Conventional and modern markers of pregnancy of unknown location: Update and narrative review

Pregnancy of unknown location (PUL) is a temporary pathologic or physiologic phenomenon of early pregnancy that requires follow up to determine the final pregnancy outcome. Evidence indicated that PUL patients suffer a remarkably higher rate of adverse pregnancy outcomes, represented by ectopic gestation and early pregnancy loss, than the general population. In the past few decades, discussion about PUL has never stopped, and a variety of markers have been widely investigated for the early and accurate evaluation of PUL, including serum biomarkers, ultrasound imaging features, multivariate analysis, and the diagnosis of ectopic pregnancy based on risk stratification. So far, machine learning (ML) methods represented by M4 and M6 logistic regression have gained a level of recognition and are continually improving. Nevertheless, the heterogeneity of PUL markers, mainly caused by the limited sample size, the differences in population and technical maturity, etc., have hampered the management of PUL. With the advancement of multidisciplinary integration and cutting-edge technologies (e.g. artificial intelligence, prediction model development, and telemedicine), novel markers, and strategies for the management of PUL are expected to be developed. In this review, we summarize both conventional and novel markers (represented by artificial intelligence) for PUL assessment and management, investigate their advancements, limitations and challenges, and propose insights on future research direction and clinical application.

Updating M6 pregnancy of unknown location risk-prediction model including evaluation of clinical factors

OBJECTIVES

Ectopic pregnancy (EP) is a major high-risk outcome following a pregnancy of unknown location (PUL) classification. Biochemical markers are used to triage PUL as high vs low risk to guide appropriate follow-up. The M6 model is currently the best risk-prediction model. We aimed to update the M6 model and evaluate whether performance can be improved by including clinical factors.

METHODS

This prospective cohort study recruited consecutive PUL between January 2015 and January 2017 at eight units (Phase 1), with two centers continuing recruitment between January 2017 and March 2021 (Phase 2). Serum samples were collected routinely and sent for β-human chorionic gonadotropin (β-hCG) and progesterone measurement. Clinical factors recorded were maternal age, pain score, bleeding score and history of EP. Based on transvaginal ultrasonography and/or biochemical confirmation during follow-up, PUL were classified subsequently as failed PUL (FPUL), intrauterine pregnancy (IUP) or EP (including persistent PUL (PPUL)). The M6 models with (M6P ) and without (M6NP ) progesterone were refitted and extended with clinical factors. Model validation was performed using internal-external cross-validation (IECV) (Phase 1) and temporal external validation (EV) (Phase 2). Missing values were handled using multiple imputation.

RESULTS

Overall, 5473 PUL were recruited over both phases. A total of 709 PUL were excluded because maternal age was < 16 years or initial β-hCG was ≤ 25 IU/L, leaving 4764 (87%) PUL for analysis (2894 in Phase 1 and 1870 in Phase 2). For the refitted M6P model, the area under the receiver-operating-characteristics curve (AUC) for EP/PPUL vs IUP/FPUL was 0.89 for IECV and 0.84-0.88 for EV, with respective sensitivities of 94% and 92-93%. For the refitted M6NP model, the AUCs were 0.85 for IECV and 0.82-0.86 for EV, with respective sensitivities of 92% and 93-94%. Calibration performance was good overall, but with heterogeneity between centers. Net Benefit confirmed clinical utility. The change in AUC when M6P was extended to include maternal age, bleeding score and history of EP was between -0.02 and 0.01, depending on center and phase. The corresponding change in AUC when M6NP was extended was between -0.01 and 0.03. At the 5% threshold to define high risk of EP/PPUL, extending M6P altered sensitivity by -0.02 to -0.01, specificity by 0.03 to 0.04 and Net Benefit by -0.005 to 0.006. Extending M6NP altered sensitivity by -0.03 to -0.01, specificity by 0.05 to 0.07 and Net Benefit by -0.005 to 0.006.

CONCLUSIONS

The updated M6 model offers accurate diagnostic performance, with excellent sensitivity for EP. Adding clinical factors to the model improved performance in some centers, especially when progesterone levels were not suitable or unavailable. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Development of a single-visit protocol for the management of pregnancy of unknown location following in vitro fertilization: a retrospective study

STUDY QUESTION

Can women with pregnancy of unknown location (PUL) following in vitro fertilization (IVF) be risk-stratified regarding the subsequent need for medical intervention, based on their demographic characteristics and the results of serum biochemistry at the initial visit?

