Diagnosis and Management of Pregnancies of Unknown Location (PULs)
Pregnancies of unknown location (PULs) are defined as a situation in which there is a positive pregnancy test with no signs of either an intra- or extra-uterine pregnancy on transvaginal ultrasonography. Expectant management has been prospectively validated in many studies. A 'wait-and-see' approach has been shown to be safe, reduce the need for unnecessary surgical intervention and is not associated with any serious adverse outcomes. The prevalence of PULs is dependent on the quality of scanning for a given early pregnancy unit. The higher the quality of scanning, the better the detection of ectopic pregnancy using ultrasound as a single diagnostic test, which in turn results in fewer women being classified with a PUL. Varying the discriminatory zone does not significantly improve the detection of ectopic pregnancies in a PUL population. A single serum human chorionic gonadotrophin (hCG), when used in a specialised transvaginal scanning unit, is not only potentially falsely reassuring but unhelpful in excluding the presence of an ectopic pregnancy. A single-visit approach has also been shown to be ineffective.
The vast majority of women with a PUL are at low-risk for ectopic pregnancy. When the location of a pregnancy cannot be confirmed on the basis of an ultrasound scan, serum hCG and progesterone are measured at presentation and also at 48 h. It is the change in serum hCG over time, the hCG ratio (hCG at 48 h/hCG at 0 h), and the absolute level of progesterone at presentation which can be used to reliably predict the failing PULs and intra-uterine pregnancies within a PUL population, but not the ectopic pregnancies.
This justifies the recent development and use of new mathematical modeling techniques to predict ectopic pregnancies in the PUL population. Prospective studies are needed to assess the reproducibility of these models in different centres on different populations. Hopefully the use of such models in the future will enable the clinician to correctly classify PULs earlier, in turn reducing the number of follow up visits.