Table 3.
Stenosis score chart
| Characteristic | Value | Stenosis score |
|---|---|---|
| Age (years) | < 50 | 0 |
| 50–59 | 4 | |
| 60–69 | 7 | |
| 70+ | 9 | |
| Sex | male | 2 |
| female | 0 | |
| History of vascular disease | no | 0 |
| yes | 3 | |
| Systolic blood pressure (mmHg) | < 125 | 0 |
| 125–139 | 2 | |
| 140+ | 4 | |
| Diastolic blood pressure (mmHg) | < 75 | 2 |
| 75–84 | 1 | |
| 85+ | 0 | |
| TCHDL ratio | < 5 | 0 |
| 5+ | 1 | |
| Diabetes mellitus | no | 0 |
| yes | 1 | |
| Current smoking | no | 0 |
| yes | 3 | |
The stenosis score ranges from 0 to 25 points. The predicted prevalence of stenosis is defined as 1 / (1+e−LP), where LP refers to the linear predictor in a logistic regression model. Two LPs were defined as follows:
- LPsevere stenosis = − 10.74 + 0.384 × sum score;
- LPmoderate stenosis = − 7.16 + 0.265 × sum score.
Using these models, the mean predicted probability of severe stenosis was 0.5% and the mean predicted probability of moderate stenosis was 2.0%. We estimated the intercepts for other prevalence figures, so when the model is applied in a population with other prevalence rates of stenosis, the intercept of the model can be adjusted (Webtable 1). When the prevalence of stenosis is lower, the intercept needs to be more negative, leading to lower predicted prevalences.