Clinical information does not improve the performance of mathematical models in predicting the outcome of pregnancies of unknown location

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.

Diagnostic accuracy validation study of the M6 model without initial serum progesterone (M6NP) in triage of pregnancy of unknown location

OBJECTIVES

The M6 prediction model stratifies the risk of development of ectopic pregnancy (EP) for women with pregnancy of unknown location (PUL) into low risk or high risk, using human chorionic gonadotrophin (hCG) and progesterone levels at the initial visit to a gynaecological emergency room and hCG level at 48 h. This study evaluated a second model, the M6NP model, which does not include the progesterone level at the initial visit. The main aim of this study was to validate the diagnostic accuracy of the M6NP model in a population of French women.

STUDY DESIGN

Between January and December 2021, all women with an hCG measurement from the gynaecological emergency department of a teaching hospital were screened for inclusion in this study. Women with a pregnancy location determined before or at the second visit were excluded. The diagnostic test was based on logistic regression of the M6NP model, with classification into two groups: high risk of EP (≥5%) and low risk of EP (<5%). The reference test was the final outcome based on clinical, biological and sonographic results: failed PUL (FPUL), intrauterine pregnancy (IUP) or EP. Diagnostic performance for risk prediction of EP, and also IUP and FPUL, was calculated.

RESULTS

In total, 759 women with possible PUL were identified. After screening, 341 women with PUL were included in the main analysis. Of these, 186 (54.5%) were classified as low risk, including three (1.6%) with a final outcome of EP. The remaining 155 women with PUL were classified as high risk, of whom 60 (38.7%), 66 (42.8%) and 29 (18.7%) had a final outcome of FPUL, IUP and EP, respectively. Of the 32 women with PUL with a final outcome of EP, 29 (90.6%) were classified as high risk and three (9.4%) were classified as low risk. Therefore, the performance of the M6NP model to predict EP had a negative predictive value of 98.4%, a positive predictive value of 18.7%, sensitivity of 90.6% and specificity of 59.2%. If the prediction model had been used, it is estimated that 4.5 visits per patient could have been prevented.

CONCLUSION

The M6NP model could be used safely in the French population for risk stratification of PUL. Its use in clinical practice should result in a substantial reduction in the number of visits to a gynaecological emergency room.

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.

Evaluation of a New Model for Human Chorionic Gonadotropin Rise in Pregnancies of Unknown Viability

OBJECTIVE

To evaluate the performance of a new human chorionic gonadotropin (hCG) threshold model to classify pregnancies as viable or nonviable using a longitudinal cohort of individuals with pregnancy of unknown viability. The secondary objective was to compare the new model with three established models.

METHODS

This is a single-center, retrospective cohort study of individuals seen at the University of Missouri from January 1, 2015, until March 1, 2020, who had at least two consecutive quantitative hCG serum levels with an initial level greater than 2 milli-international units/mL and 5,000 milli-international units/mL or less, with the first interval between laboratory draws no greater than 7 days. Prevalence of correct classification of viable intrauterine pregnancies, ectopic pregnancies, and early pregnancy losses was evaluated with a new proposed hCG threshold model and compared with three established models describing minimum expected rates of hCG rise for a viable intrauterine pregnancy.

RESULTS

Of an initial cohort of 1,295 individuals, 688 patients met inclusion criteria. One hundred sixty-seven individuals (24.3%) had a viable intrauterine pregnancy; 463 (67.3%) had an early pregnancy loss; and 58 (8.4%) had an ectopic pregnancy. A new model based on the total additive percent rise of hCG at 4 and 6 days after initial hCG (70% or greater and 200% or greater rise, respectively) was created. The new model was able to correctly identify 100% of viable intrauterine pregnancies while minimizing incorrect classification of early pregnancy losses and ectopic pregnancies as normal pregnancies. At 4 days after initial hCG, 14 ectopic pregnancies (24.1%) and 44 early pregnancy losses (9.5%) were incorrectly classified as potentially normal pregnancies. At 6 days after initial hCG, only seven ectopic pregnancies (12.1%) and 25 early pregnancy losses (5.6%) were incorrectly classified as potentially normal pregnancies. In established models, up to nine intrauterine pregnancies (5.4%) were misclassified as abnormal pregnancies and up to 26 ectopic pregnancies (44.8%) and 58 early pregnancy losses (12.5%) were incorrectly classified as potentially normal pregnancies.

