Performance of late pregnancy biometry for gestational age dating in low-income and middle-income countries: a prospective, multicountry, population-based cohort study from the WHO Alliance for Maternal and Newborn Health Improvement (AMANHI) Study Group

Maternal serum biomarkers of placental insufficiency at 24-28 weeks of pregnancy in relation to the risk of delivering small-for-gestational-age infant in Sylhet, Bangladesh: a prospective cohort study

BACKGROUND

Small-for-gestational-age (SGA), commonly caused by poor placentation, is a major contributor to global perinatal mortality and morbidity. Maternal serum levels of placental protein and angiogenic factors are changed in SGA. Using data from a population-based pregnancy cohort, we estimated the relationships between levels of second-trimester pregnancy-associated plasma protein-A (PAPP-A), placental growth factor (PlGF), and serum soluble fms-like tyrosine kinase-1 (sFlt-1) with SGA.

METHODS

Three thousand pregnant women were enrolled. Trained health workers prospectively collected data at home visits. Maternal blood samples were collected, serum aliquots were prepared and stored at -80℃. Included in the analysis were 1,718 women who delivered a singleton live birth baby and provided a blood sample at 24-28 weeks of gestation. We used Mann-Whitney U test to examine differences of the median biomarker concentrations between SGA (< 10th centile birthweight for gestational age) and appropriate-for-gestational-age (AGA). We created biomarker concentration quartiles and estimated the risk ratios (RRs) and 95% confidence intervals (CIs) for SGA by quartiles separately for each biomarker. A modified Poisson regression was used to determine the association of the placental biomarkers with SGA, adjusting for potential confounders.

RESULTS

The median PlGF level was lower in SGA pregnancies (934 pg/mL, IQR 613-1411 pg/mL) than in the AGA (1050 pg/mL, IQR 679-1642 pg/mL; p < 0.001). The median sFlt-1/PlGF ratio was higher in SGA pregnancies (2.00, IQR 1.18-3.24) compared to AGA pregnancies (1.77, IQR 1.06-2.90; p = 0.006). In multivariate regression analysis, women in the lowest quartile of PAPP-A showed 25% higher risk of SGA (95% CI 1.09-1.44; p = 0.002). For PlGF, SGA risk was higher in women in the lowest (aRR 1.40, 95% CI 1.21-1.62; p < 0.001) and 2nd quartiles (aRR 1.30, 95% CI 1.12-1.51; p = 0.001). Women in the highest and 3rd quartiles of sFlt-1 were at reduced risk of SGA delivery (aRR 0.80, 95% CI 0.70-0.92; p = 0.002, and aRR 0.86, 95% CI 0.75-0.98; p = 0.028, respectively). Women in the highest quartile of sFlt-1/PlGF ratio showed 18% higher risk of SGA delivery (95% CI 1.02-1.36; p = 0.025).

CONCLUSIONS

This study provides evidence that PAPP-A, PlGF, and sFlt-1/PlGF ratio measurements may be useful second-trimester biomarkers for SGA.

Overview of the Global and US Burden of Preterm Birth

Preterm birth (PTB) is the leading cause of morbidity and mortality in children globally, yet its prevalence has been difficult to accurately estimate due to unreliable methods of gestational age dating, heterogeneity in counting, and insufficient data. The estimated global PTB rate in 2020 was 9.9% (95% confidence interval: 9.1, 11.2), which reflects no significant change from 2010, and 81% of prematurity-related deaths occurred in Africa and Asia. PTB prevalence in the United States in 2021 was 10.5%, yet with concerning racial disparities. Few effective solutions for prematurity prevention have been identified, highlighting the importance of further research.

Utilization of third-trimester fetal transcerebellar diameter measurement for gestational age estimation: a comparative study using Bland-Altman analysis

BACKGROUND

Several studies show that gestational age estimation during the third trimester of pregnancy using fetal transcerebellar diameter is superior to that measured using fetal biometry (biparietal diameter, head circumference, abdominal circumference, and femur diaphysis length). However, the conclusion of the studies stemmed from findings of correlation and regression statistical tests, which are not the recommended statistical analysis methods for comparing the values of 1 variable as measured by 2 different methods.

OBJECTIVE

This study aimed to compare the accuracy of gestational age estimation using transcerebellar diameter to that using fetal biometry during the third trimester of pregnancy using Bland-Altman statistical analysis.

STUDY DESIGN

This was a cross-sectional study on pregnant women who presented for routine antenatal care follow-up in the third trimester of pregnancy (28-41 weeks of gestation) at St. Paul's Hospital Millennium Medical College (Ethiopia) between November 1, 2020, and February 28, 2021. Data were collected prospectively using a structured questionnaire on the Open Data Kit. The primary outcome of our study was the mean bias of gestational age estimation (error in estimating gestational age) using transcerebellar diameter and composite fetal biometry (composite gestational age). Data were analyzed using Stata (version 15; StataCorp, College Station, TX). Simple descriptive analysis, Bland-Altman analysis, and the Kendall τa discordance measurement were performed as appropriate. The mean bias (error) and limits of agreement were used to present the significance of the finding.