SUMMARY ANSWER

The ratio of serum hCG to number of days from conception (hCG/C) or the initial serum hCG level at ≥5 weeks' gestation could be used to estimate the risk of women presenting with PUL following IVF and needing medical intervention during their follow-up.

WHAT IS KNOWN ALREADY

In women with uncertain conception dates presenting with PUL, a single serum hCG measurement cannot be used to predict the final pregnancy outcomes, thus, serial levels are mandatory to establish a correct diagnosis. Serum progesterone levels can help to risk-stratify women at their initial visit but are not accurate in those taking progesterone supplementation, such as women pregnant following IVF.

STUDY DESIGN, SIZE, DURATION

This was a retrospective study carried out at two specialist early pregnancy assessment units between May 2008 and January 2021. A total of 224 women met the criteria for inclusion, but 14 women did not complete the follow-up and were excluded from the study.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We selected women who had an IVF pregnancy and presented with PUL at ≥5 weeks' gestation.

MAIN RESULTS AND THE ROLE OF CHANCE

A total of 30/210 (14.0%, 95% CI 9.9-19.8) women initially diagnosed with PUL required surgical intervention. The hCG/C was significantly higher in the group of women requiring an intervention compared to those who did not (P = 0.003), with an odds ratio of 3.65 (95% CI 1.49-8.89, P = 0.004). A hCG/C <4.0 was associated with a 1.9% risk of intervention, which accounted for 25.7% of the study population. A similar result was obtained by substituting hCG/C <4.0 with an initial hCG level <100 IU/l, which was associated with 2.0% risk of intervention, and accounted for 23.8% of the study population (P > 0.05).

LIMITATIONS, REASONS FOR CAUTION

A limitation of our study is that it is retrospective in nature, and as such, we were reliant on existing data.

WIDER IMPLICATIONS OF THE FINDINGS

A previous study in women with PUL after spontaneous conception found that a 2% intervention rate was considered low enough to eliminate the need for close follow-up and serial blood tests. Using the same 2% cut-off, a quarter of women with PUL after IVF could also avoid attending for further visits and investigations.

STUDY FUNDING/COMPETING INTEREST(S)

No external funding was required for this study. No conflicts of interest are required to be declared.

TRIAL REGISTRATION NUMBER

N/A.

Liability, risks, and recommendations for ultrasound use in the diagnosis of obstetrics diseases

This literature review will summarize the liability issues, risks, and ultrasound recommendations for diagnosing obstetrics diseases. One liability issue is related to misdiagnosis or failure to detect abnormalities during an ultrasound examination. Ultrasound images can be subjective interpretations, and errors may occur due to factors such as operator skill, equipment limitations, or fetal positioning. Another liability concern is related to the potential adverse effects of ultrasound exposure on both the mother and fetus. While extensive research has shown that diagnostic ultrasound is generally safe when used appropriately, there are still uncertainties regarding long-term effects. Some studies suggest a possible association between prolonged or excessive exposure to ultrasound waves and adverse outcomes such as low birth weight, developmental delays, or hearing impairment. Additionally, obtaining informed consent from patients is crucial in mitigating liability risks. Patients should be informed about the purpose of the ultrasound examination, its benefits, limitations, potential risks (even if minimal), and any alternative diagnostic options available. This ensures that patients know the procedure and can make informed decisions about their healthcare. Proper documentation helps establish a clear record of the care provided and can serve as evidence in any legal disputes.

Follow-up and outcomes of patients with a pregnancy of unknown location: A comparison of two prediction models

BACKGROUND

The time period while delineating the final diagnosis following presentation with a pregnancy of unknown location (PUL) can be an anxious time, as well as being time and resource intensive. Prediction models have been utilised in order to tailor counselling, frame expectations and plan care.

OBJECTIVES

We aimed to review diagnoses of PUL in our population and assess the value of two prediction models.

STUDY DESIGN

We reviewed all 394 PUL diagnoses over a three year period in a tertiary level maternity hospital. We then retrospectively applied the M1 and M6NP models to assess their accuracy when compared to the final diagnosis.