CONCLUSION

The proposed new hCG threshold model optimizes a balance between identifying potentially viable intrauterine pregnancies and minimizing misdiagnosis of ectopic pregnancies and early pregnancy losses. External validation in other cohorts is needed before widespread clinical use.

Predicting Ectopic Pregnancy Using Human Chorionic Gonadotropin (hCG) Levels and Main Cause of Infertility in Women Undergoing Assisted Reproductive Treatment: Retrospective Observational Cohort Study

Background

Ectopic pregnancy (EP) is a serious complication of assisted reproductive technology (ART). However, there is no acknowledged mathematical model for predicting EP in the ART population.

Objective

The goal of the research was to establish a model to tailor treatment for women with a higher risk of EP.

Methods

From December 2015 to July 2016, we retrospectively included 1703 women whose serum human chorionic gonadotropin (hCG) levels were positive on day 21 (hCG21) after fresh embryo transfer. Multivariable multinomial logistic regression was used to predict EP, intrauterine pregnancy (IUP), and biochemical pregnancy (BCP).

Results

The variables included in the final predicting model were (hCG21, ratio of hCG21/hCG14, and main cause of infertility). During evaluation of the model, the areas under the receiver operating curve for IUP, EP, and BCP were 0.978, 0.962, and 0.999, respectively, in the training set, and 0.963, 0.942, and 0.996, respectively, in the validation set. The misclassification rates were 0.038 and 0.045, respectively, in the training and validation sets. Our model classified the whole in vitro fertilization/intracytoplasmic sperm injection–embryo transfer population into four groups: first, the low-risk EP group, with incidence of EP of 0.52% (0.23%-1.03%); second, a predicted BCP group, with incidence of EP of 5.79% (1.21%-15.95%); third, a predicted undetermined group, with incidence of EP of 28.32% (21.10%-35.53%), and fourth, a predicted high-risk EP group, with incidence of EP of 64.11% (47.22%-78.81%).

Conclusions

We have established a model to sort the women undergoing ART into four groups according to their incidence of EP in order to reduce the medical resources spent on women with low-risk EP and provide targeted tailor-made treatment for women with a higher risk of EP.

Methotrexate Administration to Patients With Presumed Ectopic Pregnancy Leads to Methotrexate Exposure of Intrauterine Pregnancies

OBJECTIVE

To report clinical experience with methotrexate (MTX) treatment for suspected but not definite ectopic pregnancy (EP).

METHODS

This was a retrospective cohort study. All patients treated with MTX for presumed EP between 2000 and 2016 were included. Demographic, clinical, sonographic, and outcome data were collected and analyzed.

RESULTS

A total of 820 patients were treated with MTX, 692 (84.4%) of which were lacking definitive features of EP; 155 (22.4%) failed to follow up until complete resolution and were excluded. Retrospective sonographic categorization was applied to 537 patients; of those patients, 393 (73.2%) were categorized as probable EPs, 136 (25.3%) pregnancies of unknown location (PULs), and 8 (1.5%) probable intrauterine pregnancies (IUPs). Sixteen were eventually diagnosed with IUP: 6 from the probable EPs, 9 from the PULs, and 1 from the probable IUP group. Patients with final diagnosis of IUP had higher values of β-human chorionic gonadotropin as well as lower prevalence of adnexal mass (38% versus 74%; P = .003), higher prevalence of intracavitary fluid (44% versus 9%; P = .0004) and thicker endometrium (17.1 ± 11.8 versus 9.7 ± 5.6; P = .04). None of the sonographic parameters were able to distinguish patients with IUP. One patient of the 16 with IUP was diagnosed with a viable pregnancy, and 7 additional patients had a possible viable pregnancy. None of them elected to continue the pregnancy.

