Intrapartum Electronic Foetal Monitoring : Does it Lead or Mislead?

A cross-sectional comparison of three guidelines for intrapartum cardiotocography

OBJECTIVE

To compare the cardiotocography classification systems outlined by the International Federation of Gynecology and Obstetrics (FIGO) in 2015 and the UK National Institute for Health and Care Excellence (NICE) in 2007 and 2014.

METHODS

A cross-sectional observational study of cardiotocography practices at a UK hospital was conducted among labor ward staff (n=21) from November 1 to November 31, 2015. All observers classified ten cardiotocography traces according to the three guidelines using a bespoke form. Outcome measures included interobserver agreement (κ values), percentage agreement, intervention rate, and perceived ease of use.

RESULTS

The κ values were 0.38 (FIGO 2015), 0.37 (NICE 2007), and 0.34 (NICE 2014). The percentage agreement was identical across the three systems for both normal cardiotocography results (100.0%) and for intermediate or suspicious results (80.9%). By contrast, the percentage agreement for abnormal or pathological findings was 47.6% for NICE 2014, 76.2% for FIGO 2015, and 91.0% for NICE 2007 guidelines. Among 210 observations, intervention was deemed necessary for 48 (22.9%) for FIGO 2015, 29 (13.8%) for NICE 2014, and 56 (26.7%) for NICE 2007 guidelines. The FIGO 2015 system was considered the easiest to use by 13 (61.9%) observers.

CONCLUSION

Interobserver agreement of cardiotocography classification is suboptimal. The FIGO 2015 system offered favorable agreement scores, perceived ease of use, and a moderate intervention rate.

A mobile multi-agent information system for ubiquitous fetal monitoring

Electronic fetal monitoring (EFM) systems integrate many previously separate clinical activities related to fetal monitoring. Promoting the use of ubiquitous fetal monitoring services with real time status assessments requires a robust information platform equipped with an automatic diagnosis engine. This paper presents the design and development of a mobile multi-agent platform-based open information systems (IMAIS) with an automated diagnosis engine to support intensive and distributed ubiquitous fetal monitoring. The automatic diagnosis engine that we developed is capable of analyzing data in both traditional paper-based and digital formats. Issues related to interoperability, scalability, and openness in heterogeneous e-health environments are addressed through the adoption of a FIPA2000 standard compliant agent development platform—the Java Agent Development Environment (JADE). Integrating the IMAIS with light-weight, portable fetal monitor devices allows for continuous long-term monitoring without interfering with a patient’s everyday activities and without restricting her mobility. The system architecture can be also applied to vast monitoring scenarios such as elder care and vital sign monitoring.