Risk Stratification for Cardiovascular Disease: A Comparative Analysis of Cluster Analysis and Traditional Prediction Models.

Aim: Primary prevention of cardiovascular disease (CVD) relies on effective risk stratification to guide interventions. Current models, primarily developed using regression analysis, can lead to inaccurate estimates when applied to external populations. This study evaluates the utility of cluster analysis as an alternative method for developing CVD risk stratification models, comparing its performance with established CVD risk prediction models.

Health-related quality of life in surgically treated asymptomatic meningioma patients: A population-based matched cohort study.

Background: Asymptomatic patients with meningiomas are increasingly detected, where management can be challenging in terms of surgery versus watchful waiting. Health-related quality of life (HRQoL) is an important factor in clinical decision-making, albeit not greatly studied in this patient group. The aim of this paper is to map the HRQoL among patients with surgically removed asymptomatic meningioma as compared to the general population.

Predicting new cases of hypertension in Swedish primary care with a machine learning tool.

Background: Many individuals with hypertension remain undiagnosed. We aimed to develop a predictive model for hypertension using diagnostic codes from prevailing electronic medical records in Swedish primary care.

Methods: This sex- and age-matched case-control (1:5) study included patients aged 30-65 years living in the Stockholm Region, Sweden, with a newly recorded diagnosis of hypertension during 2010-19 (cases) and individuals without a recorded hypertension diagnosis during 2010-19 (controls), in total 507,618 individuals.

The influence of the COVID-19 pandemic on physical activity in Stockholm County - Evidence from time series models of smartphone measured daily steps data spanning over 3 years.

Background: It has been reported that physical activity levels decreased during the COVID-19 pandemic. Previous studies often relied on self-reported physical activity, which has low accuracy. Studies based on objectively measured physical activity have had short data collection periods, thereby not allowing the consideration of pre-pandemic levels of physical activity or the influence over the different waves of the pandemic.

Undiagnosed type 2 diabetes is common - intensified screening of established risk groups is imperative in Sweden: the SDPP cohort.

Background: Undiagnosed type 2 diabetes (T2D) is a global problem. Current strategies for diagnosis in Sweden include screening individuals within primary healthcare who are of high risk, such as those with hypertension, obesity, prediabetes, family history of diabetes, or those who smoke daily. In this study, we aimed to estimate the proportion of individuals with undiagnosed T2D in Stockholm County and factors associated with T2D being diagnosed by healthcare.