Abstract
Disorders of metabolic processes in the "proteoglycans-collagen" system, changes in enzymatic reactions in patients with reactive arthritis (ReA) are often preceded by many complications, including impaired renal function. Classical regression methods are not very informative in determining the mutual burden of ReA and chronic pyelonephritis (CP), as well as the primacy of the disease.Objective - to investigate the possible relationship between ReA and CP in order to establish early criteria for predicting the development of CP on the background of ReA on the indicators of connective tissue metabolism. Material and methods. 113 patients were examined, which were divided into two groups: the first group - patients with urogenic ReA, activity I-III. FTS I-III st. (n = 65); the second group - patients with urogenic ReA and CKD I-II: pyelonephritis in the acute phase (n = 48). The control group consisted of 20 healthy individuals. The average duration of the disease of the examined patients was 24.4 ± 4.7 months. The mean age of patients was 32.5 ± 1.2 years. DataMining clustering and classification methods were used to process the obtained research results.Results. As a result of clustering methods (k-means and fuzzy clustering), the same results of cluster membership were obtained. In particular, ReA disease was correctly diagnosed in 48 cases, which is 74% of all diagnosed, 17 people (26%) were assigned to cluster "2". There is also a mismatch in the second cluster. In particular, out of 32 people diagnosed with ReA + CP, according to mathematical calculations, 28 people (88%) got into this cluster. Four patients (13%) were assigned to cluster "1" – to the group of persons in whom only one ReA disease should be diagnosed. This indicates that the boundary between the ReA and ReA + CP clusters are somewhat blurred. And this is the basis for establishing the fact that ReA disease can gradually lead to CP.Conclusions. Using DataMining clustering methods the greatest significance was defined in the diagnostic algorithm of ReA progression of such indicators as free oxyproline (FOP), protein-bound oxyproline (PBOP), the degree of collagenolytic activity (CLA) (intensity of azocol lysis), which showed a direct dependence on the degree of activity of the inflammatory process. Increases in FOP> 13.8 μmol/l, PBOP> 65.0 μmol/l and CLA (azocol)> 0.85 μg / ml in 1 h are probable risk factors for progression and early criteria for severe ReA and CP.
Highlights
В частности, верно диагностирована болезнь реактивний артрит (РеА) в 48 случаях, что составляет 74% всех диагностированных, 17 человек (26%) отнесены к кластеру «2»
Objective - to investigate the possible relationship between reactive arthritis (ReA) and chronic pyelonephritis (CP) in order to establish early criteria for predicting the development of CP on the background of ReA on the indicators of connective tissue metabolism
Material and methods. 113 patients were examined, which were divided into two groups: the first group - patients with urogenic ReA, activity I-III
Summary
За допомогою методів кластеризації DataMining встановлено найбільшу значущість у діагностичному алгоритмі прогресування РеА таких показників, як вміст у крові вільного оксипроліну (ВОП), білокзв'язаного оксипроліну (БЗОП), ступінь колагенолітичної активності (КЛА) плазми крові (інтенсивність лізису азоколу), котрі показали пряму залежність від ступеня активності запального процесу. Для обробки даних використано три різних методи кластеризації, що базуються на абсолютно різних математичних теоріях: класичний метод kсередніх, карти Кохонена (нейронні мережі), нечіткі k-середні (нечітка логіка). Однак на відміну від двох перших методів, нечітка кластеризація дозволяє встановити ступінь належності пацієнта до того чи іншого кластеру.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.