CONCLUSIONS

Most patients with suspected EP who are eligible for medical treatment lack definitive sonographic features of EP. Treatment with MTX in such cases should be delayed, as clinically reasonable, to improve the diagnosis and prevent inadvertent administration of MTX to patients with a viable IUP.

Prediction of Tubal Ectopic Pregnancy Using Offline Analysis of 3-Dimensional Transvaginal Ultrasonographic Data Sets: An Interobserver and Diagnostic Accuracy Study

OBJECTIVES

To assess interobserver reproducibility in detecting tubal ectopic pregnancies by reading data sets from 3-dimensional (3D) transvaginal ultrasonography (TVUS) and comparing it with real-time 2-dimensional (2D) TVUS.

METHODS

Images were initially classified as showing pregnancies of unknown location or tubal ectopic pregnancies on real time 2D TVUS by an experienced sonologist, who acquired 5 3D volumes. Data sets were analyzed offline by 5 observers who had to classify each case as ectopic pregnancy or pregnancy of unknown location. The interobserver reproducibility was evaluated by the Fleiss κ statistic. The performance of each observer in predicting ectopic pregnancies was compared to that of the experienced sonologist. Women were followed until they were reclassified as follows: (1) failed pregnancy of unknown location; (2) intrauterine pregnancy; (3) ectopic pregnancy; or (4) persistent pregnancy of unknown location.

RESULTS

Sixty-one women were included. The agreement between reading offline 3D data sets and the first real-time 2D TVUS was very good (80%-82%; κ = 0.89). The overall interobserver agreement among observers reading offline 3D data sets was moderate (κ = 0.52). The diagnostic performance of experienced observers reading offline 3D data sets had accuracy of 78.3% to 85.0%, sensitivity of 66.7% to 81.3%, specificity of 79.5% to 88.4%, positive predictive value of 57.1% to 72.2%, and negative predictive value of 87.5% to 91.3%, compared to the experienced sonologist's real-time 2D TVUS: accuracy of 94.5%, sensitivity of 94.4%, specificity of 94.5%, positive predictive value of 85.0%, and negative predictive value of 98.1%.

CONCLUSIONS

The diagnostic accuracy of 3D TVUS by reading offline data sets for predicting ectopic pregnancies is dependent on experience. Reading only static 3D data sets without clinical information does not match the diagnostic performance of real time 2D TVUS combined with clinical information obtained during the scan.

Differences in Serum Human Chorionic Gonadotropin Rise in Early Pregnancy by Race and Value at Presentation

OBJECTIVE

To assess whether variation in serum human chorionic gonadotropin (hCG) measures, used to assess early gestation viability, are associated with differences in clinical presentation and patient factors.

METHOD

This retrospective cohort study included 285 women with first-trimester pain and bleeding and a pregnancy of unknown location for whom a normal intrauterine pregnancy was ultimately confirmed. Serial samples were collected at three U.S. sites and hCG changes were analyzed for differences by race, ethnicity, and clinical factors. A nonlinear, mixed-effects regression model was used assuming a random subject shift in the time axis.

RESULTS

The hCG rise in symptomatic women with ongoing intrauterine pregnancy differs by patient factors and level at presentation. The 2-day minimum (first percentile) rise in hCG was faster when presenting hCG values were low and slower when presenting hCG value was high. African American women had a faster hCG rise (P<.001) compared with non-African American women. Variation in hCG curves was associated with prior miscarriage (P=.014), presentation of bleeding (P<.001), and pain (P=.002). For initial hCG values of less than 1,500, 1,500-3,000 and greater than 3,000 milli-international units/mL, the predicted 2-day minimal (first percentile) rise was 49%, 40%, and 33%, respectively.

