Table 1 Predictors of non-obstructive azoospermia in azoospermia patients via logistic regression analysis.

From: Developing a nomogram model for predicting non-obstructive azoospermia using machine learning techniques

Characteristics

Univariate regression

Multiple regression

OR (95% CI)

P-value

OR (95% CI)

P-value

Age (year)

0.96 (0.90, 1.02)

0.182

  

Mean testicular volume (ml)

0.53 (0.45, 0.62)

< 0.001

0.74 (0.57, 0.96)

0.021

Semen volume (ml)

1.66 (1.34, 2.05)

< 0.001

1.33 (0.87, 2.02)

0.186

Semen pH

21.53 (8.37, 55.41)

< 0.001

9.15 (1.02, 82.27)

0.048

Prolactin (mIU/L)

1.00 (1.00, 1.00)

0.467

  

Follicle stimulating hormone (IU/L)

1.93 (1.59, 2.34)

< 0.001

1.56 (1.23, 1.97)

< 0.001

Luteinizing hormone (IU/L)

1.84 (1.56, 2.17)

< 0.001

1.23 (0.91, 1.66)

0.187

Estradiol (pmol/L)

1.00 (0.99, 1.00)

0.145

  

Testosterone (nmol/L)

0.93 (0.89, 0.96)

< 0.001

1.00 (0.92, 1.08)

0.900

Inhibin B (pg/ml)

0.95 (0.94, 0.96)

< 0.001

0.99 (0.97, 1.00)

0.049

  1. OR odds ratio, CI confidence interval.