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Diagnostic protocols for the management of pregnancy of unknown location: a systematic review and meta‐analysis
Background There is no international consensus on how to manage women with a pregnancy of unknown location (PUL). Objectives To present a systematic quantitative review summarising the evidence related to management protocols for PUL. Search strategy MEDLINE, COCHRANE and DARE databases were searche...
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Published in: | BJOG : an international journal of obstetrics and gynaecology 2019-01, Vol.126 (2), p.190-198 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Background
There is no international consensus on how to manage women with a pregnancy of unknown location (PUL).
Objectives
To present a systematic quantitative review summarising the evidence related to management protocols for PUL.
Search strategy
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).
Selection criteria
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.
Data collection and analysis
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.
Main results
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.
Conclusions
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.
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Pregnancy of unknown location meta‐analysis: M4 model has best test performance to predict ectopic pregnancy.
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Pregnancy of unknown location meta‐analysis: M4 model has best test performance to predict ectopic pregnancy. |
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ISSN: | 1470-0328 1471-0528 |
DOI: | 10.1111/1471-0528.15442 |