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Autor(en) / Beteiligte
Titel
Ragweed pollen concentration predicts seasonal rhino-conjunctivitis and asthma severity in patients allergic to ragweed
Ist Teil von
  • Scientific reports, 2022-09, Vol.12 (1), p.15921-15921, Article 15921
Ort / Verlag
London: Nature Publishing Group UK
Erscheinungsjahr
2022
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
  • In this work, we investigate the correlation between ragweed pollen concentration and conjunctival, nasal, and asthma symptom severity in patients allergic to ragweed pollen using ambient pollen exposure in the Milan area during the 2014 ragweed season We calculate the pollen/symptom thresholds and we assess the effectiveness of ragweed allergen immunotherapy (AIT). A total of 66 participants allergic to ragweed (Amb a 1) were enrolled in the study and divided into two groups: AIT treated (24) and no AIT treated (42). Pollen counts and daily symptom/medication patient diaries were kept. Autoregressive distributed lag models were used to develop predictive models of daily symptoms and evaluate the short-term effects of temporal variations in pollen concentration on the onset of symptoms. We found significant correlations between ragweed pollen load and the intensity of symptoms for all three symptom categories, both in no AIT treated (τ = 0.341, 0.352, and 0.721; and ρ = 0.48, 0.432, and 0.881; p-value < 0.001) and in AIT treated patients ( τ = 0.46, 0.610, and 0.66; and ρ = 0.692, 0.805, and 0.824; p-value < 0.001). In both groups, we observed a positive correlation between the number of symptoms reported and drug use. Mean symptom levels were significantly higher in no AIT treated than in AIT treated patients (p-value < 0.001) for all symptom categories. Pollen concentration thresholds for the four symptom severity levels (low, medium–low, medium–high and high) were calculated. Ragweed pollen concentration is predictive of symptom severity in patients with a ragweed (Amb a 1) allergy. Patients treated with AIT had significantly reduced mean symptom levels compared to those without AIT.
Sprache
Englisch
Identifikatoren
ISSN: 2045-2322
eISSN: 2045-2322
DOI: 10.1038/s41598-022-20069-y
Titel-ID: cdi_doaj_primary_oai_doaj_org_article_ac11c33738e84370991758b9552c3026

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