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Abstract/Summary
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Background!#!Mast cell activation syndrome (MCAS) is a clinically heterogeneous disease with allergy-like symptoms and abdominal complaints. Its etiology is only partially understood and it is often overlooked.!##!Aims!#!The aim of this study was to identify subgroups of MCAS patients to facilitate diagnosis and allow a personalized therapy.!##!Methods!#!Based on data from 250 MCAS patients, hierarchical and two-step cluster analyses as well as association analyses were performed. The data used included data from a MCAS checklist asking about symptoms and triggers and a set of diagnostically relevant laboratory parameters.!##!Results!#!Using a two-step cluster analysis, MCAS patients could be divided into three clusters. Physical trigger factors were particularly decisive for the classification as they showed remarkable differences between the three clusters. Cluster 1, labeled high responders, showed high values for the triggers heat and cold, whereas cluster 2, labeled intermediate responders, presented with high values for the trigger heat and low values for cold. The third cluster, labeled low responders, did not react to thermal triggers. The first two clusters showed more divers clinical symptoms especially with regard to dermatological and cardiological complaints. Subsequent association analyses revealed relationships between triggers and clinical complaints: Abdominal discomfort is mainly triggered by histamine consumption, dermatological discomfort by exercise, and neurological symptoms are related to physical exertion and periods of starvation. The reasons for the occurrence of cardiological complaints are manifold and triggers for respiratory complaints still need better identification.!##!Conclusion!#!Our study identified three distinct clusters on the basis of physical triggers, which also differ significantly in their clinical symptoms. A trigger-related classification can be helpful in clinical practice for diagnosis and therapy. Longitudinal studies should be conducted to further understand the relationship between triggers and symptoms.
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1000
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Hinweis
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DeepGreen-ID: fc7afbcabac64180ad32495499bb1a7f ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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