CONCLUSION

The rise of hCG levels in women with viable intrauterine pregnancies and symptoms of potential pregnancy failure varies significantly by initial value. Changes in hCG rise related to race should not affect clinical care. To limit interruption of a potential desired intrauterine pregnancy, a more conservative "cutoff" (slower rise) is needed when hCG values are high.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, https://clinicaltrials.gov, NCT00194168.

Managing pregnancy of unknown location based on initial serum progesterone and serial serum hCG levels: development and validation of a two-step triage protocol

OBJECTIVES

A uniform rationalized management protocol for pregnancies of unknown location (PUL) is lacking. We developed a two-step triage protocol to select PUL at high risk of ectopic pregnancy (EP), based on serum progesterone level at presentation (step 1) and the serum human chorionic gonadotropin (hCG) ratio, defined as the ratio of hCG at 48 h to hCG at presentation (step 2).

METHODS

This was a cohort study of 2753 PUL (301 EP), involving a secondary analysis of prospectively and consecutively collected PUL data from two London-based university teaching hospitals. Using a chronological split we used 1449 PUL for development and 1304 for validation. We aimed to assign PUL as low risk with high confidence (high negative predictive value (NPV)) while classifying most EP as high risk (high sensitivity). The first triage step assigned PUL as low risk using a threshold of serum progesterone at presentation. The remaining PUL were triaged using a novel logistic regression risk model based on hCG ratio and initial serum progesterone (second step), defining low risk as an estimated EP risk of < 5%.

RESULTS

On validation, initial serum progesterone ≤ 2 nmol/L (step 1) classified 16.1% PUL as low risk. Second-step classification with the risk model selected an additional 46.0% of all PUL as low risk. Overall, the two-step protocol classified 62.1% of PUL as low risk, with an NPV of 98.6% and a sensitivity of 92.0%. When the risk model was used in isolation (i.e. without the first step), 60.5% of PUL were classified as low risk with 99.1% NPV and 94.9% sensitivity.

CONCLUSION

PUL can be classified efficiently into being either high or low risk for complications using a two-step protocol involving initial progesterone and hCG levels and the hCG ratio. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

Accuracy of conventional MRI for preoperative diagnosis of intracranial tumors: A retrospective cohort study of 762 cases

BACKGROUND

Conventional magnetic resonance imaging (MRI) is considered a valuable tool for preoperative diagnosis of intracranial tumors. We assessed its accuracy in the diagnosis of intracranial tumors in usual clinical practice.

MATERIALS AND METHODS

MRI reports of 762 patients who had undergone conventional brain MRI prior to surgery were retrospectively reviewed. A 4-grade scoring system was devised to establish diagnostic agreement. Each tumor type was compared with the corresponding pathological diagnoses by dichotomization. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated for the overall patient population as well as for each tumor type.

RESULTS

664 cases (87.1%) were tumor-positive, and 98 cases (12.9%) were tumor-negative. The most common tumor types were meningiomas, gliomas, pituitary adenomas and schwannomas. These four types together comprised 74.5% of all cases reviewed. Sensitivity and PPV for the overall population were 72.0-90.7% and 91.9-95.4%, respectively. Diagnostic accuracy differed among tumor types. Meningiomas, pituitary adenomas, schwannomas and cholesteatomas were more likely to be diagnosed correctly (sensitivities were 82.6-96.9%, 86.1-96.7%, 88.9-98.2% and 91.3-100.0%, respectively); while some other types like solitary fibrous tumors (SFTs) seemed difficult to identify. Gliomas tended to be confused with metastases, meningiomas with SFTs, and pituitary adenomas with craniopharyngiomas.

CONCLUSION

The accuracy of conventional MRI for diagnosing intracranial tumors is generally satisfactory but should not be too heavily relied upon, especially for certain tumor types. In cases of discrepancy, neurosurgeons are encouraged to confer with the reporting neuroradiologists to achieve optimal preoperative diagnoses.

