Abstract
BackgroundMaternal critical illness occurs in 1.2 to 4.7 of every 1000 live births in the United States and approximately 1 in 100 women who become critically ill will die. Patient characteristics and comorbid conditions are commonly summarized as an index or score for the purpose of predicting the likelihood of dying; however, most such indices have arisen from non-pregnant patient populations. We sought to systematically review comorbidity indices used in health administrative datasets of pregnant women, in order to critically appraise their measurement properties and recommend optimal tools for clinicians and maternal health researchers.MethodsWe conducted a systematic search of MEDLINE and EMBASE to identify studies published from 1946 and 1947, respectively, to May 2017 that describe predictive validity of comorbidity indices using health administrative datasets in the field of maternal health research. We applied a methodological PubMed search filter to identify all studies of measurement properties for each index.ResultsOur initial search retrieved 8944 citations. The full text of 61 articles were identified and assessed for final eligibility. Finally, two eligible articles, describing three comorbidity indices appropriate for health administrative data remained: The Maternal comorbidity index, the Charlson comorbidity index and the Elixhauser Comorbidity Index. These studies of identified indices had a low risk of bias. The lack of an established consensus-building methodology in generating each index resulted in marginal sensibility for all indices. Only the Maternal Comorbidity Index was derived and validated specifically from a cohort of pregnant and postpartum women, using an administrative dataset, and had an associated c-statistic of 0.675 (95% Confidence Interval 0.647–0.666) in predicting mortality.ConclusionsOnly the Maternal Comorbidity Index directly evaluated measurement properties relevant to pregnant women in health administrative datasets; however, it has only modest predictive ability for mortality among development and validation studies. Further research to investigate the feasibility of applying this index in clinical research, and its reliability across a variety of health administrative datasets would be incrementally helpful. Evolution of this and other tools for risk prediction and risk adjustment in pregnant and post-partum patients is an important area for ongoing study.
Highlights
Maternal critical illness occurs in 1.2 to 4.7 of every 1000 live births in the United States and approximately 1 in 100 women who become critically ill will die
59 studies were excluded, for the following reasons: 10 because there was insufficient information provided in the conference abstract and there was no subsequent full-text article, 6 that did not focus on mortality prediction, 13 that did not report upon model performance, 24 that explored physiology based indices initially developed for nonpregnant populations, in Intensive Care Unit (ICU) settings, and which employed vital signs and laboratory results in addition to comorbidities (i.e. APACHE, SAPS, the MPM, Sepsis-related Organ Failure Assessment [23,24,25,26]), and 6 studies that did not focus on comorbidities
The other article was an external validation of the Maternal Comorbidity Index using Canadian health administrative datasets [28]
Summary
Maternal critical illness occurs in 1.2 to 4.7 of every 1000 live births in the United States and approximately 1 in 100 women who become critically ill will die. We sought to systematically review comorbidity indices used in health administrative datasets of pregnant women, in order to critically appraise their measurement properties and recommend optimal tools for clinicians and maternal health researchers. Maternal critical illness occurs in 1.2 to 4.7 of every 1000 live births in the United States and is associated with a fetal loss rate of 30% [2,3,4]. Clinicians, patients and families would benefit from a tool that could predict the risk of maternal mortality from commonly available data, across a range of gestational age in order to assist with decision-making on an appropriate level of monitoring and care. Maternal health research would be assisted by a tool to help risk-adjust in observational studies among patients with different probabilities of death
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