Short summary

It is of importance in epidemiologic and health service research that comorbidities are identified and accounted for in analyses investigating associations to avoid confounding bias. The aim of this study is to validate a comorbidity index for use in obstetric patient in an unselected national cohort.

This study is a register-based study including all mothers in Denmark giving from 2000 to 2014. By use of the unique personal identification number assigned to all Danish citizens, data on comorbidities will identified in the National health registers using an algorithm described by Bateman et al. (2013). Outcomes are end organ injury as defined by Bateman et al (2013) or death from delivery admission through 30 days postpartum. 

---

Rationale

Although maternal mortality related to pregnancy and the postpartum period are extremely rare in Denmark, we should do everything possible to prevent such events as every one mother in danger of dying during labor or from pregnancy-related comorbidities is one to many. Further, severe maternal morbidity may affect both the health of the fetus/newborn and the mother, and identification and prediction of maternal comorbidity is important in order to take the appropriate actions. Looking at a broader perspective, maternal mortality is still alarmingly high in developing countries and even in high-income countries as the US, maternal deaths have not decreased the last 30 years and severe morbidity in relation to childbirth have even increased.

In order to determine predictors of severe maternal morbidity and mortality and summarize the burden of comorbidity into a single numerical score in obstetric patient, Bateman et al. have developed a maternal comorbidity index to predict severe maternal morbidity and mortality as well as for use as an adjustment variable when studying causal associations. The index has until now only been validated within selected cohorts, and validation of the index in an unselected population is of high importance to determine external validity. A well-validated comorbidity index for use in obstetric patients may serve for two purposes: (1) Clinically, to identify women of high obstetric risk in order to refer to the proper obstetric services, and (2) as a tool to control for confounding in health service research to determine causal interference.

Aim:

The Danish health registers with complete data on all obstetric patients due to free access to health services are unique sources for assessment of the validity of the Comorbidity Index for Use in Obstetric Patients by Bateman et al. in a complete and unselected study population. Hence, we propose to validate the Comorbidity Index in a Danish setting both by the algorithm described by Bateman et al. and by including further information from Danish registers. We hypothesize that the Comorbidity Index for Use in Obstetric Patients is applicable to predict severe maternal morbidity and mortality in this unselected study population and is able to discriminate between low and high risk obstetric patient in prediction of maternal end-organ damage and death. Further, we expect that the index can be qualified additionally by data from the Danish registers.

---

Description of the cohort

All women giving birth during the period January 2000 - December 2014. The study unit will be each pregnancy (hence each women can be included more than once) anticipating approximately 900,000 pregnancies in the final cohort.

Data and biological material

All pregnancies identified in the Danish Birth Registry will be linked with the Danish National Patient Register, the Danish Register of Causes of Death and the Danish Civil Registration System. We will also include data from the Danish National Prescription Registry and the Danish Psychiatric Central Research Register for further validation. Virtually all medical care in Denmark is reported to the public health authorities, whereby these data resources allow true population-based studies, covering all inhabitants of Denmark. 

Collaborating researchers and departments

OPEN Odense Patient data Explorative Network, Odense University Hospital & Department of Clinical Research, University of Southern Denmark

• Postdoc Mette Bliddal, PhD
• Statistician Sören Möller, PhD

Gynaecology and Obstetrics, Odense University Hospital & Department of Clinical Research, University of Southern Denmark

• Postdoc Christina Vinter, MD, PhD

Clinical Pharmacology and Pharmacy, University of Southern Denmark

• Associated professor Anton Pottegaard, PhD