Online Program

Movement and pulse index: A clinical prediction model to improve fetal surveillance

Wednesday, November 6, 2013 : 12:30 p.m. - 12:50 p.m.

Laura Schummers, SM student, Department of Epidemiology; Division of Midwifery, Harvard School of Public Health; University of British Columbia, Boston, MA
Lisa Paine, CNM, DrPH, The Hutchinson Dyer Group, Cambridge, MA
KS Joseph, MD, PhD, Department of Obstetrics and Gynaecology; School of Population and Public Health;, University of British Columbia, Vancouver, BC, Canada
Saraswathi Vedam, RM, FACNM, MSN, SciD(h.c.), Division of Midwifery, Department of Family Practice, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
Background: Fetal health assessment aims to identify fetuses at risk for stillbirth or neonatal mortality but the poor validity of the current tests can lead to iatrogenic intervention. Most tests are high-technology, which limits their use in low resources settings. In 2009, an NIH committee identified the need for innovation in antenatal testing, with specific attention toward fetal movement assessments and novel combinations of test results. Methods: Our team piloted two innovative combined tests: 1) Movement and Pulse index (MAPi), a clinical prediction model that uses appropriate statistical methods to combine novel and extant indicators of fetal well-being and 2) MobileMAPi, a low-cost, low-technology model for use in low-resource settings. We studied pregnant women receiving standard antenatal testing (NST: Non-Stress Test, AFI: Amniotic Fluid Index), and added a newly developed Fetal Movement and Behavior Log and the Auscultated Acceleration Test (AAT), a low-technology test developed in 1986 by midwives as an innovation in low-technology fetal assessment. Results: 51 participants were recruited into our pilot study, for a total of 194 AATs, 97 NSTs, and 55 AFIs performed, and 260 completed Fetal Behavior and Movement Logs. The rate of neonatal morbidity was 5.3%, and the rate of cesarean delivery was 34.2%. Pilot results confirmed feasibility for combining parameters from each assessment modality to develop MAPi and MobileMAPi, and will inform our subsequent research in this area. Conclusion: Mapi and MobileMAPi are innovations that could reduce stillbirth rates and maternal-newborn morbidity, and enhance the availability of fetal surveillance methods in low-resource settings.

Learning Areas:

Clinical medicine applied in public health
Conduct evaluation related to programs, research, and other areas of practice
Other professions or practice related to public health
Public health or related nursing
Public health or related research

Learning Objectives:
Describe how an innovative clinical prediction model that combines results from multiple tests may address shortcomings of the current antenatal testing programs, improve maternal and neonatal outcomes, and expand antenatal care in all settings.

Keyword(s): Birth Outcomes, Prenatal Care

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have worked as the Research Manager for the Division of Midwifery at the University of British Columbia since 2008. I worked as the Coordinator for this study of antenatal fetal health surveillance since 2009. I am currently a Masters of Science student in the Department of Epidemiology at the Harvard School of Public Health. My scientific interests are related to perinatal epidemiology and birth outcomes.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.