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|dc.description.abstract||Introduction: The clinical manifestations of influenza range from mild and self-limiting respiratory infections to severe clinical manifestations accompanied with significant morbidity and mortality. Having knowledge of the predictors of an unfavorable outcome is of utmost significance for making an early and right decision for a proper treatment. The aim of the study is to define a model of prognosic factors which will point to unfavorable outcome for the people infected with seasonal influenza, through defining demographic, clinical, biochemical, comorbid factors and most frequent complications. Material and methods: The research is prospective, compared in groups and it was carried out at The University Clinic for Infectious Diseases in Skopje in a time range of three years 2012-2015. 122 adult patients with clinical and laboratory confirmed seasonal influenza have been analyzed, which have further been divided into groups of mild and severe form of the disease. The patients from the severe influenza group have been divided into two sub-groups: survived and deceased .The confirmation of the virus of influenza in nasopharyngeal swab was made at the admission using the method of real time RT-PCR (Reverse transcription polymerase chain reaction). On admition demographic data and comorbidities were evaluated. At the hospital admition day, 24 hours and after 48 hours clinical, biochemical data were noted and the SAPS 2 index of the severity of the disease and prediction of mortality was calculated. The variables which in The Univariant Analysis were significantly associated with the severity of the disease and the death outcome, were included in The Multivariant logistic regression analysis, in order to determine the independent predictors for a severe form of influenza and lethal outcome. Results: Out of totally 122 analyzed patients, 87 were with a severe form of disease, whereas the remaining 35 with a mild one. 12 patients from the severe influenza group died, i.e. the mortality rate was 13,8%. The Multivariant analysis pointed out the cardiovascular diseases (OR=2.964; 95% CI, 1.382 – 6.370; p=0.01), dyspnea (OR=3.056;95% CI, 1.87 – 7.2; p=0.001), tachypnea with > 20 respirations in a minute (OR = 1.706; 95% CI, 1.529 – 6.187; p=0.005), references of LDH higher than 618 U/L (OR=1.706; 95% CI 1.014 – 3.224; p=0.048) and the SAPS 2 index (OR – 1.87; 95% CI, 1.23 – 2.98; p=0.031), as independent references which predict the severity of the disease at the very admission. The surface below ROC curve is 0.826, (95% CI), which suggests probability for a severe form of influenza of 82.6%. The global precision of this model to predict a severe form of influenza is 81.1%, sensitivity is 88.5%, and the specificity 72.9%. As independent references of the lethal outcome for the people infected with severe influenza, the multivariant analysis at the admission pointed out the cardiologic comorbidity diseases (OR = 2.024; 95% CI, 1.842 – 17.337; p=0.014), the value of urea higher than 8.3 U/L (OR = 1.89; 95% CI, 1.091 – 11.432; p=0.045) and the SAPS 2 index (OR=1.12; 95% CI, 1.01 – 2.976, p= 0,048). The surface below the ROC curve is 0.755, with a 95% interval of confidence of 0.587 – 0.923, which leads to conclude that the probability of combination of these three predictors for death for the influenza patients was 75.5%. The global precision of this predictive model to predict lethal outcome is 80%, sensitivity is 82%, specificity is 70%. Conclusion: The study showed good discriminatory ability for distinguises severe from mild forms of influenza through analysis of parameters for cardiologic diseases, dyspnea, tachypnea, LDH value higher than 618U/L and the SAPS 2 index, especially when the same are in combination. The cardiovascular diseases, higher value of urea and the SAPS 2 index as a combination in the group with severe influenza present a good prognostic model for lethal outcome.||en_US|
|dc.title||ПРОГНОСТИЧКИ ФАКТОРИ ЗА НЕПОВОЛЕН ИСХОД КАЈ БОЛНИТЕ СО СЕЗОНСКА ИНФЛУЕНЦА||en_US|
|crisitem.author.dept||Faculty of Medicine||-|
|Appears in Collections:||Faculty of Medicine: PhD Theses|
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