Logistic regression models to predict prevalent CKD
| Model 1 | Model 2 | Model 3a | Model 3b | |
| Selected variables* | Age Years of education Occupation Tobacco use (ever) Family history of HTN DM† Heart disease† Stroke† HTN† Kidney disease† Kidney stone† PAD† BMI Waist circumference BMI × Waist circumference SBP DBP Urine dipstick glucose Urine dipstick albumin Fasting plasma glucose | Age Years of education Source of drinking water Alcohol use DM† HTN† Kidney disease† Kidney stone† DM† | Age Sex BMI Waist circumference BMI × Waist circumference SBP DBP Urine dipstick glucose Urine dipstick albumin | Age Sex BMI SBP DBP Urine dipstick albumin Fasting plasma glucose |
| C-statistic‡ | ||||
| Development | 0.79 (0.78 to 0.81) | 0.73 (0.72 to 0.75) | 0.77 (0.75 to 0.79) | 0.77 (0.76 to 0.79) |
| Bootstrap validation | 0.78 (0.77 to 0.80) | 0.73 (0.72 to 0.75) | 0.76 (0.75 to 0.78) | 0.77 (0.75 to 0.79) |
| CARRS I validation | – | – | 0.74 (0.73 to 0.74) | – |
| UDAY validation | – | – | 0.70 (0.69 to 0.71) | – |
| Calibration slope | 0.96 | 0.98 | 0.98 | 0.99 |
| Probability threshold | 0.09 | 0.09 | 0.09 | 0.09 |
| Sensitivity‡ | 0.72 (0.69 to 0.75) | 0.68 (0.65 to 0.71) | 0.71 (0.68 to 0.74) | 0.71 (0.68 to 0.74) |
| Specificity‡ | 0.72 (0.71 to 0.73) | 0.67 (0.66 to 0.68) | 0.70 (0.69 to 0.71) | 0.70 (0.69 to 0.71) |
| Positive predictive value‡ | 0.24 (0.22 to 0.26) | 0.20 (0.19 to 0.21) | 0.22 (0.21 to 0.24) | 0.22 (0.21 to 0.24) |
| Negative predictive value‡ | 0.96 (0.95 to 0.96) | 0.95 (0.94 to 0.95) | 0.95 (0.95 to 0.96) | 0.95 (0.95 to 0.96) |
*Variables selected from group of variables presented in table 1.
†Self-reported.
‡95% CI.
BMI, body mass index; CKD, chronic kidney disease; DBP, diastolic blood pressure; DM, diabetes mellitus; HTN, hypertension; PAD, peripheral arterial disease;SBP, systolic blood pressure.