Objective: Antihistamines are among the most prescribed medicines in otorhinolaryngology. This drug is excellent for rhinorrhea, sneezing and itching, however, it has a debatable effect in rhinosinusitis. At this point, it is useful to examine the relationship between antihistamine and the incidence of sinusitis based on large-cohort data analysis. Design: Retrospective study Setting: A Nationwide cohort study which used population-based insurance data (consisting of data from approximately 1 million patients). Participants: The antihistamine (AH) group consisted of patients who were diagnosed with allergic rhinitis (AR) between January 1, 2003 and December 31, 2003, taking at least one dose of antihistamine. Non-antihistamine (non-AH) group of patients who did not take antihistamines was obtained by 1:4 propensity score matching. Main outcome measures: Primary endpoint was the occurrence of sinusitis. Results: The adjusted hazard ratio for the sinusitis in the AH group was 1.53 [95% CI: 1.36-1.72] compared with the non-AH group. Sinusitis was more frequent in women (HR: 1.34), and less frequent the older the age (HR: 0.74, 0.58, 0.46, respectively) after exposure to antihistamine. In the subgroup analysis regarding the AH usage duration, there was no significant difference between the four subgroups. Conclusion: Antihistamines are probably the most prescribed medicines in the rhinologic area. But as all things have advantages and disadvantages, this large-scale longitudinal study shows that antihistamines are closely associated with sinusitis regardless of prescription duration and thus should be cautiously prescribed.

Background: Chronic obstructive pulmonary disease (COPD) exacerbation (CE) is characterized by the rapid deterioration of respiratory symptoms caused by air pollution, but there have been no comprehensive studies with regard to the age-stratified effect of air pollution. We investigate the short-term effects of air pollution and environmental factors on CE. Methods: By merging the individualized environmental data and Korea’s National Health Insurance cohort, we conducted Quasi-Poisson analysis to evaluate the effects of air pollutants and environmental factors on CE. Results: From January 2007 to December 2012, a total of 15110 CE events occurred, which showed seasonal dynamics in CE events, air pollutants (particulate matter less than 10 µm (PM10), NO2, SO2) and environmental factors (wind speed (WS), solar sunshine (SS)). The only factor affecting CE was PM10, and this occurred on lag days 4, 5, and 6 and had a peak hazard ratio (HR) of 1.0404 on lag day 5. PM10 also had a lag-cumulative effect on CE risk from lag day 6 to lag day 10. In subgroup analysis on age and level of parameters, each factor had a different significant effect on CE on different lag days. Conclusions: PM10 uniquely affects CE at lag-specific day 5 (from lag day 4 to lag day 6). PM10 also had a lag-cumulative effect on CE risk which showed a pattern proportional to the concentration of PM10. Considering the subgroup analysis, we need to devise different strategies for air pollutants and age for patients with COPD exacerbation.