High risk group of stroke individuals
Screening records ranging from 2012 to 2016 were provided by CNSSPP, a nationally ongoing community-based study, which was conducted by the National Project Office of Stroke Prevention and Control. Screenings were performed at 21 communities throughout the city of Nanjing.
Individuals were selected for cluster sampling. They should meet these criterions: Age≥40 years old, living in the community for at least 9 month per year, and at least 85% population were included.
According to the standard established by the CNSSPP committee, high-risk group of stroke were defined as follows: at least 40 years old, at least three of the following risk factors, including hypertension, atrial fibrillation, smoking, dyslipidemia, diabetes mellitus, physical inactivity, overweight or obesity (BMI ≥26 kg/m2), and family history of stroke. Individuals who had the history of stroke or transient ischemic attack were also considered at high risk.
Hypertension was defined as systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mmHg, self-reported hypertension diagnosed by a physician, or use of antihypertensive medications . Atrial fibrillation was defined as ECG examination indicated atrial fibrillation, self-reported diagnosis of atrial fibrillation, or use of anticoagulant medications. Smoking status was classified as smoking (current smoking or had a history of smoke for more than one year) or never smoking (never smoking or had a history of smoke for less than one year). Dyslipidemia was defined as having one or more of the following conditions: triglyceride ≥2.26 mmol/L, total cholesterol ≥6.22 mmol/L, high-density lipoprotein cholesterol <1.04 mmol/L, low-density lipoprotein cholesterol ≥4.14 mmol/L, self-reported diagnosis of dyslipidemia, or taking cholesterol-lowering medications . Diabetes mellitus was defined as fasting plasma glucose ≥7.0 mmol/L, self-reported diagnosis of diabetes mellitus, or use of oral antidiabetic agents or insulin injection. Physical activity was defined as regular physical exercise >3 times/week for at least 30 minutes per session. Body mass index was calculated as body weight (in kg) divided by the square of height (in m; kg/m2). Overweight or obesity was defined as body mass index ≥26kg/m2, according to the guidelines of the Working Group on Obesity in China . A family history of stroke was defined as the occurrence of stroke in parents or siblings.
Before carotid duplex scans, subjects were asked to complete a standardized CNSSPP questionnaire, including demographic information, lifestyle risk factors, medical history, and family history of stroke, which were collected through face-to-face interviews by trained staff. The questionnaire of CNSSPP is provided in additional file 1.
Fast venous blood (5mL) was collected, centrifugated at 3000g for 10 min and stored at -80°C Freezer. Levels of fasting plasma glucose (FPG), homocysteine (Hcy), Total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglyceride (TG) were determined using OLYMPUS AU5400 (OLYMPUS, Japan). EDTA anticoagulated whole blood samples (2ml) were collected to determine HbA1c level by TOSOH G8 (TOSOH, Japan).
Carotid artery ultrasound screening protocol
According to Chinese stroke vascular ultrasound examination guideline , the duplex scan consists of ultrasound imaging of the distal common carotid artery, bulb, and proximal internal and external carotid arteries, with evaluation of a Doppler signal for 3 to 5 beats in each location on both sides. Plaque is interpreted as greater than 1.5mm of IMT based on Doppler-derived . Plaques with hypoechoic, mixed echoes, or ulceration are defined as unstable plaques. Carotid duplex examinations were performed by four experienced registered vascular technicians in Nanjing Brain Hospital, which is a Stroke Screening and Training Center. All of the vascular technicians were unaware of clinical information of subjects. Screening work was conducted in compliance with the protocol established by CNSSPP committee.
Predictive model evaluation
The whole sample was randomly divided into a model derivation set and a model validation set, which consisted of approximately two-thirds and one-third of the sample, respectively. A comparison was performed between the two groups with t-test for continuous variables and with χ2 tests for categorical variables. Univariate logistic regression was carried out for each risk factor. When the value of P was less than 0.1, the variable was included in the multivariable logistic regression model (Stepwise forward). Variables with P values less than 0.05 are retained. According to the previous study , we also generated a scoring system based on the regression coefficients. The lowest coefficient in absolute value was used as denominator. The coefficient of each independent risk factor was divided by the absolute value of the lowest coefficient and then rounded up to the nearest integers. Each subject would have a score according to the model and then scores of all the subjects were used to plot receiver operator characteristic (ROC) curve, and to determine the prediction power of unstable carotid plaque, and the best cutoff score by Youden index.
We used validation set to evaluate the ability of the predictive model to discriminate between subjects with and without unstable carotid plaque, which was also assessed using a ROC curve by SYSSTAT (SPSS Inc, Chicago, IL). A ROC curve plots the true-positive rate (test sensitivity) for a given threshold on the y-axis and the corresponding false-positive rate (one-test specificity) on the x-axis. The area under the resulting fitted curve represents the discriminating ability of that particular screening method and is assumed to be normally distributed. An area of 50% represents a non-discriminant screening test in which the true-positive rate equals the false-positive rate. The area under the ROC curve for excellent test and poor test approximates 100% and 50%, respectively.
After checking the normality of all continuous variables, continuous variables were presented as means (Standard deviation, SD), and categorical variables were presented as percentages. According to empirical formula of sample estimation based on multi factor analysis, more than 228 cases were needed in this study. All statistical analyses were performed using the SPSS version 20.0 software for Windows (SPSS, Inc, Chicago, IL, USA). In all statistical analyses, a P value <0.05 was considered statistically significant.