Chen YY, Guo Y, Xue XH, Pang F. Application of metagenomic next-generation sequencing in the diagnosis of infectious diseases of the central nervous system after empirical treatment. World J Clin Cases 2022; 10(22): 7760-7771 [PMID: 36158512 DOI: 10.12998/wjcc.v10.i22.7760]
Corresponding Author of This Article
Ying-Ying Chen, PhD, Additional Professor, Department of Neurology, Liaocheng People's Hospital, No. 67 Dongchang West Road, Liaocheng 252000, Shandong Province, China. chen323232azqiqi@163.com
Research Domain of This Article
Clinical Neurology
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Clin Cases. Aug 6, 2022; 10(22): 7760-7771 Published online Aug 6, 2022. doi: 10.12998/wjcc.v10.i22.7760
Table 1 The performance of metagenomic next-generation sequencing and the conventional methods in the diagnosis of central nervous system virus infections
Sensitivity
Specificity
Accuracy
Positive predictive value
Negative predictive value
Conventional methods+
53.5% (42.7%, 64.2%)
85.7% (69.0%, 94.6%)
62.8% (53.5%, 71.3%)
90.2% (77.8%, 96.3%)
42.9% (31.3%, 55.2%)
mNGS+
66.3% (55.2%, 75.9%)
88.6% (72.3%, 96.3%)
72.7% (63.7%, 80.2%)
93.4% (83.3%, 97.9%)
51.7% (38.5%, 64.6%)
P value
0.087
1.000
0.099
0.779
0.316
Table 2 Inconsistency between metagenomic next-generation sequencing and conventional methods in diagnosing central nervous system virus infections
mNGS
Conventional methods (+, -)
Total
+
38, 19
57
_
7, 22
29
Total
45, 41
86
Table 3 Performance of metagenomic next-generation sequencing and the conventional methods in the diagnosis of central nervous system bacterial infections
Sensitivity
Specificity
Accuracy
Positive predictive value
Negative predictive value
Conventional methods+
14.3% (8.5%, 23.6%)
84.6% (64.3%, 95.0%)
33.3% (24.2%, 43.8%)
71.4% (42.0%, 90.4%)
26.8% (17.9%, 37.9%)
mNGS+
65.7% (53.3%, 76.4%)
88.5% (68.7%, 97.0%)
71.9% (61.6%, 80.3%)
93.9% (82.1%, 98.4%)
48.9% (34.3%, 63.7%)
P value
< 0.001
1.000
< 0.001
0.061
0.011
Table 4 Inconsistency of metagenomic next-generation sequencing and conventional methods in diagnosing central nervous system bacterial infections
mNGS
Conventional test (+, -)
Total
+
8, 37
45
_
2, 23
25
Total
10, 60
70
Table 5 Performance of metagenomic next-generation sequencing and the conventional methods in the diagnosis of central nervous system fungal infections
Sensitivity
Specificity
Accuracy
Positive predictive value
Negative predictive value
Conventional methods
44.4% (26.0%, 64.4%)
83.3% (36.5%, 99.1%)
51.5% (33.9%, 68.8%)
92.3% (62.1%, 99.6%)
25.0% (9.6%, 49.4%)
mNGS
63.0% (42.5%, 79.9%)
100.0% (51.7%, 100.0%)
69.7% (51.1%, 83.8%)
100.0% (77.1%, 100.0%)
37.5% (16.3%, 64.1%)
P value
0.172
1.000
0.131
0.433
0.656
Table 6 Inconsistency between metagenomic next-generation sequencing and Conventional methods in diagnosing central nervous system fungal infections
mNGS
Conventional test (+, -)
Total
+
7, 10
17
_
5, 5
10
Total
12, 15
27
Table 7 The results of meningitis in all patients were compared between the two methods
Sensitivity
Specificity
Accuracy
Positive predictive value
Negative predictive value
Conventional methods
37.2% (30.2%, 44.6%)
85.1% (73.8%, 92.2%)
50.0% (43.7%, 56.3%)
87.2% (77.2%, 83.3%)
33.1% (26.3%, 40.8%)
mNGS
65.6% (58.2%, 72.3%)
89.6% (79.1%, 95.3%)
72.0% (65.9%, 77.4%)
94.5% (88.6%, 97.6%)
48.8% (39.7%, 57.9%)
P value
< 0.001
0.436
< 0.001
0.065
0.007
Citation: Chen YY, Guo Y, Xue XH, Pang F. Application of metagenomic next-generation sequencing in the diagnosis of infectious diseases of the central nervous system after empirical treatment. World J Clin Cases 2022; 10(22): 7760-7771