Predicting Mortality in Pregnancy-Specific Liver Disease

Summary and Comment |
January 28, 2014

Predicting Mortality in Pregnancy-Specific Liver Disease

  1. Atif Zaman, MD, MPH

A simple model using total bilirubin and the international normalized ratio accurately predicted 1-month mortality in hospitalized patients.

  1. Atif Zaman, MD, MPH

Up to 3% of pregnancies are complicated by abnormal liver test results. In the minority of patients, such abnormalities indicate severe disease — most commonly preeclampsia and HELLP (hemolysis, increased liver enzymes, low platelets). To aid in risk stratification of these patients, investigators identified predictors of mortality in pregnant women admitted to a university teaching hospital in India for liver disease or jaundice between 2000 and 2011.

Using a retrospective design, researchers collected clinical, hematologic, and biochemical data and developed regression models to predict 1-month mortality. Follow-up data were available until death or 3 months after delivery.

Of 130 patients identified with pregnancy-specific liver disease, 32 (24.6%) died during the follow-up period. In univariate analysis, encephalopathy, ascites, total bilirubin, creatinine, platelet count, international normalized ratio (INR), total protein, and alkaline phosphatase were associated with mortality. In multivariate analysis, only total bilirubin (adjusted odds ratio, 1.17; 95% confidence interval, 1.08–1.26) and INR (aOR, 2.09; 95% CI, 1.24–3.52) were independently associated with mortality. Both the model for end-stage liver disease (MELD) score and the 2-variable model of total bilirubin and INR, which are variables in the MELD equation, accurately predicted mortality (C-statistics, 0.83 and 0.86, respectively).


In this large retrospective study, the authors identified a simple predictive model that used only total bilirubin and international normalized ratio to accurately predict 1-month mortality among pregnant women presenting with abnormal liver tests or jaundice. Once these findings are verified in prospective studies, clinicians will have a simple model to identify those patients most likely to have complications.

Editor Disclosures at Time of Publication

  • Disclosures for Atif Zaman, MD, MPH at time of publication Speaker’s bureau Bristol-Myers Squibb; Genentech; Gilead; Kadmon; Merck; Salix; Vertex


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