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Table 1 Characteristics of the studied populations

From: Would artificial neural networks implemented in clinical wards help nephrologists in predicting epoetin responsiveness?

 

AIMS data (± SD)

EOCdata (± SD)

N

340

92

Sex (% of males)

58.2

45.6

Age (y)

63.5 ± 14.6

69.7 ± 12.1

Weight (kg)

69.5 ± 15.3

69.9 ± 15.4

Diabetes mellitus (%)

27.4

34.7

Cardiomyopathy (%)

16.5

13.0a

ACE-I or ARB treatment (%)

No data

89.1

Haemoglobin g/dL b

11.8 ± 1.4

11.6 ± 0.7

Creatinine ÎĽmol/L b

580 ± 156

552 ± 145

BUN mmol/L b

No data

24.6 ± 6.0

Kt/V

No data

1.33 ± 0.26

pH b

No data

7.36 ± 0.04

Phosphate mmol/L b

No data

2.00 ± 1.38

Ionized calcium mmol/L b

No data

1.20 ± 0.07

Albumin g/L b

No data

37.9 ± 2.9

Ferritin mg/mL

411 ± 297

482 ± 255

PTH pmol/L

No data

25.8 ± 21.9

CRP mg/L b

No data

15.7 ± 15.8

Iron intravenously mg/month

No data

134 ± 50

Epoetin beta dose IU/Kg/week to reach a haemoglobin of 11.5 g/dL

149 ± 104

107 ± 63

Epoetin administration route % of subcutaneous

71

0

  1. a only patients with a left ventricular ejection fraction <50%; b pre-dialysis values
  2. Anthropometric data, comorbidity incidence, ACE-I or ARB treatment and mean results of the monthly biochemical parameters of the AIMS and EOC data pools.