Highlights Higher step count is inversely associated with the risk of premature death and cardiovascular events. As measured by accelerometers, 8959 steps/day (Q3) had a 40.36% lower risk of all-cause mortality than 4183 steps/day (Q1). As measured by accelerometers, 9500 steps/day (Q3) had a 35.05% lower risk of cardiovascular events than 3500 steps/day(Q1). These associations were in nonlinear dose–response patterns.

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Summary Background Although solely topical treatment often suffices, patients with psoriasis may require more intensive treatment (phototherapy and/or systemic treatments) to control their disease. However, in paediatric, adolescent and young adult patients, little is known about persistence of topical treatment and time until switch to systemic treatment. Objectives To determine the median time from psoriasis onset until (i) discontinuation of solely topical agents and (ii) switch to systemic treatment, and to identify patient characteristics associated with switching to systemic treatments. Methods Data were extracted from the Child‐CAPTURE registry, a prospective, observational cohort of patients with paediatric‐onset psoriasis followed into young adulthood from 2008 to 2018. Data prior to inclusion in the registry were collected retrospectively. Median times were determined through Kaplan–Meier survival analyses. Cox regression analysis was used to identify patient characteristics associated with switch to systemic treatment. Results Of 448 patients, 62·3% stayed on solely topical treatment until data lock; 14·3% switched from topicals to phototherapy, but not to systemic treatment; and 23·4% switched to systemic treatment. The median time from psoriasis onset until discontinuation of solely topical treatment was 7·3 years, and until switch to systemics was 10·8 years. Higher Psoriasis Area and Severity Index and (Children’s) Dermatology Life Quality Index > 5 were independently associated with switching to systemic treatment. Conclusions In a population of paediatric and adolescent patients with mild‐to‐severe psoriasis, one‐third needed more intensive treatment than solely topical therapy to control their disease. We consider the median time until switching to systemics to be long.

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Objective: The aim of this study was to identify, describe, and evaluate the available cardiovascular disease risk prediction models developed or validated in the hypertensive population. Methods: MEDLINE and the Web of Science were searched from database inception to March 2019, and all reference lists of included articles were reviewed. Results: A total of 4766 references were screened, of which 18 articles were included in the review, presenting 17 prediction models specifically developed for hypertensive populations and 25 external validations. Among the 17 prediction models, most were constructed based on randomized trials in Europe or North America to predict the risk of fatal or nonfatal cardiovascular events. The most common predictors were classic cardiovascular risk factors such as age, diabetes, sex, smoking, and SBP. Of the 17 models, only one model was externally validated. Among the 25 external validations, C-statistics ranged from 0.58 to 0.83, 0.56 to 0.75, and 0.64 to 0.78 for models developed in the hypertensive population, the general population and other specific populations, respectively. Most of the development studies and validation studies had an overall high risk of bias according to PROBAST. Conclusion: There are a certain number of cardiovascular risk prediction models in patients with hypertension. The risk of bias assessment showed several shortcomings in the methodological quality and reporting in both the development and validation studies. Most models developed in the hypertensive population have not been externally validated. Compared with models developed for the general population and other specific populations, models developed for the hypertensive population do not display a better performance when validated among patients with hypertension. Research is needed to validate and improve the existing cardiovascular disease risk prediction models in hypertensive populations rather than developing completely new models.