The introduction of polymerase chain reaction (PCR) techniques has improved the detection of respiratory viruses, particularly with the use of multiplex real-time technique with the capability of simultaneous detection of various pathogens in a single reaction. The aim of this study was to apply the above technology for the diagnosis of influenza infections and at the same time to differentiate between common flu species between hospitalized patients in Laleh hospital (Iran) between two flu seasons (2016-2017 and 2017-2018). Different respiratory specimens were collected from 540 patients from a period of December 2016 to May 2018 and were sent to the laboratory for molecular diagnosis. RNAs were extracted and subsequently, a multiplex real time PCR identifying flu A, flu B and typing flu A (H1N1) was carried out. The mean age of patients was 47.54±23.96. 216 (40%) and 321 (60%) of subjects were male and female, respectively. 219 out of 540 (40.5%) were positive for influenza infection including flu A (n=97, 44.3%), flu A (H1N1) (n=45, 20.7%) and flu B (n=77, 35%). Flu A was the dominant species on 2016-2017 and flu B was the major species on 2017-2018. Flu A (H1N1) was comparable in both time periods. Flu infections were most frequently diagnosed in age groups 21-40. Flu-positive patients suffered more from body pain and sore throat than flunegative patients with significant statistical difference (P values <0.001). The mean duration of hospitalization was shorter for flu-positive patients (P value = 0.016). Application of multiplex real time PCR could facilitate the influenza diagnosis in a short period of time, benefiting patients from exclusion of bacterial infections and avoiding unnecessary antibiotic therapy. Influenza diagnosis was not achieved in up to 60% of flu-like respiratory infections, suggesting the potential benefit of adopting the same methodology for assessing the involvement of other viral or/and bacterial pathogens in those patients.
Keywords: FLU A (H1N1); Influenza; Multiplex Real Time PCR.
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