BioMed Research International / 2013 / Article / Tab 2

Clinical Study

Comparison of a Bayesian Network with a Logistic Regression Model to Forecast IgA Nephropathy

Table 2

Characteristics of patients in the learning versus validation sample.

GroupLearning
( )
Validation
( )
P

Age (years)Mean ± SEM NS
Age < 40 years28 (37%)25 (34%)NS
40 ≤ age < 60 years26 (35%)25 (34%)
Age ≥ 60 years21 (28%)24 (32%)
Male gender44 (59%)50 (68%)NS
History of hypertension31 (41%)35 (47%)NS
Microhematuria32 (43%)34 (46%)NS
Macrohematuria12 (16%)13 (18%)NS
Family history of hematuria3 (4%)1 (1%)NS
History of diabetes5 (7%)12 (16%)NS
Mean GFR (MDRD mL/min/1.73 m²)Mean ± SEM NS
Stage of renal failureeGFR ≤ 29 mL/min/1.73 m²11 (15%)11 (15%)NS
30 ≤ eGFR ≤ 59 mL/min/1.73 m²25 (33%)21 (28%)
60 mL/min/1.73 m² ≤ eGFR39 (52%)42 (57%)
Serum Ig AIncreased14 (19%)13 (18%)NS
Normal25 (33%)26 (35%)
Not performed36 (48%)35 (47%)
Proteinuria (g/24 h)Mean ± SEM NS
Proteinuria < 0.3 g/24 h 8 (10%)10 (14%)NS
0.3 g/24 h ≤ proteinuria < 1 g/24 h17 (23%)13 (18%)NS
1 g/24 h ≤ proteinuria < 3 g/24 h26 (35%)24 (32%)
Proteinuria ≥ 3 g/24 h24 (32%)27 (36%)
Number of IgAN26 (35%)18 (24%)NS

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