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Table 1 Univariate analaysis highlighting the association between intestinal microbiota profiles and host factors among 200 patients with enteric infections

From: Intestinal microbial communities associated with acute enteric infections and disease recovery

 

Community clusters I and II (n = 152)

Community clusters III–V (n = 47)

 

Characteristics

No. (%) of individuals

No. (%) of individuals

P valuea

Age group

    

0.17

 0–2 years (n = 31)

25

(16.5)

6

(12.8)

 

 3–18 years (n = 55)

44

(29.0)

11

(23.4)

 

 19–52 years (n = 76)

58

(38.2)

18

(38.3)

 

 >52 years (n = 37)

25

(16.5)

12

(25.5)

 

Gender

    

0.02

 Male (n = 104)

86

(57.3)

18

(38.3)

 

 Female (n = 93)

64

(42.7)

29

(61.7)

 

Symptoms

     

 No diarrhea (n = 3)

2

(1.5)

1

(2.3)

0.03

 Diarrhea only (n = 91)

63

(46.3)

28

(65.1)

 Bloody diarrhea (n = 85)

71

(52.2)

14

(32.6)

 No vomiting (n = 118)

84

(62.7)

34

(79.1)

0.05

 Vomiting (n = 59)

50

(37.3)

9

(20.9)

 No fever (n = 62)

42

(33.9)

20

(54.1)

0.03

 Fever (n = 99)

82

(66.1)

17

(46.0)

 

Length of hospitalization

    

0.67

 None (n = 126)

94

(66.2)

32

(74.4)

 

 1–2 days (n = 19)

18

(12.7)

1

(2.3)

 

 ≥3 days (n = 40)

30

(21.1)

10

(23.3)

 

Type of pathogen (n = 199)

    

0.05

Campylobacter (n = 71)

55

(36.2)

16

(34.0)

 

Salmonella (n = 66)

49

(32.2)

17

(36.2)

 

 Shiga toxin E. coli (n = 28)

16

(10.5)

12

(25.5)

 

Shigella (n = 34)

32

(21.1)

2

(4.3)

 
  1. Percentages represent the frequency of each characteristic out of the total number of patients per cluster group. Denominators for host characteristics do not always add up to the total number of infected individuals (n = 200) as some data were missing. Symptom data was missing for up to 23 patients. Because most patients with missing data had microbiota communities belonging to clusters I/II, it is not likely that inclusion of the missing data would impact the direction of each significant association
  2. aThe likelihood ratio chi-square or Mantel-Haenszel chi-square (for variables with more than two outcomes) were used to highlight differences between clusters I–II and clusters III–V