Study information

NethOSS - Netherlands Obstetric Surveillance System

Objective

-     To determine the incidence of three specific forms of maternal morbidity (e.g. Eclampsia; Cardiac arrest and Amniotic Fluid Embolism (AFE)) in a consecutive two-year timeframe in the Netherlands.

-     To compare management strategies in cases of eclampsia compared to a control group of women with severe preeclampsia without eclampsia.

-     To design a prediction model for eclampsia.

Study design
National prospective observational study.

Study population
All women in the Netherlands, pregnant or in puerperium meeting the definitions used for the registered forms of maternal morbidity.

Methods
All hospitals in the Netherlands are asked to participate in this study. During the studied timeframe an affiliated gynaecologist will receive a monthly mail indicating the possible forms of maternal morbidity as registered by this study.

After identification of a case, anonymised photocopies of all relevant case-files will be mailed to the principal investigator, showing only the study-ID obtained after contacting the principal investigator. The Principal investigator will distil the necessary data from the anonymous case-files and enter the parameters in a dedicated ProMISe database from the Leiden University Medical Centre.

A control group will be constructed using the case as a reference. We will identify two controls before and two controls after the case of eclampsia. These controls are subdivided in a group of women who develop severe preeclampsia but no eclampsia and a group representing the general population.

Outcome measures
Primary outcome measures will be the incidence of registered forms of morbidity. Secondary outcome measures are differences in characteristics, putative risk factors, outcome and differences in management strategies between cases of eclampsia and severe preeclampsia. Furthermore a prediction model will be constructed for eclampsia.

Power/data analysis
During a consecutive 2 year period all women meeting the inclusion criteria will be registered in this study. We suspect a total of 100 cases of eclampsia and subsequently a total of 400 controls will be registered. An estimated 7 cases of cardiac arrest and 5 cases of amniotic fluid embolism will be registered.

Economic evaluation
Not applicable

Time schedule
Starting date 01-05-2013, duration 24 months, 12 month data analysis.

Projectleaders
Drs. T.P.Schaap, UMCU, Utrecht

Dr K.W.M. Bloemenkamp, LUMC, Leiden

Prof. Dr J. van Roosmalen. LUMC, Leiden

Prof A Franx, UMCU, Utrecht

Dr J.J. Zwart, Deventer ziekenhuis, Deventer

prof. Dr. J.M.M. van Lith, LUMC, Leiden

Health Technology Assessment
Not applicable

Methodology
An incidence for all registered forms of morbidity will be constructed using data from the Centraal Bureau voor de Statistiek. An international comparison of incidence, characteristics and management will be performed using the International Network Of Obstetric Survey Systems (INOSS).

All interventions in cases of eclampsia and severe pre-eclampsia will be registered in a database. Analysis of time-dependent variables will be performed to compare management strategies between both group.

Using the cases and controls we will perform a logistic regression analysis to predict the primary endpoint (eclampsia) from clinical characteristics. For individual dichotomous and continuous variables, univariate pooled odds ratios and 95% confidence intervals (CI), as well as P-values will be calculated. Using this, it is possible to perform a multivariable logistic regression analysis with a stepwise backward selection of predictors to construct a prediction model. To evaluate the discriminative performance of the logistic model, the area under the receiver –operating characteristics (ROC) curve will be calculated, comparing actual outcomes to the outcome predicted by the model. Subsequently, we can evaluate the calibration of the prediction model by plotting observed and predicted event rates for 10 subgroups of patients on the basis of deciles of the predicted probability.  Furthermore, we can assess the reliability of the model with the Hosmer and Lemeshow test for goodness of fit. Internal validation and extent of over fitting of the model can be assessed by bootstrapping.

Subsidy
none

Contact (researcher)

Drs. Timme Schaap, AIOS gynaecologie & promovendus NethOSS

E:   info@nethoss.nl

T:   06-45194573