The clinical performance of the M4 decision support model to triage women with a pregnancy of unknown location as at low or high risk of complications

STUDY QUESTION

What are the adverse outcomes associated with using the M4 model in everyday clinical practice for women with pregnancy of unknown location (PUL)?

SUMMARY ANSWER

There were 17/835 (2.0%) adverse events and no serious adverse events associated with the performance of the M4 model in clinical practice.

WHAT IS KNOWN ALREADY

The M4 model has previously been shown to stratify women classified as a PUL as at low or high risk of complications with a good level of test performance. The triage performance of the M4 model is better than single measurements of serum progesterone or the hCG ratio (serum hCG at 48 h/hCG at presentation).

STUDY DESIGN, SIZE, DURATION

A prospective multi-centre cohort study of 1022 women with a PUL carried out between August 2012 and December 2013 across 2 university teaching hospitals and 1 district general hospital.

PARTICIPANTS/MATERIALS, SETTING, METHODS

All women presenting with a PUL to the early pregnancy units of the three hospitals were recruited. The final outcome for PUL was either a failed PUL (FPUL), intrauterine pregnancy (IUP) or ectopic pregnancy (EP) (including persistent PUL (PPUL)), with EP and PPUL considered high-risk PUL. Their hCG results at 0 and 48 h were entered into the M4 model algorithm. If the risk of EP was ≥5%, the PUL was predicted to be high-risk and the participant was asked to re-attend 48 h later for a repeat hCG and transvaginal ultrasound scan by a senior clinician. If the PUL was classified as 'low risk, likely failed PUL', the participant was asked to perform a urinary pregnancy test 2 weeks later. If the PUL was classified as 'low risk, likely intrauterine', the participant was scheduled for a repeat scan in 1 week. Deviations from the management protocol were recorded as either an 'unscheduled visit (participant reason)', 'unscheduled visit (clinician reason)' or 'differences in timing (blood test/ultrasound)'. Adverse events were assessed using definitions outlined in the UK Good Clinical Practice Guidelines' document.

MAIN RESULTS AND THE ROLE OF CHANCE

A total of 835 (82%) women classified as a PUL were managed according to the M4 model (9 met the exclusion criteria, 69 were lost to follow-up, 109 had no hCG result at 48 h). Of these, 443 (53%) had a final outcome of FPUL, 298 (36%) an IUP and 94 (11%) an EP. The M4 model predicted 70% (585/835) PUL as low risk, of which 568 (97%) were confirmed as FPUL or IUP. Of the 17 EP and PPUL misclassified as low risk, 5 had expectant management, 7 medical management with methotrexate and 5 surgical intervention.Nineteen PUL had an unscheduled visit (participant reason), 38 PUL had an unscheduled visit (clinician reason) and 68 PUL had deviations from protocol due to a difference in timing (blood test/ultrasound).Adverse events were reported in 26 PUL and 1 participant had a serious adverse event. A total of 17/26 (65%) adverse events were misclassifications of a high risk PUL as low risk by the M4 model, while 5/26 (19%) adverse events were related to incorrect clinical decisions. Four of the 26 adverse events (15%) were secondary to unscheduled admissions for pain/bleeding. The serious adverse event was due to an incorrect clinical decision.

LIMITATIONS, REASONS FOR CAUTION

A limitation of the study was that 69/1022 (7%) of PUL were lost to follow-up. A 48 h hCG level was missing for 109/1022 (11%) participants.

WIDER IMPLICATIONS OF THE FINDINGS

The low number of adverse events (2.0%) suggests that expectant management of PUL using the M4 prediction model is safe. The model is an effective way of triaging women with a PUL as being at high- and low-risk of complications and rationalizing follow-up. The multi-centre design of the study is more likely to make the performance of the M4 model generalizable in other populations.

STUDY FUNDING/COMPETING INTERESTS

None.

TRIAL REGISTRATION NUMBER

Not applicable.

