Prediction of adverse maternal outcomes in pre-eclampsia: development and validation of the fullPIERS model

TLDR: In this paper, the authors developed and validated the fullPIERS model with the aim of identifying the risk of fatal or life-threatening complications in women with pre-eclampsia within 48 h of hospital admission for the disorder.

About: This article is published in The Lancet.The article was published on 2011-01-15 and is currently open access. It has received 404 citations till now.

Figures

Figure 1 Performance of the fullPIERS model developed with data from first 48h after eligibility. Combined adverse maternal outcome predicted within 48h of eligibility using only data collected prior to the outcome (an on-line tool to calculate fullPIERS probabilities is available at www.piers.cfri.ca).

Table 2 Characteristics of women in the PIERS study (median [interquartile range] and number (%))

Figure 2 fullPIERS areas under the receiver-operator curves (AUCs; error bars: 95% confidence intervals) from 2 – 7 days after PIERS study eligibility.

Table 4 Univariable analyses of candidate predictor variables with p<0.1 and collected in >80% of cases

Table 3 Adverse maternal outcomes (definitions available [www.piers.cfri.ca])

Table 1 Variables considered in the PIERS modelling

Frequently asked questions

Q1. What are the contributions mentioned in the paper "Predicting adverse maternal outcomes in pre-eclampsia: the fullpiers (pre-eclampsia integrated estimate of risk) model – development and validation authors" ?

In this paper, the authors developed and validated a pre-eclampsia outcome prediction model, the fullPIERS ( Preeclampia Integrated Estimate of RiSk ) model, which is designed for use in well-resourced settings. 

Q2. What are the main factors that affect the outcomes of pre-eclampsia?

For pre-eclampsia arising remote from term, supportive and temporising measures (“expectant management”) are used to improve perinatal outcomes. 

Q3. Why was a 48 hour time period chosen?

A 48 hour time period was chosen because it would improve perinatal outcomes by giving time for steroid administration remote from term and it would inform decisions about the place of delivery/in utero transfer from level 1 and 2 units. 

Q4. What variables were included in the initial multivariable regression model?

Variables associated with the outcome (p<0.1) were included in the initial multivariable regression model along with variables deemed important, a priori, on clinical grounds. 

Q5. What is the way to predict maternal outcomes after preeclampsia?

Standardising antenatal and postnatal assessment and surveillance of pre-eclampsia with protocols that recognise the systemic inflammatory model of pre-eclampsia (1) has been associated with reduced maternal morbidity (11). 

Q6. What is the role of fullPIERS in the study?

fullPIERS should assist decisions around delivery, especially at gestational ages when expectant management has important perinatal advantages (1). 

Q7. How many women were included in the study?

Only candidate predictor variables available for ≥80% of the women were included in modelling, as, routine use is a prerequisite for day-to-day clinical utility. 

Q8. What was the value of the variables used to predict the outcome?

The ‘worst value’ (e.g., highest sBP or lowest platelet count) measured prior to outcome occurrence or completion of the 48 hour time period, whichever was first, was used. 

Q9. What is the way to predict adverse outcomes of preeclampsia?

being able to predict adverse maternal outcomes within a time frame that would inform and guide clinical care (e.g., 48 hours - 7 days) would optimise both the management of women admitted with preeclampsia and resource utilisation. 

Q10. What did the authors do to ensure that the data was accurate?

The authors undertook abstractor training, checked the data collection methods, monitored data logic, and performed random re-abstraction of charts (randomly in 102 (5%) cases and for all adverse maternal or perinatal outcomes were suspected or confirmed). 

Q11. What is the reason why the HYPITAT trial was not supported?

the authors believe that clinicians faced with a hypertensive woman with proteinuria on dipstick analysis at term will decide to advise delivery rather than accept the delay inherent in a 24 hour collection; a decision supported by both the HYPITAT trial (7), and the inaccuracy of 24 hour urine collections for proteinuria estimation in pregnancy (33). 

Q12. What is the mean platelet volume (fL) of a child?

Mean platelet volume (fL) 1953 (96.5) 1.00 [0.88, 1.13] 0.939 0.51 [0.46, 0.57] MPV x 106/platelet count ratio 1952 (96.5) 45.46 [1.63, 1269] 2.9E-25 0.66 [0.59, 0.72] 

Q13. What were the predictors of adverse outcomes for pre-eclampsia?

The model included the following predictors: gestational age at eligibility, chest pain/dyspnoea, SpO2, platelet count, serum creatinine, and AST. 

Q14. What is the significance of the AUC ROC for fullPIERS?

Restricting the analysis to the tightest possible research definition (primigravid women with proteinuric hypertension) did not meaningfully change the AUC ROC. 

Q15. What is the definition of the fullPIERS model?

The fullPIERS (Pre-eclampsia Integrated Estimate of RiSk) model was developed and validated for women with pre-eclampsia to identify their risk of life-ending, -altering, or -threatening complications within 48h of hospital admission with pre-eclampsia.