Role of ultrasound in the evaluation of first-trimester pregnancies in the acute setting

Consensus Statements for Assessment and Management of Threatened Miscarriage in the First Trimester in Pakistan: A Three-Step Modified Delphi Approach

BACKGROUND AND OBJECTIVE

It aimed to develop an expert consensus regarding the risk assessment, diagnosis, and threatened miscarriage management during the first trimester in Pakistan.

METHODS

A three-step modified Delphi method was applied to develop the consensus. Eleven specialized obstetricians and gynecologists participated in its development. If 75% or higher agreement level was attained on each assertion, it was declared as a consensus.

RESULTS

Age of 35 or above, previous history of two or more previous miscarriages, and direct strong trauma were considered to be threatened miscarriage risk factors. Infection was discussed and specified to include specific infectious diseases, like malaria, and COVID-19 as a risk factor. The experts agreed from the first time on considering endocrinological disorders, thrombophilia, and lifestyle variables as threatened miscarriage risk factors. They proposed adding a statement concerning acquired thrombophilia which was accepted unanimously. Finally, experts agreed on the importance of educating pregnant women about factors whose risk can be modified by modifying their behavior. As for diagnosis statements, it was agreed to be trifold: physical examination, imaging, and laboratory testing. Physical examination included abdominal and pelvic exams but focused more on vaginal examination with speculum to identify bleeding severity and etiology. The statements regarding the imaging approaches to diagnose threatened miscarriage in the first trimester achieved a consensus in most statements. TVS was recommended to check on uterine structural abnormalities, fetus viability focusing on heartbeat and crown-to-rump length, gestation sac size and emptiness, subchorionic hematoma, and ectopic pregnancy. Each was defined on how to identify and diagnose in separate statements. Statements about laboratory tests indicated the need for human chorionic gonadotropin hormone assessment whether serial or once is dependent on the ultrasound. Recommended hematologic investigations include complete blood count for anemia, Rh factor for potential bleeding risk and in special cases, thrombophilia assessment is undertaken. The first and foremost management aspect was follow-up while most management statements were controversial, and some were altogether removed with only some reaching agreement after discussion.

CONCLUSION

These consensus statements aggregated the best available evidence and experts' opinion-supported statements to improve patient education, risk assessment, diagnosis, and evaluation as well as management of threatened miscarriage during the first trimester in Pakistan.

Comparison of luteal support protocols in fresh IVF/ICSI cycles: a network meta-analysis

Despite the proven superiority of various luteal phase support protocols (LPS) over placebo in view of improved pregnancy rates in fresh cycles of IVF (in vitro fertilization) and ICSI (intracytoplasmic sperm injection) cycles, there is ongoing controversy over specific LPS protocol selection, dosage, and duration. The aim of the present study was to identify the optimal LPS under six core aspects of ART success, clinical pregnancy, live birth as primary outcomes and biochemical pregnancy, miscarriage, multiple pregnancy, ovarian hyperstimulation syndrome (OHSS) events as secondary outcomes. Twelve databases, namely Embase (OVID), MEDLINE (R) (OVID), GlobalHealth (Archive), GlobalHealth, Health and Psychosocial Instruments, Maternity & Infant Care Database (MIDIRS), APA PsycTests, ClinicalTrials.gov, HMIC Health Management Information Consortium, CENTRAL, Web of Science, Scopus and two prospective registers, MedRxiv, Research Square were searched from inception to Aug.1st, 2023, (PROSPERO Registration: CRD42022358986). Only Randomised Controlled Trials (RCTs) were included. Bayesian network meta-analysis (NMA) model was employed for outcome analysis, presenting fixed effects, odds ratios (ORs) with 95% credibility intervals (CrIs). Vaginal Progesterone (VP) was considered the reference LPS given its' clinical relevance. Seventy-six RCTs, comparing 22 interventions, and including 26,536 participants were included in the present NMA. Overall CiNeMa risk of bias was deemed moderate, and network inconsistency per outcome was deemed low (Multiple pregnancy χ2: 0.11, OHSS χ2: 0.26), moderate (Clinical Pregnancy: χ2: 7.02, Live birth χ2: 10.95, Biochemical pregnancy: χ2: 6.60, Miscarriage: χ2: 11.305). Combinatorial regimens, with subcutaneous GnRH-a (SCGnRH-a) on a vaginal progesterone base and oral oestrogen (OE) appeared to overall improve clinical pregnancy events; VP + OE + SCGnRH-a [OR 1.57 (95% CrI 1.11 to 2.22)], VP + SCGnRH-a [OR 1.28 (95% CrI 1.05 to 1.55)] as well as live pregnancy events, VP + OE + SCGnRH-a [OR 8.81 (95% CrI 2.35 to 39.1)], VP + SCGnRH-a [OR 1.76 (95% CrI 1.45 to 2.15)]. Equally, the progesterone free LPS, intramuscular human chorionic gonadotrophin, [OR 9.67 (95% CrI 2.34, 73.2)] was also found to increase live birth events, however was also associated with an increased probability of ovarian hyperstimulation, [OR 1.64 (95% CrI 0.75, 3.71)]. The combination of intramuscular and vaginal progesterone was associated with higher multiple pregnancy events, [OR 7.09 (95% CrI 2.49, 31.)]. Of all LPS protocols, VP + SC GnRH-a was found to significantly reduce miscarriage events, OR 0.54 (95% CrI 0.37 to 0.80). Subgroup analysis according to ovarian stimulation (OS) protocol revealed that the optimal LPS across both long and short OS, taking into account increase in live birth and reduction in miscarriage as well as OHSS events, was VP + SCGnRH-a, with an OR 2.89 [95% CrI 1.08, 2.96] and OR 2.84 [95% CrI 1.35, 6.26] respectively. Overall, NMA data suggest that combinatorial treatments, with the addition of SCGnRH-a on a VP base result in improved clinical pregnancy and live birth events in both GnRH-agonist and antagonist ovarian stimulation protocols.

