Results
This study has been conducted on 366 patients with suspected CMV infection attending pediatric department at Zagazig University Hospital.
Table (1): Age distribution of the studied patients (except for neonates with congenital anomalies) (N=344)
Studied patients (N=344)
No.
%
Age (years)
Mean ± SD
9.9 ± 3.4
Median (Range)
10.0 (3.5 – 18.0)
The mean age and standard deviation (SD) of ages of the studied patients (except for neonates with congenital anomalies) in years as shown in table (1) was 9.9 ± 3.4.
Table (2): Age distribution of neonates with congenital anomalies (N=22)
Studied patients (N=22)
No.
%
Age of neonates with congenital anomalies group (days)
Mean ± SD
Median (Range)
4.1 ± 1.6
4.0 (2.0 – 7.0)
Table (2) shows that The mean age and standard deviation (SD) of ages ofneonates with congenital anomalies were 4.1 ± 1.6 days
Table (3): Sex distribution of the studied patients (N=366)
Studied patients (N=366)
No.
%
Sex
Male
202
55.2%
Female
164
44.8%
Table(3) shows that 55.2% (202 out of 366) of the studied patients were males, while 44.8% were females.
Figure (1): Pie diagram showing sex distribution of the studied patients (N=366)
Table (4): Distribution of the risk factors among the studied patients (N=366)
Risk factors
Studied patients
(N=366)
No.
%
Malignant hematological disease with chemotherapy
43
11.7 %
Receiving repeated blood transfusion
164
44.8 %
Fever of unknown origin
16
4.4 %
Critically ill patients lying in the ICUs with prolonged hospitalization
28
7.7 %
Receiving corticosteroids or other immunosuppressives for long period
22
6 %
Chronic renal failure with haemodialysis
64
17.5 %
Fever with pancytopenia
7
1.9 %
Neonates with congenital anomalies
22
6 %
As shown in table (4) and figure (2),44.8% of the studied patients were receiving repeated blood transfusion, 17.5% were suffering from chronic renal failure and receiving haemodialysis, 11.7% were suffering from Malignant hematological disease and receiving chemotherapy, 7.7% were critically ill patients lying in the ICUs with prolonged hospitalization, 6% were receiving immunosuppressive agents for long period, 6% were neonates with congenital anomalies, 4.4% had fever of unknown origin, and 1.9% suffered from fever with pancytopenia.
Figure (2): Pie diagram showing Distribution of the risk factors in the studied patients (N=366).
Table (5): Results of ELISA IgM and IgG for CMV in the enrolled patients (N=366)
ELISA results
Studied patients
(N=366)
IgM
Positive
60
16.4 %
Negative
306
83.6 %
IgG
Positive
93
25.4 %
Negative
273
74.6 %
Over all seropositivity
Positive both IgM and IgG
109
29.8 %
As shown in table (5), out of the 366 studied patients, 60 (16.4%) and 93 (25.4%) were positive for CMV IgM and IgG in an ELISA test respectively.
Table (6): Agreement between ELISA IgM and IgG in the studied patients (N=366)
ELISA IgM
ELISA IgG
Total
#Test
P-value
Negative
Positive
Negative
No.
257
49
306
0.469
0.000*
(HS)
%
94.1 %
52.7 %
83.6 %
Positive
No.
16
44
60
%
5.9 %
47.3 %
16.4 %
Total
No.
273
93
366
%
100.0 %
100.0 %
100.0 %
# Kappa measure of agreement
P< 0.05 is significant.
Statistical Significance
Standards for strength of agreement for the kappa coefficient:
?0=poor,
.01-.20=slight,
.21-.40=fair,
.41-.60=moderate,
.61-.80=substantial, and
.81-1=almost perfect.
Table 6 shows that there is a moderate agreement between ELISA IgM and IgG in the detection of CMV in children with high statistical significance.
Table (7): Prevalence of CMV IgM seropositivity among different risk groups
Risk Factors
No.
Studied patients
(N=366)
Positive IgM
No.
