CIPHER - Collaborative integrated pregnancy High-dependancy estimation of risk

• Grant number: 12/15827-5
• Support Opportunities: Regular Research Grants
• Start date: December 01, 2012
• End date: November 30, 2015
• Field of knowledge: Health Sciences - Medicine - Maternal and Child Health
• Principal Investigator: José Guilherme Cecatti
• Grantee: José Guilherme Cecatti
• Host Institution: Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

The purpose of our study is to identify variables that predict outcome in critically ill pregnant and postpartum women. Background: Maternal mortality is a rare occurrence in the developed world, with an adjusted maternal mortality ratio of 12 - 24 per 100,000 women in North America. However, worldwide, H 350,000 women die each year due to pregnancy-related complications1. Maternal Intensive Care Unit (ICU) admissions follow both obstetric and non-obstetric complications in pregnancy. 0.25-1.5% of hospital admissions during pregnancy will require admission to the ICU. About two-thirds of these admissions are due to obstetric causes (e.g. haemorrhage and pre-eclampsia) and one-third is due to maternal medical or surgical complications. Pregnant women with underlying medical conditions are over-represented in maternal mortality and severe morbidity statistics.A number of critical care outcome prediction models exist in ICU to predict hospital mortality, by incorporating measures of physiologic derangement and co-morbidities. The most commonly used models are the Acute Physiology and Chronic Health Evaluation (APACHE) and the Simplified Acute Physiology Score (SAPS). Their use in obstetric populations admitted to ICU for obstetric reasons to predict hospital mortality has a tendency to overestimate mortality.Pregnancy and the post-partum state have unique physiology. Maternal cardiac output, respiratory rate and heart rate increase in pregnancy11. Equally, maternal "normal range" blood values are altered in pregnancy, with lower levels of creatinine, haematocrit & blood urea nitrogen. No outcome prediction models have been designed specifically for use in obstetric patients. The identification of variables that predict outcome in pregnant or recently delivered women admitted to the ICU, is the first step in the development of a new clinical prediction model for obstetric patients in the ICU. Such a tool will assist in providing more aggressive management to those that require it most.AIM: To developing and evaluating a prediction tool for maternal morbidity or mortality for pregnant or recently delivered women in ICU: The Collaborative Integrated Pregnancy High-dependency Estimate of Risk (CIPHER). This study is being carried out in a number of tertiary care hospitals worldwide looking at ICU data. (AU)