Diagnostic utility of clinicodemographic, biochemical and metabolite variables to identify viable pregnancies in a symptomatic cohort during early gestation

A significant number of pregnancies are lost in the first trimester and 1-2% are ectopic pregnancies (EPs). Early pregnancy loss in general can cause significant morbidity with bleeding or infection, while EPs are the leading cause of maternal mortality in the first trimester. Symptoms of pregnancy loss and EP are very similar (including pain and bleeding); however, these symptoms are also common in live normally sited pregnancies (LNSP). To date, no biomarkers have been identified to differentiate LNSP from pregnancies that will not progress beyond early gestation (non-viable or EPs), defined together as combined adverse outcomes (CAO). In this study, we present a novel machine learning pipeline to create prediction models that identify a composite biomarker to differentiate LNSP from CAO in symptomatic women. This prospective cohort study included 370 participants. A single blood sample was prospectively collected from participants on first emergency presentation prior to final clinical diagnosis of pregnancy outcome: LNSP, miscarriage, pregnancy of unknown location (PUL) or tubal EP (tEP). Miscarriage, PUL and tEP were grouped together into a CAO group. Human chorionic gonadotrophin β (β-hCG) and progesterone concentrations were measured in plasma. Serum samples were subjected to untargeted metabolomic profiling. The cohort was randomly split into train and validation data sets, with the train data set subjected to variable selection. Nine metabolite signals were identified as key discriminators of LNSP versus CAO. Random forest models were constructed using stable metabolite signals alone, or in combination with plasma hormone concentrations and demographic data. When comparing LNSP with CAO, a model with stable metabolite signals only demonstrated a modest predictive accuracy (0.68), which was comparable to a model of β-hCG and progesterone (0.71). The best model for LNSP prediction comprised stable metabolite signals and hormone concentrations (accuracy = 0.79). In conclusion, serum metabolite levels and biochemical markers from a single blood sample possess modest predictive utility in differentiating LNSP from CAO pregnancies upon first presentation, which is improved by variable selection and combination using machine learning. A diagnostic test to confirm LNSP and thus exclude pregnancies affecting maternal morbidity and potentially life-threatening outcomes would be invaluable in emergency situations.

Combining deep learning and intelligent biometry to extract ultrasound standard planes and assess early gestational weeks

OBJECTIVES

To develop and validate a fully automated AI system to extract standard planes, assess early gestational weeks, and compare the performance of the developed system to sonographers.

METHODS

In this three-center retrospective study, 214 consecutive pregnant women that underwent transvaginal ultrasounds between January and December 2018 were selected. Their ultrasound videos were automatically split into 38,941 frames using a particular program. First, an optimal deep-learning classifier was selected to extract the standard planes with key anatomical structures from the ultrasound frames. Second, an optimal segmentation model was selected to outline gestational sacs. Third, novel biometry was used to measure, select the largest gestational sac in the same video, and assess gestational weeks automatically. Finally, an independent test set was used to compare the performance of the system with that of sonographers. The outcomes were analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and mean similarity between two samples (mDice).

RESULTS

The standard planes were extracted with an AUC of 0.975, a sensitivity of 0.961, and a specificity of 0.979. The gestational sacs' contours were segmented with a mDice of 0.974 (error less than 2 pixels). The comparison showed that the relative error of the tool in assessing gestational weeks was 12.44% and 6.92% lower and faster (min, 0.17 vs. 16.6 and 12.63) than that of the intermediate and senior sonographers, respectively.

CONCLUSIONS

This proposed end-to-end tool allows automatic assessment of gestational weeks in early pregnancy and may reduce manual analysis time and measurement errors.

CLINICAL RELEVANCE STATEMENT

The fully automated tool achieved high accuracy showing its potential to optimize the increasingly scarce resources of sonographers. Explainable predictions can assist in their confidence in assessing gestational weeks and provide a reliable basis for managing early pregnancy cases.

KEY POINTS

• The end-to-end pipeline enabled automatic identification of the standard plane containing the gestational sac in an ultrasound video, as well as segmentation of the sac contour, automatic multi-angle measurements, and the selection of the sac with the largest mean internal diameter to calculate the early gestational week. • This fully automated tool combining deep learning and intelligent biometry may assist the sonographer in assessing the early gestational week, increasing accuracy and reducing the analyzing time, thereby reducing observer dependence.

