.7, which was at a lower prediction level.

Conclusion

In patients with long T2DM duration, CPS has a higher ability to predict the occurrence and severity of CAD. However, femoral artery plaque has special value in predicting moderate to severe coronary artery disease in patients with long-term T2DM.

Nomogram and Carotid Risk Score for Predicting Moderate or High Carotid Atherosclerosis among Asymptomatic Elderly Recycling Volunteers

Carotid atherosclerosis is associated with cardiovascular and cerebrovascular events. We explored an appropriate method for selecting participants without ischemic cerebrovascular disease but with various comorbidities eligible for a carotid ultrasound. This was a retrospective subgroup analysis of the carotid plaque burden from a previous study involving a vascular and cognitive survey of 956 elderly recycling volunteers (778 women and 178 men; mean age: 70.8 years). We used carotid ultrasound to detect the carotid plaque and computed the carotid plaque score (CPS). A moderate or high degree of carotid atherosclerosis (MHCA) was defined as CPS > 5 and was observed in 22% of the participants. The CPS had positive linear correlations with age, systolic blood pressure, and fasting glucose. We stratified the participants into four age groups: 60−69, 70−74, 75−79, and ≥80 years. Multivariable analysis revealed that significant predictors for MHCA were age, male sex, hypertension, diabetes mellitus, hyperlipidemia, coronary artery disease, and a nonvegetarian diet. Coronary artery disease and advanced age were the two strongest predictors. We chose the aforementioned seven significant predictors to establish a nomogram for MHCA prediction. The area under the receiver operating characteristic curve in internal validation with 10-fold cross-validation and the classification accuracy of the nomogram were 0.785 and 0.797, respectively. We presumed people who have a ≥50% probability of MHCA warranted a carotid ultrasound. A flowchart table derived from the nomogram addressing the probabilities of all models of combinations of comorbidities was established to identify participants who had a probability of MHCA ≥ 50% (corresponding to a total nomogram score of ≥15 points). We further established a carotid risk score range from 0 to 17 comprising the seven predictors. A carotid risk score ≥ 7 was the most optimal cutoff value associated with a probability of MHCA ≥ 50%. Both total nomogram score ≥ 15 points and carotid risk score ≥ 7 can help in the rapid identification of individuals without stroke but who have a ≥50% probability of MHCA—these individuals should schedule a carotid ultrasound.