Ectopic pregnancy prediction in women with a pregnancy of unknown location: data beyond 48 h are necessary

STUDY QUESTION

Are there improvements in the accuracy of prediction of ectopic pregnancy (EP) in women with early symptomatic pregnancy using human chorionic gonadotrophin (hCG) curves when clinicians consider visits beyond the first 48 h after initial presentation?

SUMMARY ANSWER

Two hCG values, measured 48 h (2 days) apart, are often not sufficient to accurately predict the outcome of a woman with a pregnancy of unknown location (PUL), but adding a third visit on Day 4 or 7 significantly improved the prediction for 1 in 15 women.

WHAT IS KNOWN ALREADY

The use of serial hCG values is commonly used to aid in the prediction of the final diagnosis in women with a PUL. Initial outcome predictions based on two hCG values may often be incorrect.

STUDY DESIGN, SIZE, DURATION

This retrospective multicenter cohort study included 646 women with a PUL, recruited over 2 years. Of these women, 146 were ultimately diagnosed with EP.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Women presenting to the emergency room with first trimester pain or bleeding, with a PUL, at least 2 hCG values and a definitive final diagnosis from the University of Pennsylvania, University of Miami and University of Southern California, were recruited from 2007 to 2009.

MAIN RESULTS AND THE ROLE OF CHANCE

Using currently recommended prediction rules, adding a third hCG evaluation on Day 4 after initial presentation significantly improved the accuracy of initial prediction from the first two values (48 h apart, or Day 2) by 9.3% (P = 0.015). Adding a third value on Day 7 improved prediction significantly by 6.7% (P = 0.031), compared with prediction based on first two values. The improvement in prediction by assessing four hCG values (Days 0, 2, 4 and 7) compared with three values (Days 0, 2 and 4) was 1.3% and not statistically significant.

LIMITATIONS, REASONS FOR CAUTION

Missing data imputation likely biased results toward the null; predicted outcomes may not match those made by clinicians; and the study does not predict intrauterine pregnancy and spontaneous miscarriage separately.

WIDER IMPLICATIONS OF THE FINDINGS

This study provides useful information for the prediction of outcomes for women with a symptomatic first trimester pregnancy of unknown location, but may not be generalizable to all pregnant women.

STUDY FUNDING/COMPETING INTEREST(S)

Supported by NIH grant numbers R01-HD036455 to Dr Barnhart and Dr Sammel, K24HD060687 to Dr Barnhart, and 5T32MH065218 to Ms. Zee. The authors have no conflicts of interest to declare.

Is there a need to definitively diagnose the location of a pregnancy of unknown location? The case for "no"

The ability to predict the outcome of a pregnancy of unknown location (PUL) has been extensively studied over the past decade. Between 8%-14% of PULs will develop into ectopic pregnancies (EP), and therefore the need to confirm pregnancy location is not without good reason. Strategies to predict EP in the PUL population have included the use of various maternal serum biomarkers and repeat transvaginal ultrasound (TVS) examinations in order to avoid delaying this diagnosis. These follow-up tests are associated with substantial financial cost to the healthcare system, as well as impacting on maternal anxiety. However, the majority of women with a PUL at follow-up will either have an intra-uterine pregnancy or a spontaneously resolving PUL, and therefore represent low-risk PULs. Most of these low-risk PULs do not need intervention and expectant management has been shown to be safe and not associated with adverse outcomes. Therefore we need consider whether the current strategies to determine pregnancy location are indeed essential for women with a PUL, especially when balancing the additional health care burden with the potential increase in maternal morbidity/mortality associated with delay in diagnosis. This beckons the question, "Do we really need to definitively diagnose pregnancy location in women with a PUL?

Validation of a clinical risk scoring system, based solely on clinical presentation, for the management of pregnancy of unknown location

OBJECTIVE

To assess a scoring system to triage women with a pregnancy of unknown location.

DESIGN

Validation of prediction rule.

SETTING

Multicenter study.

