Patent Application: US-201013144545-A

Abstract:
according to the invention there is provided a method for diagnosing urticaria or angioedema including : asking a patient the following questions : are any nsaids or aspiring being taken ; are symptoms triggered by aspirin , aspirin - containing drugs , orange juice , curry or high - aspirin content food ; is tingling of the mouth or lips , swelling of the tongue , the inside of the mouth or throat , difficulty swallowing , or difficulty breathing experienced after other medications than those known to cause urticaria or angioedema ; does urticaria or angioedema come on with physical stimuli such as cold , wet , wind and pressure ; carrying out one or more tests which includes a rast test to cat ; inputting the results of the questions and tests into a neural network that has been trained to diagnose urticaria or angioedema ; and producing an output indicative of urticaria or angioedema .

Description:
table 1 shows the distribution of diagnoses in patients presenting to the welsh clinical allergy service ( wcas ) outpatient clinics in 2001 , and is representative of the caseload seen in this regional allergy centre . it will be seen that a high proportion of patients presented to the service with symptoms of urticaria and angioedema . distribution of diagnoses in patients seen in wcas outpatient clinics in 2001 ( n = 213 ) no . of patients percentage of diagnostic category with diagnosis all patients % urticaria / angioedema 46 21 . 6 rhinitis 43 20 . 2 drug - induced angioedema / reaction 28 13 . 1 food allergy 26 12 . 2 food intolerance 14 6 . 6 salicylate intolerance 11 5 . 2 venom insensitivity 7 3 . 3 non - allergic / miscellaneous conditions 38 17 . 8 total 213 100 bro taf local research ethics committee granted ethical approval for all aspects of this study and the project was registered with cardiff and vale nhs trust research and development office . all participants were required to complete a consent form . data were anonymised prior to analysis and handled in accordance with the data protection act 1998 . this study made use of a standard questionnaire comprising questions and tests were created using the commercial cardiff teleform information capture system v7 . 0 designer module . this questionnaire was devised as an integral part of the nurse practitioner - based diagnosis and management evaluation program and aimed to gather demographic and clinical information in a structured format . this questionnaire was endorsed by a multidisciplinary panel of experts and piloted in wcas clinics throughout 2001 . data were gathered during 2004 . patients aged 18 to 75 referred to the wcas by general practitioners or hospital doctors due to symptoms of urticaria or angioedema were drawn from the routine non - urgent outpatient waiting list and recruited using an approved protocol . all consenting patients with predominant presenting symptoms of urticaria or angioedema were entered into the study . there were no exclusion criteria . participants underwent skin prick testing immediately prior to an initial conventional consultation with either the consultant clinical immunologist or allergy nurse practitioner . the order of consultation was randomized so that roughly equal numbers of patients were seen first by the nurse practitioner as by the consultation clinical immunologist . findings were recorded on the standard questionnaire ensuring all sections were fully completed . patients were then seen independently by the other practitioner , and findings annotated upon a separate questionnaire . total serum ige and rast testing were performed upon clinical discretion . as per current wcas protocol , a clinic letter outlining the final diagnosis and management plan was dictated by the consultant clinical immunologist and posted to the referring medical practitioner and patient . a similar letter was dictated independently by the allergy nurse practitioner , which was retained as supporting evidence to her questionnaire , for analysis in a later study . once available , all rast and other test results were added to data recorded during respective consultations . completed questionnaires were processed using the commercial cardiff teleform information capture system v8 . 2 scan station , reader and verifier modules ( see fig1 ). data were exported into separate microsoft excel files for each clinician . data imported into microsoft excel were anonymised . all input variables were inspected for transfer accuracy and errors corrected manually . data were normalised ( scaled ) within a uniform range for each input variable , some variables removed ( e . g . domestic demographic data , ethnic origin and marital status ) and a number of new input variables created following recoding of defined input groups . the final aetiological diagnosis for each patient was coded into one of five output categories ( chronic idiopathic urticaria / angioedema , physical urticaria , aspiring - included urticaria , non - aspirin drug induced urticaria / angioedema , and urticaria after unidentified food additives ). data were partitioned into two separate excel parent databases ( i . e . separate excel worksheets ) ( i ) ‘ all questionnaire inputs ’ and ( ii ) ‘ clinically selected inputs ’ ( 79 input variables ; five output variables ) ( see table 2 ), as it became available . ann models were developed using data and diagnoses from the consultant clinical immunologist . model development required data from each parent database to be divided into two subsets : ( i ) training and