BACKGROUND: Women who suffer an early pregnancy loss require specific clinical care, aftercare, and ongoing support. In the UK, the clinical management of early pregnancy complications, including loss is provided mainly through specialist Early Pregnancy Assessment Units. The COVID-19 pandemic fundamentally changed the way in which maternity and gynaecological care was delivered, as health systems moved to rapidly reconfigure and re-organise services, aiming to reduce the risk and spread of SARS-CoV-2 infection. PUDDLES is an international collaboration investigating the pandemic\'s impact on care for people who suffered a perinatal bereavement. Presented here are initial qualitative findings undertaken with UK-based women who suffered early pregnancy losses during the pandemic, about how they navigated the healthcare system and its restrictions, and how they were supported.
METHODS: In-keeping with a qualitative research design, in-depth semi-structured interviews were undertaken with an opportunity sample of women (N = 32) who suffered any early pregnancy loss during the COVID-19 pandemic. Data were analysed using a template analysis to understand women\'s access to services, care, and networks of support, during the pandemic following their pregnancy loss. The thematic template was based on findings from parents who had suffered a late-miscarriage, stillbirth, or neonatal death in the UK, during the pandemic.
RESULTS: All women had experienced reconfigured maternity and early pregnancy services. Data supported themes of: 1) COVID-19 Restrictions as Impractical & Impersonal; 2) Alone, with Only Staff to Support Them; 3) Reduction in Service Provision Leading to Perceived Devaluation in Care; and 4) Seeking Their Own Support. Results suggest access to early pregnancy loss services was reduced and pandemic-related restrictions were often impractical (i.e., restrictions added to burden of accessing or receiving care). Women often reported being isolated and, concerningly, aspects of early pregnancy loss services were reported as sub-optimal.
CONCLUSIONS: These findings provide important insight for the recovery and rebuilding of health services in the post-pandemic period and help us prepare for providing a higher standard of care in the future and through any other health system shocks. Conclusions made can inform future policy and planning to ensure best possible support for women who experience early pregnancy loss.

Patients followed for a pregnancy of unknown location are generally followed by a team of clinicians through telephone calls, and their contraceptive needs at the time of pregnancy resolution may not be addressed.
This study aimed to assess contraceptive counseling and contraceptive uptake before and after a telephone-based intervention.
This was a retrospective pre-post study assessing pregnancy intendedness in patients with a pregnancy of unknown location and the proportion of patients who received contraceptive counseling and a contraceptive prescription before and after the initiation of a telephone-based intervention. We reviewed medical records 1 year before and 1 year after implementation of our intervention for demographic characteristics, pregnancy intendedness, pregnancy outcome, contraceptive counseling documentation, receipt of contraception, and repeat pregnancy within 6 months. We assessed the effects of an implementation strategy to address family planning needs once pregnancy was resolved by comparing the proportions of patients who were counseled and received contraception before and after our intervention was implemented. We performed logistic regression to identify associations between covariates and the outcomes of contraceptive counseling documentation and receipt of contraception.
Of the 220 patients in the combined cohort, the majority were Black (161/220, 73%) and ultimately had a resolved pregnancy of unknown location (162/220, 74%), and the proportion of pregnancies documented as unintended was 60% (132/220). Before our intervention, 27 of 100 (27%) patients received contraceptive counseling, compared with 94 of 120 (78%) patients after the intervention (odds ratio [OR] 9.77, 95% CI 5.26-18.16). Before the intervention, 17 of 90 (19%) patients who did not desire repeat pregnancy received contraception, compared with 32 of 86 (37%) patients after the intervention (OR 2.54, 95% CI 1.28-5.05). Our postintervention cohort had an increased odds of receiving contraceptive counseling (OR 9.77, 95% CI 5.26-18.16) and of receiving a contraceptive prescription (OR 2.54, 95% CI 1.28-5.05) compared with our preintervention cohort.
We found that over half of patients with a pregnancy of unknown location have an unintended pregnancy, and standardization of care through a telephone-based intervention improves contraceptive counseling and prescribing in patients with a resolved pregnancy of unknown location. This intervention could be used at any institution that follows patients with a pregnancy of unknown location remotely to improve care.

Pregnancy of unknown location (PUL) is a condition in which a pregnancy test, such as elevation of serum or urine β-human chorionic gonadotrophin (hCG) level, is rendered positive; however, intrauterine or extrauterine pregnancy cannot be confirmed by transvaginal sonography (TVS). Diagnostic dilation and curettage (D&C) or laparoscopy may be performed to search for the pregnancy location. We experienced a case of PUL in which D&C was performed and histological examination revealed a tiny complete hydatidiform mole within the uterine contents. A retrospective review of the clinical course of this case, such as the evaluation of serum β-hCG levels and TVS findings, suggested that this medical entity could be explained by a tiny hydatidiform mole. In PUL, during D&C, when abnormal villi are detected, even if the lesion is tiny, a suspicion of a hydatidiform mole should be considered by the pathologists, and immunostaining and/or chromosome testing/molecular genotyping should be subsequently performed. Whether a tiny hydatidiform mole poses a risk of persistent gestational trophoblastic disease requires further study based on the accumulation of cases. D&C for PUL patients may be a useful procedure to determine such diagnoses and pick up cases.

