WHO systematic review of maternal morbidity and mortality: the prevalence of severe acute maternal morbidity (near miss) - Pattinson Robert C; Gülmezoglu A Metin; Say Lale (BMC, 2004)
Abstract Aim To determine the prevalence of severe acute maternal morbidity (SAMM) worldwide (near miss). Method Systematic review of all available data. The methodology followed a pre-defined protocol, an extensive search strategy of 10 electronic databases as well as other sources. Articles were evaluated according to specified inclusion criteria. Data were extracted using data extraction instrument which collects additional information on the quality of reporting including definitions and identification of cases. Data were entered into a specially constructed database and tabulated using SAS statistical management and analysis software. Results A total of 30 studies are included in the systematic review. Designs are mainly cross-sectional and 24 were conducted in hospital settings, mostly teaching hospitals. Fourteen studies report on a defined SAMM condition while the remainder use a response to an event such as admission to intensive care unit as a proxy for SAMM. Criteria for identification of cases vary widely across studies. Prevalences vary between 0.80% - 8.23% in studies that use disease-specific criteria while the range is 0.38% - 1.09% in the group that use organ-system based criteria and included unselected group of women. Rates are within the range of 0.01% and 2.99% in studies using management-based criteria. It is not possible to pool data together to provide summary estimates or comparisons between different settings due to variations in case-identification criteria. Nevertheless, there seems to be an inverse trend in prevalence with development status of a country. Conclusion There is a clear need to set uniform criteria to classify patients as SAMM. This standardisation could be made for similar settings separately. An organ-system dysfunction/failure approach is the most epidemiologically sound as it is least open to bias, and thus could permit developing summary estimates.