INCIDENCE OF INFLUENZA VIRUS PNEUMONIA DURING THE TIME OF CORONOVIRUS-2019 PANDEMIC

Background: Isoferulic acid (IFA) is a main active ingredient of the rhizoma ofCimicifuga heracleifolia, which is used frequently in Japanese traditional medicine as an anti-inflammatory drug. It has been revealed that IFA inhibits the production of macrophage inflammatory protein-2 (MIP-2), which is a murine counterpart of the chemokine family that may contribute to the pathogenesis of inflammatory diseases through the chemotactic activity for inflammatory and immune effector cells.Aim of the study: In this study, we investigated the therapeutic effect of IFA on the progression of lethal influenza virus pneumonia in mice by comparison with that of dexamethasone (DX), a potent inhibitor for various inflammatory cytokines including MIP-2.Methods: Mice were infected by intranasal inoculation of influenza virus under ether anesthesia. The IFA or DX was given by oral administration once daily for 4 days after infection. After infection, the survival rate and the change in body weight were daily monitored.Results: IFA administration markedly improved the survival rate and body weight loss of influenza virusinfected mice in a suitable dose range (0.5 mg/day). However, DX administration did not show a beneficial effect at any dose.Conclusion: These data suggested that IFA is a novel tool not only for the intervention therapy, but also for the studies on the pathogenesis of influenza virusinduced pneumonia.

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Radiographic and High-Resolution CT Findings of Influenza Virus Pneumonia in Patients with Hematologic Malignancies

American Journal of Roentgenology ◽

10.2214/ajr.181.2.1810507 ◽

2003 ◽

Vol 181 (2) ◽

pp. 507-511 ◽

Cited By ~ 44

Author(s):

Anastasia Oikonomou ◽

Nestor L. Müller ◽

Stephen Nantel

Keyword(s):

Influenza Virus ◽

High Resolution ◽

Hematologic Malignancies ◽

High Resolution Ct ◽

Ct Findings ◽

Virus Pneumonia

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Correction: Macrophage-expressed IFN-β Contributes to Apoptotic Alveolar Epithelial Cell Injury in Severe Influenza Virus Pneumonia

PLoS Pathogens ◽

10.1371/journal.ppat.1005716 ◽

2016 ◽

Vol 12 (6) ◽

pp. e1005716 ◽

Cited By ~ 1

Author(s):

Katrin Högner ◽

Thorsten Wolff ◽

Stephan Pleschka ◽

Stephanie Plog ◽

Achim D. Gruber ◽

...

Keyword(s):

Influenza Virus ◽

Epithelial Cell ◽

Cell Injury ◽

Alveolar Epithelial Cell ◽

Alveolar Epithelial ◽

Severe Influenza ◽

Virus Pneumonia ◽

Epithelial Cell Injury

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Radiomics Is Effective for Distinguishing Coronavirus Disease 2019 Pneumonia From Influenza Virus Pneumonia

Frontiers in Public Health ◽

10.3389/fpubh.2021.663965 ◽

2021 ◽

Vol 9 ◽

Author(s):

Liaoyi Lin ◽

Jinjin Liu ◽

Qingshan Deng ◽

Na Li ◽

Jingye Pan ◽

...

Keyword(s):

Influenza Virus ◽

Characteristic Curve ◽

Operator Method ◽

Training Sample ◽

Receiver Operator Characteristic Curve ◽

Stepwise Logistic Regression ◽

Data Sets ◽

Validation Data ◽

Virus Pneumonia ◽

Selection Operator

Objectives: To develop and validate a radiomics model for distinguishing coronavirus disease 2019 (COVID-19) pneumonia from influenza virus pneumonia.Materials and Methods: A radiomics model was developed on the basis of 56 patients with COVID-19 pneumonia and 90 patients with influenza virus pneumonia in this retrospective study. Radiomics features were extracted from CT images. The radiomics features were reduced by the Max-Relevance and Min-Redundancy algorithm and the least absolute shrinkage and selection operator method. The radiomics model was built using the multivariate backward stepwise logistic regression. A nomogram of the radiomics model was established, and the decision curve showed the clinical usefulness of the radiomics nomogram.Results: The radiomics features, consisting of nine selected features, were significantly different between COVID-19 pneumonia and influenza virus pneumonia in both training and validation data sets. The receiver operator characteristic curve of the radiomics model showed good discrimination in the training sample [area under the receiver operating characteristic curve (AUC), 0.909; 95% confidence interval (CI), 0.859–0.958] and in the validation sample (AUC, 0.911; 95% CI, 0.753–1.000). The nomogram was established and had good calibration. Decision curve analysis showed that the radiomics nomogram was clinically useful.Conclusions: The radiomics model has good performance for distinguishing COVID-19 pneumonia from influenza virus pneumonia and may aid in the diagnosis of COVID-19 pneumonia.

