Research article

An evaluation of classification systems for stillbirth

Vicki Flenady^{* 1,2} , J Frederik Frøen^{* 3,4} , Halit Pinar⁵ , Rozbeh Torabi⁵ , Eli Saastad^3,6 , Grace Guyon⁷ , Laurie Russell⁸ , Adrian Charles⁹ , Catherine Harrison⁹ , Lawrence Chauke⁹ , Robert Pattinson¹⁰ , Rachel Koshy¹¹ , Safiah Bahrin¹¹ , Glenn Gardener¹ , Katie Day¹ , Karin Petersson¹² , Adrienne Gordon¹³ and Kristen Gilshenan¹

¹Mater Mothers' Research Centre, Mater Health Services, Brisbane, Australia

²Department of Obstetrics and Gynecology, University of Queensland, Brisbane, Australia

³Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Oslo, Norway

⁴Department of Obstetrics, Gynecology and Reproductive Biology, Harvard Medical School, Boston, MA, USA

⁵Department of Pathology and Laboratory Medicine, Brown University Medical School, Providence, RI, USA

⁶Department of Midwifery, Faculty of Nursing Education, Arkeshus University College, Lillestrøm, Norway

⁷Alberta Perinatal Health Program, Edmonton, Canada

⁸Division of Anatomical Pathology, Department of Laboratory Medicine & Pathology, University of Alberta Hospitals, University of Alberta, Edmonton, Canada

⁹Department of Paediatric and Perinatal Pathology, King Edward Memorial Hospital, Perth, Australia

¹⁰Department of Obstetrics and Gynaecology, University of Pretoria School of Medecine, Pretoria, South Africa

¹¹Division of Family Health Development, Ministry of Health Malaysia, Putrajaya, Malaysia

¹²Department of Obstetrics, Karolinska University Hospital, Stockholm, Sweden

¹³Department of Neonatal Medicine, Royal Prince Alfred Hospital, Sydney, Australia

author email corresponding author email* Contributed equally

BMC Pregnancy and Childbirth 2009, 9:24doi:10.1186/1471-2393-9-24

Published:	19 June 2009

Abstract

Background

Audit and classification of stillbirths is an essential part of clinical practice and a crucial step towards stillbirth prevention. Due to the limitations of the ICD system and lack of an international approach to an acceptable solution, numerous disparate classification systems have emerged. We assessed the performance of six contemporary systems to inform the development of an internationally accepted approach.

Methods

We evaluated the following systems: Amended Aberdeen, Extended Wigglesworth; PSANZ-PDC, ReCoDe, Tulip and CODAC. Nine teams from 7 countries applied the classification systems to cohorts of stillbirths from their regions using 857 stillbirth cases. The main outcome measures were: the ability to retain the important information about the death using the InfoKeep rating; the ease of use according to the Ease rating (both measures used a five-point scale with a score <2 considered unsatisfactory); inter-observer agreement and the proportion of unexplained stillbirths. A randomly selected subset of 100 stillbirths was used to assess inter-observer agreement.

Results

InfoKeep scores were significantly different across the classifications (p ≤ 0.01) due to low scores for Wigglesworth and Aberdeen. CODAC received the highest mean (SD) score of 3.40 (0.73) followed by PSANZ-PDC, ReCoDe and Tulip [2.77 (1.00), 2.36 (1.21), 1.92 (1.24) respectively]. Wigglesworth and Aberdeen resulted in a high proportion of unexplained stillbirths and CODAC and Tulip the lowest. While Ease scores were different (p ≤ 0.01), all systems received satisfactory scores; CODAC received the highest score. Aberdeen and Wigglesworth showed poor agreement with kappas of 0.35 and 0.25 respectively. Tulip performed best with a kappa of 0.74. The remainder had good to fair agreement.

Conclusion

The Extended Wigglesworth and Amended Aberdeen systems cannot be recommended for classification of stillbirths. Overall, CODAC performed best with PSANZ-PDC and ReCoDe performing well. Tulip was shown to have the best agreement and a low proportion of unexplained stillbirths. The virtues of these systems need to be considered in the development of an international solution to classification of stillbirths. Further studies are required on the performance of classification systems in the context of developing countries. Suboptimal agreement highlights the importance of instituting measures to ensure consistency for any classification system.