UNASSIGNED: Pregnancy of unknown location (PUL) is a term used when there is a positive pregnancy test but no sonographic evidence for an intrauterine pregnancy (IUP) or ectopic pregnancy (EP). This term is a classification and not a final diagnosis.
OBJECTIVE: This study aimed to evaluate the diagnostic value of the Inexscreen test on the outcome of patients with pregnancies of unknown location.
METHODS: In this prospective study, a total of 251 patients with a diagnosis of pregnancy of unknown location at the gynecologic emergency department of the La Conception Hospital, Marseille, France, between June 2015 and February 2019 were included. The Inexscreen (semiquantitative determination of intact human urinary chorionic gonadotropin) test was performed on patients with a diagnosis of pregnancy of unknown location. They participated in the study after information and consent collection. The main outcome measures (sensitivity, specificity, predictive values, and the Youden index) of Inexscreen were calculated for the diagnosis of abnormal pregnancy (nonprogressive pregnancy) and ectopic pregnancy.
RESULTS: The sensitivity and specificity of Inexscreen for the diagnosis of abnormal pregnancy in patients with pregnancy of unknown location were 56.3% (95% confidence interval, 47.0%-65.1%) and 62.8% (95% confidence interval, 53.1%-71.5%), respectively. The sensitivity and specificity of Inexscreen for the diagnosis of ectopic pregnancy in patients with pregnancy of unknown location were 81.3% (95% confidence interval, 57.0%-93.4%) and 55.6% (95% confidence interval, 48.6%-62.3%), respectively. The positive predictive value and negative predictive value of Inexscreen for ectopic pregnancy were 12.9% (95% confidence interval, 7.7%-20.8%) and 97.4% (95% confidence interval, 92.5%-99.1%), respectively.
CONCLUSIONS: Inexscreen is a rapid, non-operator-dependent, noninvasive, and inexpensive test that allows the selection of patients at high risk of ectopic pregnancy in case of pregnancy of unknown location. This test allows an adapted follow-up according to the technical platform available in a gynecologic emergency service.

UNASSIGNED: Ectopic pregnancy (EP) is well known for its critical maternal outcome. Early detection could make the difference between life and death in pregnancy. Our aim was to make a prompt diagnosis before the rupture occur. Thus, the predictive analytical models using both conventional statistics and machine learning (ML) methods were studied.
UNASSIGNED: A retrospective cohort study was conducted on 407 pregnancies with unknown location (PULs): 306 PULs for internal validation and 101 PULs for external validation, randomized with a nested cross-validation technique. Using a set of 22 study features based on clinical factors, serum marker and ultrasound findings from electronic medical records, analyzing with neural networks (NNs), decision tree (DT), support vector machines (SVMs), and a statistical logistic regression (LR). Diagnostic performances were compared with the area under the curve (ROC-AUC), including sensitivity and specificity for decisional use.
UNASSIGNED: Comparing model performance (internal validation) to predict EP, LR ranked first, with a mean ROC-AUC ± SD of 0.879 ± 0.010. In testing data (external validation), NNs ranked first, followed closely by LR, SVMs, and DT with average ROC-AUC ± SD of 0.898 ± 0.027, 0.896 ± 0.034, 0.882 ± 0.029, and 0.856 ± 0.033, respectively. For clinical aid, we report sensitivity of mean ± SD in LR: 90.20% ± 3.49%; SVM: 89.79% ± 3.66%; DT: 89.22% ± 4.53%; and NNs: 86.92% ± 3.24%, consecutively. However, specificity ± SD was ranked by NNs, followed by SVMs, LR, and DT, which were 82.02 ± 8.34%, 80.37 ± 5.15%, 79.65% ± 6.01%, and 78.97% ± 4.07%, respectively.
UNASSIGNED: Both statistics and the ML model could achieve satisfactory predictions for EP. In model learning, the highest ranked model was LR, showing that EP prediction might possess linear or causal data pattern. However, in new testing data, NNs could overcome statistics. This highlights the potency of ML in solving complicated problems with various patterns, while overcoming generalization error of data.

