Back

COVID-19 or seasonal influenza? How to distinguish in people younger than 65 years old: A retrospective observational cohort study comparing the 2009 pandemic influenza A H1N1 with 2022 SARS-CoV-2 Omicron BA.2 outbreaks in China.

Zhong, W.; Wu, Y.; Yue, W.; Fang, J.; Xie, B.; Xu, N.; Lin, M.; Zhu, X.; Su, Z.; Chen, Y.; Li, H.; Li, H.

2023-03-01 infectious diseases
10.1101/2023.02.28.23286466 medRxiv
Show abstract

ObjectiveThis study attempted to explore the difference of clinical characteristics in H1N1 influenza infection and SARS-CoV-2 Omicron infection in people younger than 65 years old, in order to better identify the two diseases. MethodsA total of 127 H1N1 influenza patients diagnosed from May 2009 to July 2009 and 3265 patients diagnosed and identified as SARS-CoV-2 Omicron BA.2 variant from March 2022 to May 2022 were admitted in this study. Through the 1 : 2 match based on age (The difference is less than 2 years), gender and underlying diseases, 115 patients with H1N1 infection and 230 patients with SARS-CoV-2 Omicron BA.2 infection(referred to as H1N1 group and Omicron group) were included in the statistics. The clinical manifestations of H1N1 group were compared with those of Omicron group. Logistic regression was performed to analyze the possible independent risk factors of H1N1 group and Omicron group. And multiple linear regression was used to analyze the factors for time for nucleic acid negativization (NAN). ResultsThe median age of the two groups was 21 [11,26] years. Compared with the H1N1 group, the Omicron group had lower white blood cell count and CRP levels, less fever, nasal congestion, sore throat, cough, sputum and headache, while more olfactory loss, muscle soreness and LDH abnormalities. The Omicron group used less antibiotics and antiviral drugs, and the NAN time was longer (17 [14,20] VS 4 [3,5], P < 0.001). After logistic regression, it was found that fever, cough, headache, and increased white blood cell count were more correlated with the H1N1 group, while muscle soreness and LDH abnormalities were more correlated with the Omicron group. After analyzing the factors of NAN time, it was found that fever (B 1.529, 95 % CI [0.149,2.909], P = 0.030) significantly predicted longer NAN time in Omicron patients. ConclusionThis study comprehensively evaluated the similarities and differences in clinical characteristics between SARS-CoV-2 Omicron infection and 2009 H1N1 influenza infection, which is of great significance for a better understanding for these diseases.

Matching journals

The top 12 journals account for 50% of the predicted probability mass.

1
PLOS ONE
4510 papers in training set
Top 19%
10.1%
2
BMC Infectious Diseases
118 papers in training set
Top 0.3%
6.4%
3
Frontiers in Public Health
140 papers in training set
Top 1%
4.3%
4
Journal of Medical Virology
137 papers in training set
Top 0.6%
4.3%
5
Journal of Infection and Chemotherapy
16 papers in training set
Top 0.1%
4.3%
6
Journal of Infection and Public Health
15 papers in training set
Top 0.1%
4.3%
7
International Journal of Infectious Diseases
126 papers in training set
Top 0.5%
3.6%
8
BioMed Research International
25 papers in training set
Top 0.7%
3.6%
9
Frontiers in Medicine
113 papers in training set
Top 2%
3.1%
10
Clinical Infectious Diseases
231 papers in training set
Top 2%
3.1%
11
Journal of Infection
71 papers in training set
Top 0.7%
2.7%
12
Virologica Sinica
10 papers in training set
Top 0.1%
1.9%
50% of probability mass above
13
Travel Medicine and Infectious Disease
15 papers in training set
Top 0.1%
1.9%
14
Journal of Clinical Virology
62 papers in training set
Top 0.4%
1.7%
15
Medicine
30 papers in training set
Top 1%
1.7%
16
Scientific Reports
3102 papers in training set
Top 58%
1.7%
17
BMJ Open
554 papers in training set
Top 9%
1.7%
18
Frontiers in Cellular and Infection Microbiology
98 papers in training set
Top 3%
1.5%
19
Annals of Translational Medicine
17 papers in training set
Top 0.8%
1.3%
20
PeerJ
261 papers in training set
Top 10%
1.2%
21
BMC Public Health
147 papers in training set
Top 5%
1.1%
22
Frontiers in Microbiology
375 papers in training set
Top 7%
1.1%
23
JMIR Public Health and Surveillance
45 papers in training set
Top 3%
1.1%
24
International Immunopharmacology
15 papers in training set
Top 0.3%
1.1%
25
Science China Life Sciences
26 papers in training set
Top 2%
1.0%
26
Journal of Translational Medicine
46 papers in training set
Top 2%
1.0%
27
International Journal of Environmental Research and Public Health
124 papers in training set
Top 6%
1.0%
28
Vaccines
196 papers in training set
Top 2%
0.9%
29
Influenza and Other Respiratory Viruses
44 papers in training set
Top 0.3%
0.9%
30
Microbiology Spectrum
435 papers in training set
Top 5%
0.9%