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Table 1 Baseline Characteristics of AA and MDS Patients

From: A potential predictive model based on machine learning and CPD parameters in elderly patients with aplastic anemia and myelodysplastic neoplasms

Characteristic

AA Patients

( n = 89)

MDS Patients

( n = 71)

Validation Cohort

( n = 86)

P-value

AA Patients

( n = 57)

MDS Patients

( n = 29)

Gender

 Male[(n, %)]

39

(43.820)

44

(61.972)

24

(42.105)

15

(51.724)

0.022

 Female[(n, %)]

50

(56.180)

27

(38.028)

33

(57.895)

14

(48.276)

Age [year (median IQR)]

61.000

(56.000–68.500)

69.000

(61.000–73.000)

60.000

(55.000–69.000)

65.000

(59.000–69.000)

 < 0.001

Basic disease

 Yesa[(n, %)]

50

(56.180)

43

(60.563)

18

(31.579)

17

(58.621)

0.577

 No[(n, %)]

39

(43.820)

28

(39.437)

39

(68.421)

12

(41.379)

Comorbidities [(n, %)]

 Tumorb

5

(5.618)

10

(14.085)

4

(7.018)

6

(20.690)

0.068

 Hypertension

26

(29.213)

20

(28.169)

8

(14.035)

7

(24.138)

0.885

 Diabetes

15

(16.854)

11

(15.493)

5

(8.772)

4

(13.793)

0.817

 Infectious fever

11

(12.360)

7

(9.859)

3

(5.263)

1

(3.448)

0.619

 Hypoproteinemia

5

(5.618)

5

(7.042)

1

(1.754)

1

(3.448)

0.712

 Coronary heart disease

2

(2.247)

3

(4.225)

1

(1.754)

0

(0.000)

0.475

  1. aPatients with 1 of the following: tumor, hypertension, diabetes, infectious fever, hypoproteinemia, or coronary heart disease
  2. bAny type of tumor