Reducing the proportion of stillborn babies classified as unexplained in Vietnam by application of the PSANZ clinical practice guideline

Determining the cause of stillbirth in Kumasi, Ghana

OBJECTIVE

To classify cause-of-death (COD) for stillbirths occurring in a major referral hospital in Kumasi, Ghana.

METHODS

In a retrospective review conducted between June 8, 2011, and June 12, 2012, detailed information was collected on all stillbirths delivered at Komfo Anokye Teaching Hospital in Kumasi, Ghana. Patient records were independently reviewed by investigators using the Perinatal Society of Australia and New Zealand's Perinatal Death Classification system to determine COD for each case.

RESULTS

COD was analyzed in 465 stillbirth cases. The leading causes of death were hypoxic interpartum death (105, 22.6%), antepartum hemorrhage (67, 14.4%), hypertension (52, 11.2%), and perinatal infection (32, 6.9%). One hundred and fifty seven (33.8%) stillbirths were classified as unexplained antepartum deaths.

CONCLUSIONS

This evaluation of stillbirth in a busy, tertiary care hospital in Kumasi, Ghana provides crucial insight into the high volume of stillbirth in Ghana as well as its medical causes. The study demonstrated the high rate of stillbirth attributed to hypoxic intrapartum events, placental abruption, pre-eclampsia, and unspecified bacterial infections. Yet, our rate of unexplained stillbirths underscores the need for a stillbirth classification system that thoughtfully integrates the needs and limitations of low-resource settings as unexplained stillbirth rates are a common indicator of the effectiveness of a classification system.

Perinatal mortality classification: an analysis of 112 cases of stillbirth

This was a retrospective cohort analysis of stillbirths that occurred from January 2004 to December 2013 in our institution. We compared Tulip and Wigglesworth classification systems on a cohort of stillbirths and analysed the main differences between these two classifications. In this period, there were 112 stillbirths of a total of 31,758 births (stillbirth rate of 3.5 per 1000 births). There were 99 antepartum deaths and 13 intrapartum deaths. Foetal autopsy was performed in 99 cases and placental histopathological examination in all of the cases. The Wigglesworth found 'unknown' causes in 47 cases and the Tulip classification allocated 33 of these. Fourteen cases remained in the group of 'unknown' causes. Therefore, the Wigglesworth classification of stillbirths results in a higher proportion of unexplained stillbirths. We suggest that the traditional Wigglesworth classification should be substituted by a classification that manages the available information.

Global network for women's and children's health research: a system for low-resource areas to determine probable causes of stillbirth, neonatal, and maternal death

Background

Determining cause of death is needed to develop strategies to reduce maternal death, stillbirth, and newborn death, especially for low-resource settings where 98% of deaths occur. Most existing classification systems are designed for high income settings where extensive testing is available. Verbal autopsy or audits, developed as an alternative, are time-intensive and not generally feasible for population-based evaluation. Furthermore, because most classification is user-dependent, reliability of classification varies over time and across settings. Thus, we sought to develop classification systems for maternal, fetal and newborn mortality based on minimal data to produce reliable cause-of-death estimates for low-resource settings.

Results

In six low-resource countries (India, Pakistan, Guatemala, DRC, Zambia and Kenya), we evaluated data which are collected routinely at antenatal care and delivery and could be obtained with interview, observation, or basic equipment from the mother, lay-health provider or family to inform causes of death. Using these basic data collected in a standard way, we then developed an algorithm to assign cause of death that could be computer-programmed. Causes of death for maternal (trauma, abortion, hemorrhage, infection and hypertensive disease of pregnancy), stillbirth (birth trauma, congenital anomaly, infection, asphyxia, complications of preterm birth) and neonatal death (congenital anomaly, infection, asphyxia, complications of preterm birth) are based on existing cause of death classifications, and compatible with the World Health Organization International Classification of Disease system.

Conclusions

Our system to assign cause of maternal, fetal and neonatal death uses basic data from family or lay-health providers to assign cause of death by an algorithm to eliminate a source of inconsistency and bias. The major strengths are consistency, transparency, and comparability across time or regions with minimal burden on the healthcare system. This system will be an important contribution to determining cause of death in low-resource settings.