Jiang et al reported models for predicting diabetic nephropathy in a patient with type 2 diabetes. One of these is a nomogram and another is logistic regression model. The authors are from China-Japan Friendship Hospital, Peking Union Medical College, and Beijing University of Chinese Medicine in Beijing, China.
Patient selection: type 2 diabetes
Parameters:
(1) gender
(2) duration of diabetes in years
(3) diabetic retinopathy
(4) hematuria in RBCs per high power field in urinalysis
(5) anemia (hemoglobin < 130 g/L in males or < 120 g/L in females)
(6) hemoglobin A1c
(7) eGFR in mL per min per 1.73 square meter
(8) urine protein excretion in grams per 24 hours
(9) blood pressure
Parameter
Finding
Points
gender
female
0
male
4.9
duration of diabetes
< 5 years
0
5 to 9.99 years
5.2
>= 10 years
9.5
diabetic retinopathy
no
0
yes
10
hematuria
< 5 RBCs per HPF
8.8
5 to 9.99
7.1
>= 10
0
anemia
no
0
yes
5.9
hemoglobin A1c
< 7 percent
0
>= 7 percent
1.7
eGFR
>= 90 mL per min per 1.73 sq m
0
< 90 mL per min per 1.73 sq m
3.7
urine protein excretion
< 1 gram per 24 hours
0
1 to 3.49 grams per 24 hours
2.7
>= 3.5 grams per 24 hours
3.8
blood pressure
systolic BP < 140 mm Hg and diastolic BP < 90 mm Hg
0
other
6.3
total score =
= SUM(points for all of the parameters)
Interpretation:
• minimum score: 0
• maximum score: 54.5
value of X =
= (0.2122 * (score)) - 6.979
probability of diabetic nephropathy =
= 1 / (1 + EXP((-1) * X))
Performance:
• The area under the ROC curve is 0.93.
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