%
Malignant hematological disease with chemotherapy
(43)
8
18.6 %
Receiving repeated blood transfusion
(164)
36
21.9 %
Fever of unknown origin
(16)
8
50 %
Critically ill patients lying in the ICUs with prolonged hospitalization
(28)
0
0 %
Receiving corticosteroids or other immunosuppressives for long period
(22)
0
0 %
Chronic renal failure with haemodialysis
(64)
8
12.5 %
Fever with pancytopenia
(7)
0
0 %
Neonates with congenital anomalies
(22)
0
0 %
Table (7) and figure (3) show that the highest prevalence (50%) of CMV IgM seropositivity was reported from patients suffering from fever of unknown origin.
Figure (3): Bar chart showing prevalence of CMV IgM seropositivity among different risk groups
Table (8): Association between CMV IgM seropositivity and different risk factors
Risk factors
No.
Studied patients
(N=366)
Test
p-value
ELISA IgM
Positive
(N=60)
Negative
(N=306)
No.
%
No.
%
Malignant hematological disease with chemotherapy
(43)
8
18.6 %
35
81.4%
#11.17
0.010
(S)
Receiving repeated blood transfusion
(164)
36
21.9 %
128
78%
Fever of unknown origin
(16)
8
50 %
8
50%
Chronic renal failure with haemodialysis
(64)
8
12.5 %
56
87.5%
# chi square test
P< 0.05 is significant.
*statistical Significance
Table (9): Prevalence of CMV IgG seropositivity among different risk groups
Risk factors
No.
Studied patients
(N=366)
Positive IgG
No.
%
Malignant hematological disease with chemotherapy
(43)
0
0 %
Receiving repeated blood transfusion
(164)
63
38.4 %
Fever of unknown origin
(16)
0
0 %
Critically ill patients lying in the ICUs with prolonged hospitalization
(28)
0
0 %
Receiving corticosteroids or other immunosuppressives for long period
(22)
0
0 %
Chronic renal failure with haemodialysis
(64)
8
12.5 %
Fever with pancytopenia
(7)
0
0 %
Neonates with congenital anomalies
(22)
22
100 %
Table (9) and figure (4) show that the highest prevalence (100%) of CMV IgG seropositivity was reported from neonates with congenital anomalies.
Figure (4): Bar chart showing prevalence of CMV IgG seropositivity among different risk groups.
Table (10): Association between CMV IgG seropositivity and different risk factors
Risk factors
No.
Studied patients
(N=366)
Test
p-value
ELISA IgG
Positive
(N=93)
Negative
(N=273)
No.
%
No.
%
Receiving repeated blood transfusion
(164)
63
38.4%
101
61.6%
53.96
0.000*
(HS)
Chronic renal failure with haemodialysis
(64)
8
12.5%
56
87.5%
Neonates with congenital anomalies
(22)
22
100%
0
0%
# chi square test
P< 0.05 is significant.
*highly statistical Significance
Table (11): Results of real time PCR for CMV in the enrolled patients (N=366)
Real time PCR
Studied patients (N=366)
Positive
36
9.8%
Negative
330
90.2%
Table (11) shows that 9.8% (36 out of 366) of the studied patients were positive for CMV in real time PCR test.
Table (12): Results of nested PCR for CMV in the enrolled patients (N=366)
Nested PCR
Studied patients (N=366)
Positive
29
7.9%
Negative
337
92.1%
Table (12) shows that 7.9% (29 out of 366) of the studied patients were positive for CMV in nested PCR test.
Figure (4): Results of real time PCR and nested PCR for CMV in the enrolled patients.
Figure (5): 1st run nested PCR showing band at 435 bp.
Figure (6): 2ndrun nested PCR showing band at 159 bp.
Table (13): Prevalence of CMV infection in the studied patients (using real time PCR as a gold standard test)
Risk factors
No.
Studied patients
(N=366)
Positive
No.
%
Malignant hematological disease with chemotherapy
(43)
36
83.7%
Receiving repeated blood transfusion
(164)
0
0%
Fever of unknown origin
(16)
0
0%
Critically ill patients lying in the ICUs with prolonged hospitalization
(28)
0
0%
Receiving corticosteroids or other immunosuppressives for long period
(22)
0
0%
Chronic renal failure with haemodialysis
(64)
0
0%
Fever with pancytopenia
(7)
0
0%
Neonates with congenital anomalies
(22)
0
0%
As shown in table (13), CMV infection (using real time PCR as a gold standard test) was only reported from patients suffering from malignant hematological disease and receiving chemotherapy, where 83.7% of these patients were positive for CMV.