Female infertility in the era of obesity: The clash of two pandemics or inevitable consequence?

Obesity is an epidemic that has led to a rise in the incidence of many comorbidities: among others, reduced fertility is often under-evaluated in clinical practice. The mechanisms underlying the link between reduced fertility and obesity are numerous, with insulin resistance, hyperglycaemia and the frequent coexistence of polycystic ovary syndrome being the most acknowledged. However, several other factors concur, such as gut microbiome alterations, low-grade chronic inflammation and oxidative stress. Not only do women with obesity take longer to conceive, but in vitro fertilization (IVF) is also less likely to succeed. We herein provide an updated state-of-the-art regarding the molecular bases of what we could define as dysmetabolic infertility, focusing on the clinical aspects, as well as possible treatment.

Evaluation of antenatal point-of-care ultrasound training workshops for rural/remote healthcare clinicians: a prospective single cohort study

BACKGROUND

There is limited access to life-saving antenatal ultrasound in low-resource rural and remote settings worldwide, including Australia, mainly due to shortages in skilled staff. Point-of-care ultrasound (PoCUS) offers a viable solution to this service deficit, however, rural clinicians face many barriers accessing training and professional development critical to advancing their clinical practice. Standards for PoCUS training and competency assessment are unclear. Regulation is lacking globally, allowing untrained and inexperienced clinicians to practice PoCUS clinically.

METHODS

This prospective single cohort study aimed to evaluate antenatal PoCUS training workshops for General Practitioners (GPs) and Midwives/Nurses (M/Ns) from rural/remote Australia, assessing the impact of the training on trainees' knowledge, confidence and translation of PoCUS into clinical practice. Two-day antenatal ultrasound workshops were delivered at the University of South Australia (UniSA) in 2018 and 2019 to 41 rural/remote clinicians . The training was designed and evaluated using the New world Kirkpatrick Evaluation Framework. Sixteen GPs and 25 M/Ns with mixed prior ultrasound experience were funded to attend. The course consisted of lectures interspaced with hands-on training sessions using high-fidelity simulators and live pregnant models. Pre- and post-knowledge assessments were performed. Post-workshop evaluation and follow-up surveys (3- and 6-month post-training) assessed the workshops and changes to trainees' clinical practice. A 2-day follow-up training session was conducted 12 months after the workshops for 9 trainees.

RESULTS

Pre/post knowledge testing demonstrated a 22% mean score improvement (95% CI 17.1 to 27.8, P < 0.0001). At 6 months, 62% of trainees were performing PoCUS that had assisted in patient management and clinical diagnosis, and 46% reported earlier diagnosis and changes to patient management. 74% of trainees had increased scanning frequency and 93% reported improved scanning confidence.

CONCLUSION

This study demonstrated intensive 2-day workshops can equip clinicians with valuable antenatal PoCUS skills, offering a viable solution to assist in the assessment and management of pregnant women in the rural/resource-poor setting where access to ultrasound services is limited or non-existent. Geographical isolation and lack of onsite specialist supervision poses an ongoing challenge to the continuing professional development of remote trainees and the implementation of PoCUS.

Evaluation of antenatal Point-of-Care Ultrasound (PoCUS) training: a systematic review

INTRODUCTION

There is limited access to life-saving antenatal ultrasound in rural and low-resource settings largely due to shortages in skilled staff. Studies have shown healthcare practitioners can be upskilled in PoCUS through focused training, offering a viable solution to this deficit. However, standards for training and competency assessment are unclear and regulation surrounding practice is lacking. We aimed to review published literature examining antenatal PoCUS training programs, comparing teaching approaches and study methodologies.

METHODS

A search of electronic databases EMBASE, MEDLINE and Google Scholar was conducted. Original research articles evaluating antenatal PoCUS training of healthcare professionals worldwide were identified for analysis. Articles with limited detail on the PoCUS training intervention and those describing comprehensive diagnostic training programs were excluded. Evaluations were compared against the Kirkpatrick Evaluation Framework (KEF).

RESULTS

Twenty-seven studies were included from an initial search result of 484 articles. There was considerable heterogeneity between the PoCUS training programs described. Course duration ranged from 3 hours to 2 years, with 11 of the 27 studies delivering obstetric-exclusive content. 44% trained multidisciplinary groups of health professionals. Long-term follow-up training and skills assessments were lacking in over half of the reviewed studies. Study quality and reporting detail varied, but overall beneficial outcomes were reported with 3/4s of the studies reaching upper KEF levels 3 and 4.

CONCLUSION

PoCUS performed by upskilled healthcare professionals offers an attractive solution to the problem of inequitable access to antenatal ultrasound. A review of available literature highlighted a paucity of comparable high-quality studies needed to establish a stronger evidence base for antenatal PoCUS, and a need to standardise training and competency assessment. This review may inform educators, researchers and policy-makers on existing training formats and methodologies to assist in establishing best practice antenatal PoCUS training methods for safe service delivery by remote healthcare professionals.