The clinical outcome of pregnancies of unknown location: an audit of 112 cases

Abstract

Introduction Pregnancy of unknown location (PUL) is a descriptive term applied when a woman presents with a positive pregnancy test but no signs of either intrauterine pregnancy (IUP) or ectopic pregnancy (EP) on ultrasound. This implies a level of diagnostic uncertainty requiring further investigation, with the main concern being an undetected EP. Method We examined the outcome of 112 pregnancies of unknown location (PUL) in a tertiary teaching hospital in New Zealand. Results Of 585 women referred to our service with a clinical suspicion of EP, 112 (19%) were categorised as PULs. The final outcomes in these women were complete miscarriage (52%), IUP (13%), presumed EP (11%), incomplete miscarriage (11%), confirmed EP (10%), and molar pregnancy (2%). A large proportion of women (42%) required a second ultrasound examination, and of those, 36% further required a third examination. The distribution of bHCG at presentation and symptomatology demonstrated considerable overlap in women with different clinical outcomes. Conclusion PUL continues to be a challenging and resource‐intensive clinical scenario. The rate of undiagnosed EP requiring intervention is around 10%, and the probability that a PUL represents a small nonvisualised ongoing IUP is relatively low (15%).

Frequency of outcomes of patients with pregnancy of unknown location at a tertiary care hospital.

“…The international society of ultrasound in obstetrics and Gynecology says that early pregnancy units should work towards keeping a PUL rate a less than 15% 13,14 . The current values recommended for discriminatory zone range from 1000-2400iu/l 15,16 .…”

“…The rationale of this study is that the rate of PUL among women varies between 5 and 42% and is increasing with creation of increasing number of early pregnancy units, 12 and limited local data is available, so I have designed this study to determine the frequency of outcomes of patients with pregnancy of unknown location at our hospital. This would help us in generating local data so that it could prove useful in designing the best treatment modality for the patients 13 .…”