test data and ( ii ) validation . at present there are no mathematical rules governing the required size of data subsets and most ann - based studies utilize anecdotal rules derived from experience and analogy with statistical regression techniques ( basheer and hajmeer et al 2000 ). table 3 shows the allocation of the total ( 108 patients ) data set into training and test data subsets . data utilised for the ann training subset for both parent databases were drawn from patients 001 - 073 since these were collected first , and data from patients 074 - 108 were used as test data . it is desirable that data used in ann training is nearly evenly distributed between output categories to prevent the ann model generated from being biased to over - represented output classes ( swingler 1996 ). table 3 shows the distribution of diagnoses amongst patients 001 - 074 . traditional approaches to dealing with such unbalanced data include removing examples from over - represented output classes or adding examples pertaining to under - represented classes ( basheer and hajmeer 2000 ). the relatively small size of the training and test data subsets made the first option undesirable . furthermore , whilst there is no published epidemiological data with which to compare the distribution of diagnoses in the training data subset , it seemed unlikely that significant numbers of under - represented diagnoses would be made . it was therefore decided to use unbalanced training and test data on the premise that models created would reflect what appeared to be a real - world bias to allergic and allergic angioedema in patients presenting to the wcas . the study used a commercially available ann , the neuroshell predictor ™ ( ward systems inc , frederick , md ., usa ). neuroshell predictor ™ can operate in one of two modes . in the neural mode of analysis , the neural net that dynamically grows hidden neurons to build a model which generalises well and trains quickly . a variation of the cascade correlation algorithm is utilised . when applying the trained network to new data , the neural training strategy may enable better results to be obtained on “ noisy data ” that is somewhat dissimilar from the data used to train the network . alternatively , the neuroshell predictor ™ can be used in a genetic mode of analysis . a genetic algorithm is utilised , which is a variant of the general regression neural network ( grnn ). the genetic training strategy trains slowly . when applying the trained network to new data , the genetic training strategy gets better results when the new data is similar to the training data . it also works better when the training data is sparse . the neuroshell predictor ™ was trained using the 79 - input model in neural analysis mode using the 73 patient training data subset . subsequently , when the trained ann operating in this mode was presented with the test data subset from patients 74 - 108 , the results shown in table 4 were obtained . the neuroshell predictor ™ program was trained in the genetic mode of analysis using the 73 patient training data subset and the 79 - input model . subsequently , when the trained ann was presented with the test data subset from patients 74 - 108 , the results shown in table 5 were obtained . the associated roc curve for the diagnosis of idiopathic urticaria data is shown in fig3 . table 6 shows the relative importance of the 79 - input fields into the ann after training using the genetic mode of analysis . the information shown in tables 4 and 5 , and fig2 and 3 demonstrates that the commercially available product neuroshell predictor ™ can be used to produce an ann that is capable of performing a clinical diagnosis . however , further data analysis is needed in order to determine the optimum number of reliable data inputs needed to obtain an acceptable tool for diagnosis . accordingly , the number and combination of data inputs was progressively reduced and varied , respectively , with a view to determining a preferred number and nature of inputs for producing a reliable diagnosis . this process partly involved an analysis of the relative importance of inputs into the ann , and also utilised clinical experience and judgement . table 2 shows , in addition to the 79 - input model , 54 -, 35 -, 25 -, 21 -, 17 -, 15 -, 14 - and 9 - input models obtained by using 54 , 35 , 25 , 21 , 17 , 15 , 14 and 9 data inputs , respectively . using each input model , and each mode of operation of the ann , data was obtained concerning the ann reliability of diagnosis vis a vis use of clinical analysis . table 7 shows the mean sensitivities and specificities across all five output diagnostic categories as a function of the number of input fields utilised . the results are shown separately for the ann trained in the neural mode of analysis , in the genetic mode of analysis when trained to minimise the average number of incorrect classifications over all categories and in the genetic mode of analysis when trained to minimise the total number of incorrect classifications . tables 8 - 10 show sensitivities and specificities across the five output diagnostic categories for the 14 - input model for the differently trained anns . it can be seen that the reduced inputs set of 14 to 54 inputs provide good or excellent categorisation of urticaria / angioedema by aetiological cause . the 14 inputs were reduced to 9 inputs by eliminating the following 5 inputs from the analysis : 1 . taking nsaid or aspirin 2 . symptoms triggered by aspirin , aspirin - 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