AB1063 Diagnostic Classification of Ileum-Lumbar Ligamentite

• Published in: Annals of the rheumatic diseases Vol. 74; no. Suppl 2; p. 1255
• Main Authors: Wolenski, L., Bizzi, E., Galletti, S., Galletti, R., Marchi, A.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Limited 01.06.2015
• ISSN: 0003-4967; 1468-2060
• DOI: 10.1136/annrheumdis-2015-eular.4395

BackgroundThe involvement of the ileum-lumbar ligamentite (ILL) by degenerative or inflammatory processes is difficult to detect, however it is common and a cause of pain and disability. The differential diagnosis of pain, caused by inflammatory processes borne by the ILL is complex and not always clinical semiotic guarantees a certain diagnosis.ObjectivesThe objective of the study is on identifying an echographic approach through the analysis of quantitative parameters, aimed at the eventual confirmation of diagnosis of ileum-lumbar ligamentite solely based on clinical symptoms.MethodsThe ultrasound evaluation of ILL was performed by placing the patient prone and using in the lumbar region, a linear probe for the identification of a precise point of reference for the ILL.The variable sonographic P1, consisting in the iliac insertion of the ligament, was established at 0.5 cm from the iliac crest, along the course of the ligament (Figure 2). At the level of P1 was evaluated the thickness of the ILL in both healthy subjects and in subjects in which clinical semiotic posed diagnosis of inflammatory involvement of the ILL to highlight the possible correlations between the thickness of the ILL and the clinical diagnosis. Thus a binary variable concerning the clinical diagnosis was added to the quantitative variable.The variables were submitted to a statistical analysis through the development of a binary logistic regression model, in which we assumed the diagnosis as the dependent variable and the variable thickness as regressor, with the goal of understanding if the echographic (ligament thickness in P1) and the clinical variables are interrelated.ResultsThe analysis sample is made up of 84 patients, of which 43 are healthy subjects.Demographic statistics are shown (Table 1).The analysis of quantitative statistics through distribution graph Box-plot (Figure 1) highlights an important and significant correlation between the clinical diagnosis and parameter P1, where there is an association between lower values of P1 variable and healthy patients and vice versa.In addition, healthy patients have lower dispersion with a median equal to 2.20 mm and half of patients are distributed around the median, with values ranging between 2.10 and 2.50 mm.Conversely ill patients have a median value of P1 of 3.4 mm.From binary logistic regression analysis, we affirm that the estimated model was able to correctly predict 90.5% of cases, in particular 93% of healthy subjects and 87.8% of pathological subjects (Table 2).ConclusionsThis preliminary study could enhance the role of ultrasonography in the diagnosis of ileum lumbar ligamentite.Disclosure of InterestNone declared