Women with gestational diabetes mellitus (GDM) are at seven-fold to ten-fold increased risk of type 2 diabetes mellitus (T2DM) when compared with those who experience a normoglycaemic pregnancy, and the cumulative incidence increases with the time of follow-up post birth. This protocol outlines the development and validation of a risk prediction model assessing the 5-year and 10-year risk of T2DM in women with a prior GDM diagnosis.

Data from all birth mothers and registered births in Victoria and South Australia, retrospectively linked to national diabetes data and pathology laboratory data from 2008 to 2021, will be used for model development and validation of GDM to T2DM conversion. Candidate predictors will be selected considering existing literature, clinical significance and statistical association, including age, body mass index, parity, ethnicity, history of recurrent GDM, family history of T2DM and antenatal and postnatal glucose levels. Traditional statistical methods and machine learning algorithms will explore the best-performing and easily applicable prediction models. We will consider bootstrapping or K-fold cross-validation for internal model validation. If computationally difficult due to the expected large sample size, we will consider developing the model using 80% of available data and evaluating using a 20% random subset. We will consider external or temporal validation of the prediction model based on the availability of data. The prediction model’s performance will be assessed by using discrimination (area under the receiver operating characteristic curve, calibration (calibration slope, calibration intercept, calibration-in-the-large and observed-to-expected ratio), model overall fit (Brier score and Cox-Snell R2) and net benefit (decision curve analysis). To examine algorithm equity, the model’s predictive performance across ethnic groups and parity will be analysed. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis-Artificial Intelligence (TRIPOD+AI) statements will be followed.

Ethics approvals have been received from Deakin University Human Research Ethics Committee (2021–179); Monash Health Human Research Ethics Committee (RES-22-0000-048A); the Australian Institute of Health and Welfare (EO2022/5/1369); the Aboriginal Health Research Ethics Committee of South Australia (SA) (04-23-1056); in addition to a Site-Specific Assessment to cover the involvement of the Preventative Health SA (formerly Wellbeing SA) (2023/SSA00065). Project findings will be disseminated in peer-reviewed journals and at scientific conferences and provided to relevant stakeholders to enable the translation of research findings into population health programmes and health policy.

Around 75 000 people suffer from hip fractures yearly in the United Kingdom (UK) leading to significant mortality and morbidity. Although mortality has dropped from 8% to 5% between 2013 and 2023 after hip fractures, those undergoing surgery for hip fractures have a 30-day readmission rate which has remained stagnant at around 11% over the same decade in the UK.

This study protocol describes a mixed-methods investigation (The ARTHUR Study—avoiding readmission after hip fracture) which aims to understand and offer solutions to prevent avoidable 30-day readmission after hip fracture surgery. The study will focus on two hospitals in acute and community settings in a large urban and ethnically diverse city in the UK.

We describe two work packages.

Work Package One (WP1) involves analysis of 5 year’s worth of routinely collected health data provided by PIONEER, a Health Data Research UK data hub in Acute Care for our local population. Work Package Two (WP2) will involve semistructured interviews with patients, carers or family members as well as non-participant observations of hospital processes to understand systems-based issues related to readmissions after hip fracture surgery. Although recruitment may be an issue, our timeline for recruitment reflects this. We also aim to recruit a diverse population, which has often been under-represented in studies into hip fractures and aim to explore relevant interventions which can be widely generalisable.

This protocol was submitted via IRAS: 330074 and obtained UK NHS REC approval via the West Midlands Coventry and Warwickshire Research Ethics Committee (REC 23/WM/0242) on 25 January 2024. The results of this study will be published in relevant scientific journals and presented at orthopaedic, fragility fracture and geriatric specialty conferences and scientific meetings. A lay summary of the findings will be publicly available on the HRA website.