To predict influenza related pneumonia - a continuous challenge during pandemics
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CHESOV, Dumitru. To predict influenza related pneumonia - a continuous challenge during pandemics. In: MedEspera, Ed. 1, 17 mai 2012, Chişinău. Chişinău: "Tipografia-Sirius" SRL, 2012, pp. 70-71. ISBN 978-9975-57-030-5.
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MedEspera 2012
Conferința "MedEspera"
1, Chişinău, Moldova, 17 mai 2012

To predict influenza related pneumonia - a continuous challenge during pandemics


Pag. 70-71

Chesov Dumitru
 
”Nicolae Testemițanu” State University of Medicine and Pharmacy
 
 
Disponibil în IBN: 23 ianuarie 2023


Rezumat

Background: The last influenza pandemic showed the importance of the early beginning of antiviral therapy for a successful outcome of influenza related to pneumonia (IRP). Thus the ability to differentiate the influenza pneumonia from the bacterial one, during the first hours after the patient’s admission, is crucial for further management of the case. A study was performed to investigate whether adults with severe H1N1 pneumonia could be distinguished clinically form patients with non-H1N1 community acquired pneumonia (CAP). Methods: Clinical and epidemiological data of 75 adults admitted for severe H1N1 IRP were compared with a prospective study cohort of 127 adults with severe non-H1N1 CAP admitted during interpandemic period. A multivariate logistic regression model was generated for prediction of H1N1 influenza related pneumonia. Results: In-hospital mortality in both cohorts was pretty similar, to 20% in H1N1 IRP cohort compared with 19,7% in non-H1N1 CAP cohort. A diagnostic prediction model was derived by assessing one point for each of the seven criteria: demographic (age≤ 65 years), clinical (presence of myalgia/arthralgia, absence of hypotension, absence of pathological bronchial breathing), laboratory (leucocyte count ≤ 12*109/l) and radiological (presence of bilateral involvement, extension to superior pulmonary areas). The threshold yield of the model was obtained for 4 points value of that, with a negative predictive value of 92,4% and 88% of sensibility.Accuracy of the obtained model was appreciated using the value of area under receiver operatingcurve, which corresponds to a very good one - 0,93 (95%CI 0,89 - 0,96). Conclusion: There are substantial clinical differences between H1N1influenza related to pneumonia and inter-pandemic CAP. A model based on seven accessible criteria allows the early identification of adults with severe influenza related pneumonia.