PATIENT(S)

Women with a pregnancy of unknown location.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Scores assigned to factors identified at clinical presentation, total score calculated to assess risk of ectopic pregnancy (EP) in women with a pregnancy of unknown location, and a proposed three-tiered clinical action plan.

RESULT(S)

The cohort of 1,400 women (284 ectopic pregnancies, 759 miscarriages, and 357 intrauterine pregnancies) was more diverse than the original cohort used to develop the decision rule. The recommendations of the action plan were low risk, intermediate risk, and high risk; the recommendation based on the model score was compared with clinical diagnosis. A total of 29.4% intrauterine pregnancies were identified for less frequent follow-up observation, and 18.4% nonviable gestations were identified for more frequent follow-up observation (to rule out an ectopic pregnancy) compared with intermediate risk (i.e., monitor in current standard fashion). For a decision of possible less frequent monitoring, the specificity was 90.8% (89.0-92.6) with negative predictive value of 79.0% (76.7-81.3). For a decision of more intense follow-up observation, the specificity was 95.0% (92.7-97.2). Test characteristics using the scoring system were replicated in the diverse validation cohort.

CONCLUSION(S)

A scoring system based on symptoms at presentation has value to stratify risk and influence the intensity of outpatient surveillance for women with pregnancy of unknown location but does not serve as a diagnostic tool.

Performance of human chorionic gonadotropin curves in women at risk for ectopic pregnancy: exceptions to the rules

OBJECTIVE

To investigate the accuracy of serial hCG to predict outcome of a pregnancy of unknown location in an ethnically and geographically diverse setting.

DESIGN

Multisite cohort study.

SETTING

University hospital.

PATIENT(S)

Women with a pregnancy of unknown location.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Patients were followed until diagnosed with ectopic pregnancy (EP), intrauterine pregnancy (IUP), or miscarriage. To predict outcome, observed hCG level was compared with recommended thresholds to assess deviation from defined normal curves. Predicted outcome was compared with standard of care. Sensitivity, specificity, predictive value, and accuracy were calculated, stratified by diagnosis.

RESULT(S)

The final diagnosis of 1,005 patients included 179 EPs, 259 IUPs, and 567 miscarriages. The optimal balance in sensitivity and specificity used the minimal expected 2-day increase in hCG level of 35%, and the minimal 2-day decrease in hCG level of 36%-47% (depending on the level) achieving 83.2% sensitivity, 70.8% specificity to predict EP. However, 16.8% of EPs and 7.7% of IUPs would be misclassified solely using serial hCG levels. Consideration of a third hCG and early ultrasound decreased IUP misclassification to 2.7%.

CONCLUSION(S)

Solely using serial hCG values can result in misclassification. Clinical judgment should trump prediction rules and continued surveillance with a third hCG may be prudent, especially when initial values are low or when values are near suggested thresholds.

The term "pregnancy of unknown location" is here to stay

The term "pregnancy of unknown location" is an ultrasound classification and not a final diagnosis. The use of this terminology is here to stay and should continue as long as there is an appreciation for what it really means. It is the responsibility of the clinician, who follows up these women with a PUL, to ensure that a final diagnosis is achieved while preserving the well-being of these women.

Pregnancy of unknown location: a consensus statement of nomenclature, definitions, and outcome

OBJECTIVE

To improve the interpretation of future studies in women who are initially diagnosed with a pregnancy of unknown location (PUL), we propose a consensus statement with definitions of population, target disease, and final outcome.

DESIGN

A review of literature and a series of collaborative international meetings were used to develop a consensus for definitions and final outcomes of women initially diagnosed with a PUL.

RESULT(S)

Global differences were noted in populations studied and in the definitions of outcomes. We propose to define initial ultrasound classification of findings into five categories: definite ectopic pregnancy (EP), probable EP, PUL, probable intrauterine pregnancy (IUP), and definite IUP. Patients with a PUL should be followed and final outcomes should be categorized as visualized EP, visualized IUP, spontaneously resolved PUL, and persisting PUL. Those with the transient condition of a persisting PUL should ultimately be classified as nonvisualized EP, treated persistent PUL, resolved persistent PUL, or histologic IUP. These specific categories can be used to characterize the natural history or location (intrauterine vs. extrauterine) of any early gestation where the initial location is unknown.

