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1.  Seasonality, incidence and prognosis in atrial fibrillation and stroke in Denmark and New Zealand 
BMJ Open  2012;2(4):e001210.
There are relatively few large studies of seasonal variation in the occurrence of stroke in patients with atrial fibrillation (AF). We investigated the seasonal variation in incidence rates of hospitalisation with stroke in patients from Denmark and New Zealand.
Cohort study.
Nationwide hospital discharge data from Denmark and New Zealand.
243 381 (median age 75) subjects having a first-time hospitalisation with AF in Denmark and 51 480 (median age 76) subjects in New Zealand constituted the study population. Subjects with previous hospitalisation with stroke were excluded.
Primary and secondary effect measures
Peak-to-trough ratio of the seasonal variation in incidence rates of stroke in AF patients adjusted for an overall trend was primary effect measure and was assessed using a log-linear Poisson regression model. Secondary effect measures were incidence rate ratios of AF and 30-day case fatality for stroke patients.
Incidence rates of AF per 1000 person-years in Denmark increased by 5.4% (95% CI 5.3% to 5.7%) for patients aged <65 and 5% (95% CI 4.9% to 5.1%) for patients aged ≥65, whereas the increase was 0.2% (95% CI −0.2% to 0.6%) for patients aged <65 and 2.6% (95% CI 2.4% to 2.8%) for patients aged ≥65 in New Zealand. In Denmark 36 088 subjects were hospitalised with stroke, and 7518 subjects in New Zealand, both showing peaks during winter with peak-to-trough ratios of 1.22 and 1.27, respectively and a decreasing trend. The 30-day case fatality risk for stroke patients having AF is now (2000–2008) about 20% in both countries.
Although incidence rates of hospitalisation with stroke in patients with AF have decreased in recent years, stroke remains a common AF complication with a high case fatality risk. The marked winter peak in incidence rates of hospitalisation with stroke in AF patients suggests that there are opportunities to reduce this complication. Further studies are necessary to identify how to optimise treatment of AF and prevention of stroke.
PMCID: PMC3432837  PMID: 22923628
Neurology; Stroke; Atrial fibrillation; Seasonal variation; Epidemiology; Internal Medicine; Cardiology; Poisson regression
2.  Self-diagnosis of influenza during a pandemic: a cross-sectional survey 
BMJ Open  2011;1(2):e000234.
Self-diagnosis of influenza is an important component of pandemic control and management as it may support self-management practices and reduce visits to healthcare facilities, thus helping contain viral spread. However, little is known about the accuracy of self-diagnosis of influenza, particularly during pandemics.
We used cross-sectional survey data to correlate self-diagnosis of influenza with serological evidence of 2009 pandemic influenza A(H1N1) infection (haemagglutination inhibition titres of ≥1:40) and to determine what symptoms were more likely to be present in accurate self-diagnosis. The sera and risk factor data were collected for the national A(H1N1) seroprevalence survey from November 2009 to March 2010, 3 months after the first pandemic wave in New Zealand (NZ).
The samples consisted of 318 children, 413 adults and 423 healthcare workers. The likelihood of being seropositive was no different in those who believed they had influenza from those who believed they did not have influenza in all groups. Among adults, 23.3% (95% CI 11.9% to 34.7%) of those who reported having had influenza were seropositive for H1N1, but among those reporting no influenza, 21.3% (95% CI 13% to 29.7%) were also seropositive. Those meeting NZ surveillance or Ministry of Health influenza case definitions were more likely to believe they had the flu (surveillance data adult sample OR 27.1, 95% CI 13.6 to 53.6), but these symptom profiles were not associated with a higher likelihood of H1N1 seropositivity (surveillance data adult sample OR 0.93, 95% CI 0.5 to 1.7).
Self-diagnosis does not accurately predict influenza seropositivity. The symptoms promoted by many public health campaigns are linked with self-diagnosis of influenza but not with seropositivity. These findings raise challenges for public health initiatives that depend on accurate self-diagnosis by members of the public and appropriate self-management action.
Article summary
Article focus
To determine whether lay people can accurately recognise influenza infection.
Key messages
Individuals meeting influenza case definitions were more likely to believe they had influenza.
Self-diagnosis, whether by a lay person or a healthcare worker, did not accurately predict influenza seropositivity.
Strengths and limitations of this study
This is the first published study of the effectiveness of self-diagnosis of influenza compared with laboratory evidence of infection in a broad population-based sample during a pandemic.
Some of the participants who believed they had the flu may have had a seasonal influenza or other respiratory pathogens (although H1N1 was the dominant influenza strain).
This survey was based on symptom recall rather than symptom reports, which may reflect the participants' enduring perceptions of influenza, likely to guide their behaviour in future influenza epidemics.
PMCID: PMC3191601  PMID: 22021887

Results 1-2 (2)