{Reference Type}: Journal Article
{Title}: Diagnostic protocols for the management of pregnancy of unknown location: a systematic review and meta-analysis.
{Author}: Bobdiwala S;Saso S;Verbakel JY;Al-Memar M;Van Calster B;Timmerman D;Bourne T;
{Journal}: BJOG
{Volume}: 126
{Issue}: 2
{Year}: Jan 2019
{Factor}: 7.331
{DOI}: 10.1111/1471-0528.15442
{Abstract}: <B>BACKGROUND: </B>There is no international consensus on how to manage women with a pregnancy of unknown location (PUL).<BR><B>OBJECTIVE: </B>To present a systematic quantitative review summarising the evidence related to management protocols for PUL.<BR><B>METHODS: </B>MEDLINE, COCHRANE and DARE databases were searched from 1 January 1984 to 31 January 2017. The primary outcome was accurate risk prediction of women initially diagnosed with a PUL having an ectopic pregnancy (high risk) as opposed to either a failed PUL or intrauterine pregnancy (low risk).<BR><B>METHODS: </B>All studies written in the English language, which were not case reports or series that assessed women classified as having a PUL at initial ultrasound.<BR><B>METHODS: </B>Forty-three studies were included. QUADAS-2 criteria were used to assess the risk of bias. We used a novel, linear mixed-effects model and constructed summary receiver operating characteristic curves for the thresholds of interest.<BR><B>RESULTS: </B>There was a high risk of differential verification bias in most studies. Meta-analyses of accuracy were performed on (i) single human chorionic gonadotrophin (hCG) cut-off levels, (ii) hCG ratio (hCG at 48 hours/initial hCG), (iii) single progesterone cut-off levels and (iv) the 'M4 model' (a logistic regression model based on the initial hCG and hCG ratio). For predicting an ectopic pregnancy, the areas under the curves (95% CI) for these four management protocols were as follows: (i) 0.42 (0.00-0.99), (ii) 0.69 (0.57-0.78), (iii) 0.69 (0.54-0.81) and (iv) 0.87 (0.83-0.91), respectively.<BR><B>CONCLUSIONS: </B>The M4 model was the best available method for predicting a final outcome of ectopic pregnancy. Developing and validating risk prediction models may optimise the management of PUL.<BR><B>CONCLUSIONS: </B>Pregnancy of unknown location meta-analysis: M4 model has best test performance to predict ectopic pregnancy.