Rationalizing the follow-up of pregnancies of unknown location.

BACKGROUND: To develop a strategy to rationalize the follow-up of pregnancies of unknown location (PULs) based on the predicted outcome using a mathematical model.

METHODS: Prospective interventional study. Women classified with a PUL had serum hCG levels taken at 0 and 48 h. A logistic regression model was used to predict PUL outcome at 48 h. Women were managed according to the model's prediction. If the model predicted an intrauterine pregnancy (IUP) or ectopic pregnancy (EP), women underwent a repeat scan on day 7; if the model predicted a failing PUL and the hCG ratio was also <0.87, these women were discharged; if the model predicted a failing PUL and the hCG ratio was > or =0.87, serum hCG was repeated on day 7.

RESULTS: Three hundred and sixty-three PULs were included; the final clinical outcomes were 22 (63.1%) failing PULs, 111 (30.6%) IUPs and 23 (6.3%) EPs. 88.7% (322/363) had the location of their pregnancy confirmed in the time period according to the study protocol, i.e. day 2 for failing PULs, day 7 for IUPs and EPs. By day 7, 97.5% (354/363) had been given a diagnosis and could be eliminated from any further follow-up. Only one woman (0.3%) underwent surgical intervention for the diagnosis of her pregnancy location-a diagnostic laparoscopy and surgical evacuation.

CONCLUSION: The logistic regression model developed could be used as a basis on which to rationalize the management of PULs as it can successfully minimize their follow-up by reducing the number of visits, scans and blood tests, as well as intervention rates.