Analysis of a database to predict the result of allergy testing in vivo in patients with chronic nasal symptoms and the development of the software ARSTAT

Background. This thesis consist of parts(i)Introduction in wich we present the clinical problem of rhinitis;(ii)the methods to evaluate the diagnostic choises;(iii)the rational errors in Allergy,(iv)the experimental part of thesis with wich we developed the software ARTSTAT,wich is the application of the analysis reported.Objective: We studied the ability of the logistic regression model obtained by the evaluaqtion of a database, to detect patients with positive allergy skin prick test(SPT)and patients with negative SPT. The model developed was valitated using the data set obtained from another medical institution. Methods: The analysis was carried out using a database obtained from a questionnaire administered to the patients with nasal symptoms containing personal data, clinical data result of allergy testing (SPT). All variables found to be significantly different between patients with positive and negative SPT(P<0.05),were selected for the logistic regression models and were analyzed with bacward stepwise logistic regression. A second set of patients from another Institution was used to prove the model. Results: e accuracyof the model identifying, over the second set, both patients whose SPT will bepositive and negative was high. The model detect 96 percent of patients with nasal symptoms and positive SPT, and classified 94 percent of those with negative SPT. Conclusion:The data of the thesis have been preliminary to the creation of a softwarewich cuold help the primary care doctors in diagnostic decision making process ( need of allergy testing), in patients complaining of chronic nasal symptoms.