Outcomes for older people with screening-detected versus existing chronic kidney disease: a cohort study with data linkage.

Background: Chronic kidney disease (CKD) is a common health problem associated with increased risk of cardiovascular disease (CVD), end-stage kidney disease (ESKD), and premature death. It is estimated that one-third of people aged ≥70 years have CKD globally, many of whom are undiagnosed, but little is known about the value of screening.

Aim: To compare the risk of adverse health outcomes between people with an existing diagnosis of CKD and those identified through screening, and identify factors associated with mortality in CKD.

In-Clinic and Natural Gait Observations master protocol (I-CAN-GO) to validate gait using a lumbar accelerometer.

Traditional measurements of gait are typically performed in clinical or laboratory settings where functional assessments are used to collect episodic data, which may not reflect naturalistic gait and activity patterns. The emergence of digital health technologies has enabled reliable and continuous representation of gait and activity in free-living environments. To provide further evidence for naturalistic gait characterization, we designed a master protocol to validate and evaluate the performance of a method for measuring gait derived from a single lumbar-worn accelerometer with respect to reference methods.

Accuracy of Inferences About the Reproductive Number and Superspreading Potential of SARS-CoV-2 with Incomplete Contact Tracing Data.

The basic reproductive number (R) and superspreading potential are key epidemiological parameters that inform our understanding of a disease's transmission. Often these values are estimated using the data obtained from contact tracing studies. Here we performed a simulation study to understand how incomplete data due to preferential contact tracing impacted the accuracy and inferences about the transmission of SARS-CoV-2.

Development and validation of a novel risk prediction algorithm to estimate 10-year risk of oesophageal cancer in primary care: prospective cohort study and evaluation of performance against two other risk prediction models.

Background: Methods to identify patients at increased risk of oesophageal cancer are needed to better identify those for targeted screening. We aimed to derive and validate novel risk prediction algorithms (CanPredict) to estimate the 10-year risk of oesophageal cancer and evaluate performance against two other risk prediction models.

Methods: Prospective open cohort study using routinely collected data from 1804 QResearch® general practices.

Hormone replacement therapy and cancer survival: a longitudinal cohort study: protocol paper.

Introduction: Hormone replacement therapy (HRT) can help women experiencing menopausal symptoms, but usage has declined due to uncertainty around risks of cancer and some cardiovascular diseases (CVD). Moreover, improved cancer survival rates mean that more women who survive cancer go on to experience menopausal symptoms. Understanding these relationships is important so that women and their clinicians can make informed decisions around the risks and benefits of HRT.