Ragweed pollen concentration predicts seasonal rhino-conjunctivitis and asthma severity in patients allergic to ragweed

Abstract

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 ($$\tau$$ 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.

The effectiveness of pollen allergen immunotherapy on allergic rhinitis over 18 years: A national cohort study in Denmark

“…The correlation structure takes potential within-subject correlation into account by assuming within-subject dependency between observations of AR medication from two pollen seasons, and assuming that the correlation was stronger the closer in time the two pollen seasons were. 34 The main analysis estimated the effectiveness of pollen AIT on each of the three outcomes of AR medication use (with nasal inhaler use being the primary outcome) within four time intervals since baseline: 0-2, 3-5, 6-9, and 10-18 years. The intervals were chosen because in the 0-2 years interval, up-dosing and maintenance dosing takes place (see Table S1), in the 3-5 years interval a proportion of patients continue dose maintenance, while the 6-9 and 10-18 years intervals would represent the long-term effectiveness of interest, that is, continuing after end of therapy.…”

“…The autoregressive correlation structure was applied to enable inclusion of observations of several pollen seasons from the same person. The correlation structure takes potential within‐subject correlation into account by assuming within‐subject dependency between observations of AR medication from two pollen seasons, and assuming that the correlation was stronger the closer in time the two pollen seasons were 34 . The main analysis estimated the effectiveness of pollen AIT on each of the three outcomes of AR medication use (with nasal inhaler use being the primary outcome) within four time intervals since baseline: 0–2, 3–5, 6–9, and 10–18 years.…”

Predicting reproductive phenology of wind-pollinated trees via PlanetScope time series

“…3) To compress extreme values and stabilize the variance, we transformed all pollen concentration values to their square root (Bastl et al, 2018;Bonini et al, 2022) . Here, t represents the day of year.…”

Applying geostatistical hotspot analyses to a ‘double-invaded’ plant–pest co-occurrence scenario

“…), which are and will be at high allergy risk. In fact, Bonini et al (2022) found that the severity of seasonal allergies caused by A. artemisiifolia is closely connected to the levels of the plant's pollen present in the atmosphere, with symptom intensity levels associated with specific pollen concentration thresholds. In addition, large municipalities (e.g., Paris, Warsaw, London, Naples, etc.…”