OBJECTIVES: This study is aimed at identifying discrete severity classes among adults with hypermobile Ehlers-Danlos syndrome (hEDS)/hypermobility spectrum disorders (HSD). METHODS: Subjects were selected according to the old and new nomenclatures and all completed a set of questionnaires exploring pain, fatigue, dysautonomic symptoms, coordination and attention/concentration deficits and quality of life in general. Data were investigated by hierarchical clustering on principal components. Cluster comparisons were then performed by using the two-sample unpaired t test and the standardized mean difference was reported as a measure of effect size. Conditional classification tree analysis and multivariable logistic regression were carried out in order to identify the profiles that were at higher risk to belong to the more severe cluster. Weighted linear combination was used to identify a numerical score measuring this risk. RESULTS: A total of 105 patients were selected and distributed in two distinct severity groups. These groups were statistically separated on the basis of 47 of 59 items/characteristics. One group featured the worse values of most questionnaire items (complex/severe cluster) and the other was dominated by the better values (simplex/milder cluster). Only three items were able to stratify patients according to their risk to belong to the complex cluster. A severity score was then constructed on these three items. CONCLUSION: Adults with hEDS/HSD can be separated in two severity classes, which do not mirror either the old or new criteria for hEDS. The identified severity score could allow a bi-dimensional approach to adults with hEDS/HSD for optimal management planning.

Severity classes in adults with hypermobile Ehlers-Danlos syndrome/hypermobility spectrum disorders: a pilot study of 105 Italian patients

Colombi, Marina;
2019-01-01

Abstract

OBJECTIVES: This study is aimed at identifying discrete severity classes among adults with hypermobile Ehlers-Danlos syndrome (hEDS)/hypermobility spectrum disorders (HSD). METHODS: Subjects were selected according to the old and new nomenclatures and all completed a set of questionnaires exploring pain, fatigue, dysautonomic symptoms, coordination and attention/concentration deficits and quality of life in general. Data were investigated by hierarchical clustering on principal components. Cluster comparisons were then performed by using the two-sample unpaired t test and the standardized mean difference was reported as a measure of effect size. Conditional classification tree analysis and multivariable logistic regression were carried out in order to identify the profiles that were at higher risk to belong to the more severe cluster. Weighted linear combination was used to identify a numerical score measuring this risk. RESULTS: A total of 105 patients were selected and distributed in two distinct severity groups. These groups were statistically separated on the basis of 47 of 59 items/characteristics. One group featured the worse values of most questionnaire items (complex/severe cluster) and the other was dominated by the better values (simplex/milder cluster). Only three items were able to stratify patients according to their risk to belong to the complex cluster. A severity score was then constructed on these three items. CONCLUSION: Adults with hEDS/HSD can be separated in two severity classes, which do not mirror either the old or new criteria for hEDS. The identified severity score could allow a bi-dimensional approach to adults with hEDS/HSD for optimal management planning.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/516910
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