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. 2014 Feb 7:10:77-86.
doi: 10.2147/TCRM.S57429. eCollection 2014.

Clinical differences between H3N2 and H1N1 influenza 2012 and lower respiratory tract infection found using a statistical classification approach

Affiliations

Clinical differences between H3N2 and H1N1 influenza 2012 and lower respiratory tract infection found using a statistical classification approach

Dimitris Petridis et al. Ther Clin Risk Manag. .

Abstract

Background: Influenza A H1N1 and H3N2 are two influenza waves that have been identified in past years.

Methods: Data from 77 inpatients from three tertiary hospitals were included and statistical analysis was performed in three different clusters.

Results: Thirty-four patients (44.2%) had respiratory distress upon admission, 31.2% had a smoking history or were active smokers, 37.7% manifested disease symptoms, and 7.8% were obese (body mass index >41). The mean age of patients was 51.1 years. Cough was the most common symptom observed in 77.9% of the patients, accompanied by sputum production (51.9%) and fatigue (42.9%). Hemoptysis and vomiting were rarely recorded in the patients (9.1% and 16.9%, respectively). Oseltamivir administration varied between 0 and 10 days, giving a mean value of 2.2 days. In particular, 19 patients received no drug, 31 patients received drug for only for 1 day, 19 patients for 5 days, and 8 patients from 2 to 10 days.

Conclusion: Clusters of symptoms can be used to identify different types of influenza and disease severity. Patients with vaccination had pneumonia, whereas patients without vaccination had influenza A. Patients more than 54.5 years old had H3N2 and patients less than 54.5 years had H1N1. White blood cell count values increased from normal to elevated in H3N2 patients but still remained abnormal in lower tract infection and H1N1 patients.

Keywords: H1N1; H3N2; influenza outbreak; respiratory infection; vaccination.

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Figures

Figure 1
Figure 1
Classification and regression tree classification for type of infection Notes: (A) Classification and regression tree classification for type of infection as derived from the predictor variables, vaccination history and age of the patients, at time of admission in the hospital. (B) Chi-squared automatic interaction detector classification tree for type of infection as derived by the predictor variables white blood cell (WBC) count and days of oseltamivir administration during patients’ hospitalization.
Figure 2
Figure 2
Two-dimensional arrangement of symptoms and infection type according to multiple correspondence analysis. Notes: Circled points confine symptoms and one type of infection (neighborhood relationships) and so are indicative of specific disease manifestation. The numbers 0 and 1 next to symptoms denote absence or presence of a symptom.

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