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BackgroundThe first wave of the London COVID-19 epidemic peaked in April 2020. Attention initially focused on severe presentations, intensive care capacity, and the timely supply of equipment. While general practice has seen a rapid uptake of technology to allow for virtual consultations, little is known about the pattern of suspected COVID-19 presentations in primary care.AimTo quantify the prevalence and time course of clinically suspected COVID-19 presenting to general practices, to report the risk of suspected COVID-19 by ethnic group, and to identify whether differences by ethnicity can be explained by clinical data in the GP record.Design and settingCross-sectional study using anonymised data from the primary care records of approximately 1.2 million adults registered with 157 practices in four adjacent east London clinical commissioning groups. The study population includes 55% of people from ethnic minorities and is in the top decile of social deprivation in England.MethodSuspected COVID-19 cases were identified clinically and recorded using SNOMED codes. Explanatory variables included age, sex, self-reported ethnicity, and measures of social deprivation. Clinical factors included data on 16 long-term conditions, body mass index, and smoking status.ResultsGPs recorded 8985 suspected COVID-19 cases between 10 February and 30 April 2020.Univariate analysis showed a two-fold increase in the odds of suspected COVID-19 for South Asian and black adults compared with white adults. In a fully adjusted analysis that included clinical factors, South Asian patients had nearly twice the odds of suspected infection (odds ratio [OR] = 1.93, 95% confidence interval [CI] = 1.83 to 2.04). The OR for black patients was 1.47 (95% CI = 1.38 to 1.57).ConclusionUsing data from GP records, black and South Asian ethnicity remain as predictors of suspected COVID-19, with levels of risk similar to hospital admission reports. Further understanding of these differences requires social and occupational data.

ObjectivesTo characterise gaps in antihypertensive treatment in people with hypertension and statin treatment in people with cardiovascular diseases (CVD) in a large urban population and quantify the health and economic impacts of their optimisation.DesignA cross-sectional population study and a long-term CVD decision model.SettingPrimary care, UK.ParticipantsAll adults with diagnosed hypertension or CVD in a population of about 1 million people, served by 123 primary care practices in London, UK in 2019.InterventionsFollowing UK clinical guidelines, all adults with diagnosed hypertension were categorised into optimal, suboptimal and untreated groups with respect to their antihypertensive treatment, and all adults with diagnosed CVD were categorised in the same manner with respect to their statin treatment.OutcomesProportion of patients suboptimally treated or untreated. Projected cardiovascular events avoided, years and quality-adjusted life years (QALYs) gained and healthcare costs saved with optimised treatments.Results21 954 of the 91 828 adults with hypertension (24%; mean age 59 years; 49% women) and 9062 of the 23 723 adults with CVD (38%; mean age 69 years; 43% women) were not optimally treated with antihypertensive or statin treatment, respectively. Per 1000 additional patients optimised over 5 years, hypertension treatment is projected to prevent 25 (95% CI 16 to 32) major vascular events (MVEs) and 7 (3 to 10) vascular deaths, statin treatment, 28 (22 to 33) MVEs and 6 (4 to 7) vascular deaths. Over their lifespan, a patient with uncontrolled hypertension aged 60–69 years is projected to gain 0.64 (95% CI 0.36 to 0.87) QALYs with optimised hypertension treatment, and a similarly aged patient with previous CVD not optimally treated with statin is projected to gain 0.3 (0.24 to 0.37) QALYs with optimised statin treatment. In both cases, the hospital cost savings minus extra medication costs were about £1100 per person over remaining lifespan.ConclusionsOptimising cardiovascular treatments can cost-effectively reduce cardiovascular risk and improve life expectancy.

A controversy exists concerning the relationship, if any, between obstructive sleep apnea (OSA) and the anatomical position of the anterior teeth. Specifically, there has been speculation that extraction orthodontics and retraction of the anterior teeth contributes to OSA by crowding the tongue and decreasing airway space. This retrospective study utilized electronic medical and dental health records to examine the association between missing premolars and OSA.The sample (n = 5,584) was obtained from the electronic medical and dental health records of HealthPartners in Minnesota. Half of the subjects (n = 2,792) had one missing premolar in each quadrant. The other half had no missing premolars. Cases and controls were paired in a 1:1 match on age range, gender, and body mass index (BMI) range. The outcome was the presence or absence of a diagnosis of OSA confirmed by polysomnography.Of the subjects without missing premolars, 267 (9.56%) had received a diagnosis of OSA. Of the subjects with four missing premolars, 299 (10.71%) had received a diagnosis of OSA. The prevalence of OSA was not significantly different between the groups (OR = 1.14, p = 0.144).The absence of four premolars (one from each quadrant), and therefore a presumed indicator of past "extraction orthodontic treatment," is not supported as a significant factor in the cause of OSA.

Summary Yeast are among the most frequent pathogens in humans. The dominant yeast causing human infections belong to the genus Candida and Candida albicans is the most frequently isolated species. However, several non-C. albicans species are becoming increasingly common in patients worldwide. The relationships between yeast in humans and the natural environments remain poorly understood. Furthermore, it is often difficult to identify or exclude the origins of disease-causing yeast from specific environmental reservoirs. In this study, we compared the yeast isolates from tree hollows and from clinics in Hamilton, Ontario, Canada. Our surveys and analyses showed significant differences in yeast species composition, in their temporal dynamics, and in yeast genotypes between isolates from tree hollows and hospitals. Our results are inconsistent with the hypothesis that yeast from trees constitute a significant source of pathogenic yeast in humans in this region. Similarly, the yeast in humans and clinics do not appear to contribute to yeast in tree hollows.