Background: Pulmonary embolism is the leading cause of death in pregnancy and the puerperium – accounting for nearly 20% of maternal deaths in the United States – making rapid and accurate diagnosis critically important for emergency physicians, OB/GYNs, and all who take care of these women on a regular basis. Diagnosis is made more difficult by the frequency of concerning and suggestive signs and symptoms in this population, particularly dyspnea (a common symptom in pregnancy related to an increase in progesterone levels) and tachycardia (as resting heart rate is typically expected to increase by up to 25% in normal pregnancy).
While the use of the D-dimer in conjunction with a low pre-test probability for pulmonary embolism is well-established for ruling out PE in the non-pregnant population, pregnant women were excluded from studies that derived and validated models assessing pretest clinical probability of PE, and no specific tool to assess pretest probability is available in this setting. This lack of a pretest probability assessment tool and the lack of prospective data confirming the safety of ruling out PE on the basis of a negative D-dimer result have limited the adoption of the D-dimer test in pregnant patients. Indeed, the American Thoracic Society guidelines  recommend specifically against the use of D-dimer to exclude PE in pregnancy. The DiPEP study, published in the British Journal of Haematology, attempted to add to this literature base , and was reviewed here on REBEL EM. The DiPEP authors’ conclusion, that D-dimer should not be recommended for use in the diagnostic work-up of PE in pregnancy, was echoed in our review, however this study was likely fundamentally flawed in that it did not risk stratify patients prior to application of D-dimer testing, a critical step in all validated applications.
Recently, a group of French and Swiss authors published a prospective diagnostic management outcome study for diagnosis of PE in pregnant women that sought to better define the role of D-dimer when paired with pre-test risk stratification.  Read more →