RESULTS

PUL comprises of 2.9% (394/13401) of attendances in our unit, requiring 752 scans and 1613 separate blood tests. Just under one in ten women (9.9%, n = 39) presenting with a PUL had a viable pregnancy at discharge, however of the remainder, only 18.0% (n = 83) required medical or surgical treatment for a PUL. The M1 model was more successful at predicting an ectopic pregnancy than the M6NP, with the latter over-predicting viable pregnancies (33.4%, n = 77).

CONCLUSIONS

We demonstrate that the management of women with a PUL could be stratified through the application of outcome prediction models, having positive results for framing expectations and potentially reducing this resource-intensive diagnosis.

Pregnancy of unknown location: external validation of the hCG-based M6NP and M4 prediction models in an emergency gynaecology unit

OBJECTIVE

To investigate if M6NP predicting ectopic pregnancy (EP) among women with pregnancy of unknown location (PUL) is valid in an emergency gynaecology setting and comparing it with its predecessor M4.

DESIGN

Retrospective cohort study.

SETTING

University Hospital.

PARTICIPANTS

Women with PUL.

METHODS

All consecutive women with a PUL during a study period of 3 years were screened for inclusion. Risk prediction of an EP was based on two serum human chorionic gonadotropin (hCG) levels taken at least 24 hours and no longer than 72 hours apart.

MAIN OUTCOME MEASURES

The area under the ROC curve (AUC) expressed the ability of a model to distinguish an EP from a non-EP (discrimination). Calibration assessed the agreement between the predicted risk of an EP and the true risk (proportion) of EP. The proportion of EPs and non-EPs classified as high risk assessed the model's sensitivity and false positive rate (FPR). The proportion of non-EPs among women classified as low risk was the model's negative predictive value (NPV). The clinical utility of a model was evaluated with decision curve analysis.

RESULTS

1061 women were included in the study, of which 238 (22%) had a final diagnosis of EP. The AUC for EP was 0.85 for M6NP and 0.81 for M4. M6NP made accurate risk predictions of EP up to predictions of 20% but thereafter risks were underestimated. M4 was poorly calibrated up to risk predictions of 40%. With a 5% threshold for high risk classification the sensitivity for EP was 95% for M6NP, the FPR 50% and NPV 97%. M6NP had higher sensitivity and NPV than M4 but also a higher FPR. M6NP had utility at all thresholds as opposed to M4 that had no utility at thresholds≤5%.

CONCLUSIONS

M6NP had better predictive performance than M4 and is valid in women with PUL attending an emergency gynaecology unit. Our results can encourage implementation of M6NP in related yet untested clinical settings to effectively support clinical decision-making.

External validation of risk prediction model M4 in an Australian population: Rationalising the management of pregnancies of unknown location

BACKGROUND

The prediction model M4 can successfully classify pregnancy of unknown location (PUL) into a low- or high-risk group in developing ectopic pregnancy. M4 was validated in UK centres but in very few other countries outside UK.

AIM

To validate the M4 model's ability to correctly classify PULs in a cohort of Australian women.

MATERIALS AND METHODS

A retrospective analysis of women classified with PUL, attending a Sydney-based teaching hospital between 2006 and 2018. The reference standard was the final characterisation of PUL: failed PUL (FPUL) or intrauterine pregnancy (IUP; low risk) vs ectopic pregnancy (EP) or persistent PUL (PPUL; high risk). Each patient was entered into the M4 model calculator and an estimated risk of FPUL/IUP or EP/PPUL was recorded. Diagnostic accuracy of the M4 model was evaluated.

RESULTS

Of 9077 consecutive women who underwent transvaginal sonography, 713 (7.9%) classified with a PUL. Six hundred and seventy-seven (95.0%) had complete study data and were included. Final outcomes were: 422 (62.3%) FPULs, 150 (22.2%) IUPs, 105 (15.5%) EPs and PPULs. The M4 model classified 455 (67.2%) as low-risk PULs of which 434 (95.4%) were FPULs/IUPs and 21 (4.6%) were EPs or PPULs. EPs/PPULs were correctly classified with sensitivity of 80.0% (95% CI 71.1-86.5%), specificity of 75.9% (95% CI 72.2-79.3%), positive predictive value of 37.8% (95% CI 33.8-42.1%) and negative predictive value of 95.3% (95% CI 93.1-96.9%).

CONCLUSIONS

We have externally validated the prediction model M4. It classified 67.2% of PULs as low risk, of which 95.4% were later characterised as FPULs or IUPs while still classifying 80.0% of EPs as high risk.