22 results
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D1.264 - Assessment by general practitioners of a therapeutic patient education guide for allergic patients

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D1.262 - Clinical significance of a basophil activation test for Japanese beekeepers naturally sensitized to honey bee venom

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D1.265 - Component-Resolved Diagnosis and Clinical Profiles of Anisakis Allergy in Japan

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D1.266 - Investigation of anaphylaxis in mastocytosis mouse models

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D1.267 - Recurrence of perioperative anaphylaxis: analysis of a multicenter cohort

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D1.268 - The endothelial glycocalyx as a therapeutic target in anaphylaxis

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D1.269 - Deciphering cardiovascular profiles in sera and extracellular vesicles from anaphylactic patients. Impact in endothelial cells

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D1.270 - Anaphylaxis and Adrenaline: Knowledge gaps with critical consequences

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D1.271 - Bovine gelatine-induced anaphylaxis brought on by eating beef, sweets containing gelatin, and medications

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D1.272 - Efficacy and Safety of Omalizumab in Treating Severe Allergic Reactions with Urticaria as the Initial Symptom

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D1.273 - Anaphylactic Reaction Following Sulphur Hexafluoride Administration

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D3.423 - Cross-Reactivity Among Hymenoptera Venoms: A Case Study on Apis, Vespula, and Polistes Allergens

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D3.424 - Long-term efficacy and re-sting outcomes following venom immunotherapy discontinuation: A 978-patient analysis

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D3.425 - Anaphylactic reaction to carpenter bee

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D3.426 - The Frequency of Previous Large Local Reactions in a Group of 158 Patients with a History of Systemic Reaction after Insect Sting

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D3.427 - Current practices in diagnosis and treatment of Hymenoptera venom allergy (HVA) in Poland

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D3.428 - CAP-Inhibition use to diagnose genuine double sensitization to vespoid venoms: description of a spanish cohort

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D3.429 - Performance Analysis of Five Large Language Models, Including GPTo1-Preview, On an Allergy and Clinical Immunology Exam

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D3.430 - Artificial intelligence Chatbots Can Influence the Decision-Making and Behavior of Patients with Allergies: Results of a Multicenter Evaluation Study

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D3.431 - Can Artificial Intelligence-Based Large Language Models Provide Accurate and Reliable Information to Asthma Patients? A Comparative Analysis with Expert Insights