UNASSIGNED: The purpose of the current study was to evaluate the ability of three protocols to triage women presenting with pregnancy of unknown location (PUL).
UNASSIGNED: Women with pregnancy of unknown location were recruited from Aziz Medical Centre from 1st August, 2018 to 31st July, 2020. The criterion of progesterone, human chorionic gonadotrophin (hCG) ratio, and M4 algorithm were used to predict risk of adverse pregnancy outcomes and classify women. Finally, 3 groups were established including ectopic pregnancy, failed pregnancy of unknown location, and intrauterine pregnancy (IUP). The primary outcome was to assign women to ectopic pregnancy group using these protocols. The secondary outcome was to compare the sensitivity and specificity of the three protocols relative to the final outcome.
UNASSIGNED: Of the 288 women, 66 (22.9%) had ectopic pregnancy, 144 (50.0%) had intrauterine pregnancy, and 78 (27.1%) had failed pregnancy of unknown location. The criterion of progesterone had a sensitivity of 81.8%, specificity of 27%, negative predictive value (NPV) of 83.3%, and positive predictive value (PPV) of 25% for high risk result (ectopic pregnancy). The hCG ratio had sensitivity of 72%, specificity of 73%, NPV of 90%, and PPV of 44% for high risk result (ectopic pregnancy). However, model M4 had sensitivity of 86.4%, specificity of 91.9%, NPV of 95.8%, and PPV of 76% for high risk result.
UNASSIGNED: Based on the findings of the study, it was revealed that prediction model of M4 had the highest sensitivity, specificity, negative predictive value and positive predictive value for high risk result (ectopic pregnancy).

UNASSIGNED: We have assessed the potential predictive ability of the biomarkers activin B and fibronectin (FN1) alone and when added to established markers for triaging patients as being at low or high risk of ectopic pregnancy (EP). We also assessed their use as predictors of viability at 12 weeks gestation.
UNASSIGNED: Exploratory secondary analysis of a prospective study including all women classified as a pregnancy of known location (PUL) based on transvaginal ultrasonography between January and December 2007 at the early pregnancy unit of St Georges\' Hospital (London). We used multinomial logistic regression to assess the diagnostic potential of the biomarkers to triage PUL at high risk of complications (EP or persistent PUL), and standard binary logistic regression to predict first trimester viability at 12 weeks.
UNASSIGNED: For discriminating high-risk (n = 16) from low-risk PUL (n = 93), the area under the receiver operating characteristic curve (AUC) was 0.75 (95% confidence interval 0.60-0.85) for activin B and 0.55 (0.41-0.68) for FN1. Adding activin B to a multinomial logistic regression model incorporating β-hCG ratio and initial progesterone yielded odds ratios of 0.16 (0.05-0.55) for failing vs high-risk PUL and 0.29 (0.07-1.19) for intrauterine vs high-risk PUL and increased the model\'s AUC from 0.84 to 0.89. At a risk threshold of 5% for high-risk PUL, sensitivity increased from 84% to 87% and specificity from 48% to 64%. For discriminating viable (n = 28) from non-viable (n = 81) pregnancies at 12 weeks, both markers had an AUC of 0.54.
UNASSIGNED: Our results suggested that activin B may be a promising marker to improve PUL triage in addition to established markers.

Objective: Ectopic pregnancy (EP) is a serious condition. Delayed diagnosis could lead to life-threatening outcomes. The study aimed to develop a diagnostic predictive model for EP to approach suspected cases with prompt intervention before the rupture occurred. Methods: A retrospective cross-sectional study enrolled 347 pregnant women presenting first-trimester complications (abdominal pain or vaginal bleeding) with diagnosis suspected of pregnancy of unknown location, who were eligible and underwent chart review. The data including clinical risk factors, signs and symptoms, serum human chorionic gonadotropin (hCG), and ultrasound findings were analyzed. The statistical predictive score was developed by performing logistic regression analysis. The testing data of 30 patients were performed to test the validation of predictive scoring. Results: From a total of 22 factors, logistic regression method-derived scoring model was based on five potent factors (history of pelvic inflammatory disease, current use of emergency pills, cervical motion tenderness, serum hCG ≥1,000 mIU/ml, and ultrasound finding of adnexal mass) using a cutoff score ≥3. This predictive index score was able to determine ectopic pregnancy with an accuracy of 77.8% [95% confidence interval (CI) = 73.1-82.1], specificity of 91.0% (95% CI = 62.1-72.0), sensitivity of 67.0% (95% CI = 88.0-94.0), and area under the curve of 0.906 (95% CI = 0.875-0.937). In the validation group, no patient with negative result of this score had an EP. Conclusion: Statistical predictive score was derived with high accuracy and applicable performance for EP diagnosis. This score could be used to support clinical decision making in routine practice for management of EP.

