Title: panPIERS (Pre-eclampsia Integrated Estimate of Risk Score): artificial intelligence-informed time-of-disease risk assessment for women with pre-eclampsia
Funder: Department of Health and Social Care

Abstract: Globally, pre-eclampsia (most dangerous form of pregnancy hypertension) causes >70,000 maternal and >500,000 perinatal deaths, and costs the NHS £300m annually. However, most pre-eclampsia is mild; only 10% of UK women with pre-eclampsia experience life-threatening or life-altering complications (e.g., stroke). Previously, we developed tools that accurately identify women at greatest, and least, risk for developing these complications – the NHS-recommended PIERS (Pre-eclampsia Integrated Estimate of RiSk) tools – miniPIERS (demographics, symptoms, signs) and fullPIERS (demographics, symptoms, signs, laboratory tests). In response to James Lind Alliance Priority Setting Partnership and NICE-identified priorities, we require an integrated tool, panPIERS. Aims WP1: Using artificial intelligence (AI), to develop a deployable panPIERS multistep hierarchical classifier to predict the probability of a combined adverse event outcome in women with pre-eclampsia by making optimal use of the variables available at any given point in time during an individual woman’s experience of pre-eclampsia. WP2: To engage with women, maternity care providers, and engineers to co-design and usability test a globally-relevant panPIERS digital health platform Work plan and public and patient involvement There will be two work packages (WPs). WP1: panPIERS model - We will use existing data (7 studies) related to over 20,000 hypertensive pregnant women, including place-specific risk variables. We will explore Artificial Neural Networks, Random Forests, Least Absolute Shrinkage and Selection Operator, and Bayesian Model Averaging to develop the panPIERS model. We will evaluate the AI tool performance at clinical presentation, and throughout disease progression. WP2: panPIERS app. Working with our patient group, care providers, and industry partner, K2 Medical, we will co-develop an app to inform individual women (for shared decision making) and their care providers, giving an accurate estimate of women’s risks. Dissemination and anticipated outcomes We will share results with women, their families, and through publications. Commercialisation planned with K2 Medical.

Lay abstract: Background Pre-eclampsia is the most dangerous form of high blood pressure in pregnancy, responsible for the deaths of over 70,000 women and 500,000 babies every year worldwide, and costs the NHS &pound;300m annually. However, most of the 1-in-30 pregnant women who develop pre-eclampsia have mild disease that goes away soon after birth. About 1-in-10 of UK women with pre-eclampsia experience complications that threaten or alter their lives (such as stroke). Previously, we developed tools that clearly identify the women who are at most, and least, risk for developing life-threatening and life-altering complications of pre-eclampsia &ndash; the NHS-recommended PIERS tools. The miniPIERS version includes details about the woman (prior births and weeks into pregnancy), her symptoms (such as headache), her blood pressure, how much protein she has in her urine, and the amount of oxygen in her blood. miniPIERS is particularly useful for women while they are outpatients. fullPIERS is very similar to miniPIERS, but adds the strength of laboratory tests to improve accuracy, and is useful once women are admitted to hospital. What is needed is a single tool, panPIERS, that uses all available data to best identify women at greatest and least risk. Aims In response to identified patient group priorities, to use artificial intelligence (AI) and existing large data sets to develop a novel panPIERS tool that accurately identifies individual women s risks. To create a new user-friendly panPIERS digital health app that is liked by women, their midwives and doctors, and engineers. Work plan and public and patient involvement There will be two work packages (WPs). WP1: A new AI-driven panPIERS model - We will use existing data related to over 20,000 women who participated in seven published projects. Some women have more or less amounts of data. We will use the strength of AI to develop and test our proposed new panPIERS tool that will include ethnicity, socio-economic status, and details of the current pregnancy (personal details, symptoms, blood pressure, blood oxygen concentration, laboratory and urine tests). We will evaluate the AI tool based on 1) how it performs initially, and 2) as the woman develops over the following days. WP2: The novel panPIERS digital health app. Working with our patient group, midwives, doctors, and industry partner, our design experts will co-develop an app to inform individual women (for shared decision making), and their care providers, giving an accurate estimate of women s risks when pre-eclampsia is either suspected or confirmed. Dissemination and anticipated outcomes We will share results with women and their families, and medical journal papers will be published. On the way to commercialisation, with K2 Medical, we plan to formally test the panPIERS app, including clinical trials, to find out if it improves outcomes.

Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING
Health categories: REPRODUCTIVE HEALTH AND CHILDBIRTH;CARDIOVASCULAR