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Determining the cause of stillbirth in Kumasi, Ghana
Author(s) -
Angell Jennifer N.,
AbdulMumin AbdulRazak S.,
Gold Katherine J.
Publication year - 2019
Publication title -
international journal of gynecology and obstetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.895
H-Index - 97
eISSN - 1879-3479
pISSN - 0020-7292
DOI - 10.1002/ijgo.12930
Subject(s) - medicine , placental abruption , obstetrics , eclampsia , referral , maternal death , perinatal mortality , antepartum hemorrhage , cause of death , medical record , pediatrics , retrospective cohort study , pregnancy , environmental health , population , fetus , disease , family medicine , surgery , genetics , biology
Abstract 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.