To compare the intrauterine gene expression signatures of women with surgically confirmed ectopic pregnancy (ECT) and those of women with miscarriage to inform the development of a genomic classifier for the reliable delineation of pregnancy location in women with clinically nonviable pregnancies of unknown location (NV-PULs).
Discovery-based prospective cohort study.
Academic medical center.
Women with clinically nonviable early pregnancy to include abnormal intrauterine pregnancy (AIUP), ECT, or NV-PUL.
Endometrial (EM) pipelle sampling of the uterus was conducted at the time of scheduled surgery for clinically nonviable early pregnancy (dilation and curettage, manual vacuum aspiration, or laparoscopy). All pregnancy locations were surgically and/or histologically confirmed as intrauterine or ectopic.
Gene expression profiles as determined by array hybridization, quantitative real-time polymerase chain reaction, and nCounter technology.
Intrauterine samples were obtained by EM pipelle from 27 women undergoing surgery for a clinically nonviable early pregnancy. Comparison of array-based global gene expression signatures from women with histologically confirmed ECT versus AIUP revealed 61 differentially expressed genes from which the 5 most informative were included in the pregnancy location classifier. All 5 genes (C20orf85, LRRC46, RSPH4A, WDR49, and ZBBX) were cilia-associated and showed increased expression in pipelle samples from women with ECT relative to expression in samples from women with AIUP. The 5-gene classifier demonstrated an average area under the receiver operator characteristic curve of 0.97 for the detection of ECT. In an external test set composed of publicly available EM pipelle-based gene expression data from a study with similar ECT and AIUP cohorts (n = 19), the classifier revealed an average area under the receiver operator characteristic curve of 0.84.
Consistently increased expression of cilia-associated genes in the uterine cavity of women with ECT provides a reliable molecular signal for the delineation of pregnancy location in women with clinically assessed NV-PUL. A classifier consisting of the 5 most informative cilia-associated genes demonstrated 91% (42/46) accuracy in predicting the pregnancy location.

OBJECTIVE: To assess the safety and performance of the M4 model for classifying as high risk or low risk for ectopic pregnancy (EP) pregnancies conceived by assisted reproductive technologies (ART) that present with low beta-human chorionic gonadotropin (β-hCG) concentration in early gestation.
METHODS: This was a prospective cohort study of 243 pregnancies conceived by ART with low β-hCG levels (5-50 IU/L) at 4 + 0 to 4 + 2 weeks\' gestation. After subsequent β-hCG testing at 48 h, pregnancies were classified according to the M4 model into the following categories: (i) high risk, probable EP/persistent pregnancy of unknown location (PPUL), when the risk for EP was ≥ 5%; (ii) low risk, probable intrauterine pregnancy (IUP), when the risk of EP was < 5% and the likelihood of IUP was greater than that of a failed pregnancy of unknown location (FPUL); and (iii) low risk, probable FPUL, when the risk of EP was < 5% and the likelihood of a FPUL was greater than that of an IUP. The predictive performance of the M4 model for EP and its ability to discriminate between high- and low-risk pregnancies was assessed using the final pregnancy outcome at 11 to 13 weeks of gestation as reference, which was classified as EP/PPUL, FPUL or IUP.
RESULTS: The sensitivity and specificity of the M4 model in detecting a high-risk pregnancy (EP/PPUL) were 60.0% (95% CI, 43.6-74.4%) and 79.8% (95% CI, 73.8-84.7%), respectively. The area under the receiver-operating-characteristics curve of the M4 model for discriminating between high-risk and low-risk (FPUL/IUI) pregnancies was 0.72 (95% CI, 0.62-0.81). The model had a positive likelihood ratio of 2.97 (95% CI, 2.03-4.36) and a negative likelihood ratio of 0.50 (95% CI, 0.33-0.76). The kappa index was 0.30 (95% CI, 0.16-0.43), indicating a low degree of agreement between the model classification and the final diagnosis. No serious adverse events related directly to the application of the M4 model were observed, although 14 pregnancies classified ultimately as high risk had been categorized initially as low risk by the M4 model. Of these, seven resolved with expectant management, five with methotrexate (MTX) and two required laparoscopic surgery (one after failure of medical treatment with MTX and one after deviation from the follow-up protocol). There were no cases of EP/PPUL with additional complications or need for blood or other blood product transfusion. Of the 243 ART pregnancies with low β-hCG concentration in early gestation, only 47 (19.3%) had an IUP, half (24/47) of which had an early miscarriage, resulting in only 9.5% (23/243) cases having an ongoing pregnancy.
CONCLUSIONS: Application of the M4 model in pregnancies conceived by ART with low β-hCG concentration in early gestation showed limited capacity in classifying them as being at low or high risk for EP, therefore, its use in pregnancies of this type is not recommended. No serious adverse events or complications related to the use of the model were observed. These pregnancies have a low probability of ending in an IUP as well as a high rate of early miscarriage. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.