Figure (7):
Figure (8):
Table (14): Titer of CMV viremia in patients with malignant hematological disease receiving chemotherapy
Quantitative PCR
Studied patients (N=366)
Mean ± SD
6907.30 ± 15846.04
Median (Range)
623.50 (3.70 – 57500)
The mean titer and SD of titers of CMV viremia in patients with malignant hematological disease receiving chemotherapy as shown in table (14) was 6907.30 ± 15846.04.
Table (15): Results of Nested PCR for CMV among different risk groups
Risk factors
No.
Studied patients
(N=366)
Positive
No.
%
Malignant hematological disease with chemotherapy
(43)
29
67.4%
Receiving repeated blood transfusion
(164)
0
0%
Fever of unknown origin
(16)
0
0%
Critically ill patients lying in the ICUs with prolonged hospitalization
(28)
0
0%
Receiving corticosteroids or other immunosuppressives for long period
(22)
0
0%
Chronic renal failure with haemodialysis
(64)
0
0%
Fever with pancytopenia
(7)
0
0%
Neonates with congenital anomalies
(22)
0
0%
Twenty nine out of 43 patients suffering from malignant hematological disease with chemotherapy with a percentage of 67.4 were positive for CMV in a nested PCR test as shown in table (15).
Table (16): Relation between ELISA IgM and real time PCR and nested PCR in the studied patients (N=366)
Agreement between ELISA IgM and real time PCR and nested PCR in the studied patients (N=366)
Laboratory findings
ELISA
Test
P-value
Positive IgM
(N=60)
Negative IgM
(N=306)
No.
%
No.
%
Real time PCR
Positive (n=36)
8
22.2 %
28
77.8 %
# 0.05
0. 320
(NS)
Negative (n=330)
52
15.8 %
278
84.2 %
Nested PCR
Positive
8
27.6 %
21
72.4 %
#0.082
0.090
(NS)
Negative
52
15.4 %
285
84.6 %
# Kappa measure of agreement
P< 0.05 is significant.
Statistical Significance
Standards for strength of agreement for the kappa coefficient:
?0=poor,
.01-.20=slight,
.21-.40=fair,
.41-.60=moderate,
.61-.80=substantial, and
.81-1=almost perfect.
As shown in table 16, there is poor statistical agreement between ELISA IgM and PCR reactions in the detection of CMV in children with no significance.
Table (17): Relation between ELISA IgG and real time PCR and nested PCR in the studied patients (N=366)
Agreement between ELISA IgG and real time PCR and nested PCR in the studied patients (N=366)
Laboratory findings
ELISA
Test
P-value
Positive IgG
(N=93)
Negative IgG
(N=273)
No.
%
No.
%
Real time PCR
Positive (n=36)
0
0 %
36
100 %
# -0.137
0.001*
(HS)
Negative (n=330)
93
28.2 %
237
71.8 %
Nested PCR
Positive
0
0 %
29
100 %
#-0.165
0.000*
(HS)
Negative
93
27.6 %
244
72.4 %
# Kappa measure of agreement
P< 0.05 is significant.
*highly statistical Significance
Standards for strength of agreement for the kappa coefficient:
?0=poor,
.01-.20=slight,
.21-.40=fair,
.41-.60=moderate,
.61-.80=substantial, and .81-1=almost perfect.
A high statistically significant non-agreement is present between ELISA IgG and PCR reactions in the detection of CMV in childrenas shown in table 17.
Table (18): Relation between real time PCR and nested PCR in the studied patients (N=366)
Agreement between real time PCR and nested PCR in the studied patients (N=366)
Laboratory findings
Nested PCR
Test
P-value
Positive
(N=29)
Negative (N=337)
No.
%
No.
%
Real time PCR
Positive (n=36)
29
100 %
7
2.1 %
# 0.882
0.000*
(HS)
Negative (n=330)
0
0 %
330
97.9 %
# Kappa measure of agreement
P< 0.05 is significant.
*highly statistical Significance
Standards for strength of agreement for the kappa coefficient:
?0=poor,
.01-.20=slight,
.21-.40=fair,
.41-.60=moderate,
.61-.80=substantial, and .81-1=almost perfect.
Table 18 shows that there is an almost perfect statistical agreement between real time PCR and nested PCR in the detection of CMV in children with high significance.
Table (19): Relation between real time PCR and nested