Abstract
IntroductionRisk prediction scores usually overestimate mortality in obstetric populations because mortality rates in this group are considerably lower than in others. Studies examining this effect were generally small and did not distinguish between obstetric and nonobstetric pathologies. We evaluated the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) II model in obstetric admissions to critical care units contributing to the ICNARC Case Mix Programme.MethodsAll obstetric admissions were extracted from the ICNARC Case Mix Programme Database of 219,468 admissions to UK critical care units from 1995 to 2003 inclusive. Cases were divided into direct obstetric pathologies and indirect or coincidental pathologies, and compared with a control cohort of all women aged 16–50 years not included in the obstetric categories. The predictive ability of APACHE II was evaluated in the three groups. A prognostic model was developed for direct obstetric admissions to predict the risk for hospital mortality. A log-linear model was developed to predict the length of stay in the critical care unit.ResultsA total of 1452 direct obstetric admissions were identified, the most common pathologies being haemorrhage and hypertensive disorders of pregnancy. There were 278 admissions identified as indirect or coincidental and 22,938 in the nonpregnant control cohort. Hospital mortality rates were 2.2%, 6.0% and 19.6% for the direct obstetric group, the indirect or coincidental group, and the control cohort, respectively. Cox regression calibration analysis showed a reasonable fit of the APACHE II model for the nonpregnant control cohort (slope = 1.1, intercept = -0.1). However, the APACHE II model vastly overestimated mortality for obstetric admissions (mortality ratio = 0.25). Risk prediction modelling demonstrated that the Glasgow Coma Scale score was the best discriminator between survival and death in obstetric admissions.ConclusionThis study confirms that APACHE II overestimates mortality in obstetric admissions to critical care units. This may be because of the physiological changes in pregnancy or the unique scoring profile of obstetric pathologies such as HELLP syndrome. It may be possible to recalibrate the APACHE II score for obstetric admissions or to devise an alternative score specifically for obstetric admissions.
Highlights
Risk prediction scores usually overestimate mortality in obstetric populations because mortality rates in this group are considerably lower than in others
Cox regression calibration analysis showed a reasonable fit of the Acute Physiology and Chronic Health Evaluation (APACHE) II model for the nonpregnant control cohort
This study confirms that APACHE II overestimates mortality in obstetric admissions to critical care units
Summary
Risk prediction scores usually overestimate mortality in obstetric populations because mortality rates in this group are considerably lower than in others Studies examining this effect were generally small and did not distinguish between obstetric and nonobstetric pathologies. Each admission to a critical care unit in order to standardize data for the purposes of audit and research They have been modified for clinical use as early warning scores in general wards to help junior medical and nursing staff to identify those patients who are at risk for requiring medical attention or admission to an intensive care unit (ICU). Several scores have been evaluated in obstetric patients in general ICUs and found to overestimate [1,2,3,4], underestimate [5] and accurately predict [6,7] mortality These surveys were relatively small and retrospective and may not have identified all suitable cases. Not all distinguished between obstetric and nonobstetric pathologies
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