CONCLUSION(S)

Careful definition of populations and classification of outcomes should optimize objective interpretation of research, allow objective assessment of future reproductive prognosis, and hopefully lead to improved clinical care of women initially identified to have a PUL.

Does a prediction model for pregnancy of unknown location developed in the UK validate on a US population?

BACKGROUND

A logistic regression model (M4) was developed in the UK to predict the outcome for women with a pregnancy of unknown location (PUL) based on the initial two human chorionic gonadotrophin (hCG) values, 48 h apart. The purpose of this paper was to assess the utility of this model to predict the outcome for a woman (PUL) in a US population.

METHODS

Diagnostic variables included log-transformed serum hCG average of two measurements, and linear and quadratic hCG ratios. Outcomes modeled were failing PUL, intrauterine pregnancy (IUP) and ectopic pregnancy (EP). This model was applied to a US cohort of 604 women presenting with symptomatic first-trimester pregnancies, who were followed until a definitive diagnosis was made. The model was applied before and after correcting for differences in terminology and diagnostic criteria.

RESULTS

When retrospectively applied to the adjusted US population, the M4 model demonstrated lower areas under the curve compared with the UK population, 0.898 versus 0.988 for failing PUL/spontaneous miscarriage, 0.915 versus 0.981 for IUP and 0.831 versus 0.904 for EP. Whereas the model had 80% sensitivity for EP using UK data, this decreased to 49% for the US data, with similar specificities. Performance only improved slightly (55% sensitivity) when the US population was adjusted to better match the UK diagnostic criteria.

CONCLUSIONS

A logistic regression model based on two hCG values performed with modest decreases in predictive ability in a US cohort for women at risk for EP compared with the original UK population. However, the sensitivity for EP was too low for the model to be used in clinical practice in its present form. Our data illustrate the difficulties of applying algorithms from one center to another, where the definitions of pathology may differ.

Use of serum progesterone measurements to reduce need for follow-up in women with pregnancies of unknown location

OBJECTIVE

To assess the efficacy of a progesterone-based algorithm for the management of women with pregnancies of unknown location (PULs) and explore the feasibility of developing a single-visit strategy in those with a low risk of requiring medical intervention.

METHODS

All clinically stable women in whom pregnancy could not be identified on ultrasound scan were managed by a pre-defined protocol based on measurement of serum progesterone and beta-human chorionic gonadotropin (beta-hCG). Intervention in the form of surgery or medical treatment with methotrexate was offered to all women with persistent or worsening symptoms and non-declining serum beta-hCG. Decision-tree analysis was used to develop a protocol for the management of women with resolving pregnancies who are at low risk of requiring medical intervention.

RESULTS

1110 women were included in the data analysis: normal intrauterine pregnancy was diagnosed in 248 (22.3%; 95% CI, 19.9-24.8) women. 761 (68.6%; 95% CI, 65.8-71.3) abnormal pregnancies resolved spontaneously on expectant management, while the remaining 101 (9.1%; 95% CI, 7.4-10.8) women with abnormal pregnancies required some form of medical intervention. Intervention rates in patients presenting with initial serum progesterone levels of <or= 20 nmol/L and <or= 10 nmol/L, were 3.9% (95% CI, 2.4-5.4) and 2.1% (95% CI, 0.9-3.3), respectively. In women presenting with progesterone <or= 10 nmol/L and beta-hCG < 450 IU/L, the intervention rate was 1.3% (95% CI, 0.2-2.5).

CONCLUSION

Women with PULs with progesterone <or= 10 nmol/L at presentation are at low risk of requiring medical intervention and may not benefit from attending routine follow-up visits.