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Macrophage-expressed IFN-β Contributes to Apoptotic Alveolar Epithelial Cell Injury in Severe Influenza Virus Pneumonia

PLoS Pathogens ◽

10.1371/journal.ppat.1003188 ◽

2013 ◽

Vol 9 (2) ◽

pp. e1003188 ◽

Cited By ~ 106

Author(s):

Katrin Högner ◽

Thorsten Wolff ◽

Stephan Pleschka ◽

Stephanie Plog ◽

Achim D. Gruber ◽

...

Keyword(s):

Influenza Virus ◽

Epithelial Cell ◽

Cell Injury ◽

Alveolar Epithelial Cell ◽

Alveolar Epithelial ◽

Severe Influenza ◽

Virus Pneumonia ◽

Epithelial Cell Injury

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Macrophage TRAIL Expression Is IFN-ß-dependent And Mediates Alveolar Epithelial Apoptosis And Barrier Dysfunction In Influenza Virus Pneumonia

10.1164/ajrccm-conference.2010.181.1_meetingabstracts.a2313 ◽

2010 ◽

Author(s):

Katrin Hoegner ◽

Stephan Pleschka ◽

Jens Albrecht ◽

Frank Driever ◽

Werner Seeger ◽

...

Keyword(s):

Influenza Virus ◽

Barrier Dysfunction ◽

Trail Expression ◽

Alveolar Epithelial ◽

Virus Pneumonia

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Clinical Presentation, Laboratory Findings, Complications, and Mortality of Influenza During the Epidemic of October 2019-February 2020 in Iran

10.21203/rs.3.rs-947403/v1 ◽

2022 ◽

Author(s):

Zahra Movahedi ◽

Soheil Dehghani ◽

Zoha Ali ◽

Amirali Karimi ◽

Shahram Arsangjang ◽

...

Keyword(s):

Influenza Virus ◽

Clinical Signs ◽

Cross Sectional Study ◽

Hospitalization Rate ◽

Hospitalized Patients ◽

Influenza Epidemic ◽

Laboratory Findings ◽

Cross Sectional ◽

Virus Pneumonia ◽

Pcr Test

Abstract Background: Influenza is one of the most important viruses and causes millions of infections and 290-600 thousands deaths annually. We aimed to evaluate the hospitalization rates due to complications caused by the influenza virus (pneumonia, seizures, sinusitis, otitis, myositis and encephalitis), the frequency of clinical signs, and laboratory findings in children under 15 years of age infected with Influenza.Methods: We conducted a cross-sectional study during the Influenza epidemic in Qom, Iran, from October 2019 to February 2020. Children under 15 years of age with the definitive diagnosis of influenza obtained by polymerase chain reaction (PCR) test were included.Results: Out of 1225 patients who referred to us with flu-like symptoms; 1172 patients were referred by the emergency department and our hospital clinic but 53 patients were referred to us by other paediatricians. 375 patients (30.61%) who had a positive PCR test result for influenza and suffered from complications caused by the virus were hospitalized.The number of male hospitalized patients was 231 (61.6% of hospitalized patients) and the number of female hospitalized patients was 144 (38.4% of hospitalized patients) respectively.The highest age range of patients with pneumonia was of 13 months to 3 years with a hospitalization rate of 36.41% and the lowest hospitalization rate was of 12 years to 15 years with a hospitalization rate of 0.84%.The most serious complication observed in patients caused by the influenza virus was pneumonia; with 17 cases (4.53%) reported.89.6% of patients had fever at the time of referral causing it to be the most common clinical symptom among patients. Cough ranked second with 76.8%.Lymphopenia and leukopenia was recognized as the most common laboratory findings with a frequency of 26.33% and 21.85%.Conclusions: Complications of influenza was not uncommon in children and affected a fifth of the patients. The influenza epidemic of October 2019- February 2020 imposed a heavy burden on our hospital and the learned lessons should be implemented to further assist the physicians in future influenza epidemic.

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