RESULTS

A total of 104 pregnant women in the third trimester were included in the study. The mean error (bias) when transcerebellar diameter was used to estimate the gestational age was 0.65 weeks vs a bias of 1.1 weeks using composite biometry, compared with the gold standard method from crown-lump length (in both cases). The calculated estimated limit of agreement was narrower in the case of transcerebellar diameter than in the case of composite fetal biometry (-3.56 to 2.25 vs -4.73 to 2.53). The Kendall τa discordance measurement revealed that gestational age estimations using composite biometry and crown-lump length were 51% to 70%, respectively, more likely to agree than disagree and that gestational age estimations using transcerebellar diameter and crown-lump length were 62% to 77%, respectively, more likely to agree than to disagree (P≤.001).

CONCLUSION

Gestational age estimation using transcerebellar diameter is more accurate than gestational age estimation using composite gestational age (biparietal diameter, head circumference, femur diaphysis length, and abdominal circumference). Transcerebellar diameter should be used to date third-trimester pregnancies with unknown gestational age (unknown last normal menstrual period with no early ultrasound milestone).

Can the date of last menstrual period be trusted in the first trimester? Comparisons of gestational age measures from a prospective cohort study in six low-income to middle-income countries

OBJECTIVES

We examined gestational age (GA) estimates for live and still births, and prematurity rates based on last menstrual period (LMP) compared with ultrasonography (USG) among pregnant women at seven sites in six low-resource countries.

DESIGN

Prospective cohort study SETTING AND PARTICIPANTS: This study included data from the Global Network's population-based Maternal and Newborn Health Registry which follows pregnant women in six low-income and middle-income countries (Democratic Republic of the Congo, Guatemala, India, Kenya, Pakistan and Zambia). Participants in this analysis were 42 803 women, including their 43 230 babies, who registered for the study in their first trimester based on GA estimated either by LMP or USG and had a live or stillbirth with an estimated GA of 20-42 weeks.

OUTCOME MEASURES

GA was estimated in weeks and days based on LMP and/or USG. Prematurity was defined as GA of 20 weeks+0 days through 36 weeks+6 days, calculated by both USG and LMP.

RESULTS

Overall, average GA varied ≤1 week between LMP and USG. Mean GA for live births by LMP was lower than by USG (adjusted mean difference (95% CI) = -0.23 (-0.29 to -0.17) weeks). Among stillbirths, a higher GA was estimated by LMP than USG (adjusted mean difference (95% CI)= 0.42 (0.11 to 0.72) weeks). Preterm birth rates for live births were significantly higher when dated by LMP (adjusted rate difference (95% CI)= 4.20 (3.56 to 4.85)). There was no significant difference in preterm birth rates for stillbirths.

CONCLUSION

The small differences in GA for LMP versus USG in the Guatemalan and Indian sites suggest that LMP may be a useful alternative to USG for GA dating during the first trimester until availability of USG improves in those areas. Further research is needed to assess LMP for first-trimester GA dating in other regions with limited access to USG.

TRIAL REGISTRATION NUMBER

NCT01073475.

Small babies, big risks: global estimates of prevalence and mortality for vulnerable newborns to accelerate change and improve counting

Small newborns are vulnerable to mortality and lifelong loss of human capital. Measures of vulnerability previously focused on liveborn low-birthweight (LBW) babies, yet LBW reduction targets are off-track. There are two pathways to LBW, preterm birth and fetal growth restriction (FGR), with the FGR pathway resulting in the baby being small for gestational age (SGA). Data on LBW babies are available from 158 (81%) of 194 WHO member states and the occupied Palestinian territory, including east Jerusalem, with 113 (58%) having national administrative data, whereas data on preterm births are available from 103 (53%) of 195 countries and areas, with only 64 (33%) providing national administrative data. National administrative data on SGA are available for only eight countries. Global estimates for 2020 suggest 13·4 million livebirths were preterm, with rates over the past decade remaining static, and 23·4 million were SGA. In this Series paper, we estimated prevalence in 2020 for three mutually exclusive types of small vulnerable newborns (SVNs; preterm non-SGA, term SGA, and preterm SGA) using individual-level data (2010-20) from 23 national datasets (∼110 million livebirths) and 31 studies in 18 countries (∼0·4 million livebirths). We found 11·9 million (50% credible interval [Crl] 9·1-12·2 million; 8·8%, 50% Crl 6·8-9·0%) of global livebirths were preterm non-SGA, 21·9 million (50% Crl 20·1-25·5 million; 16·3%, 14·9-18·9%) were term SGA, and 1·5 million (50% Crl 1·2-4·2 million; 1·1%, 50% Crl 0·9-3·1%) were preterm SGA. Over half (55·3%) of the 2·4 million neonatal deaths worldwide in 2020 were attributed to one of the SVN types, of which 73·4% were preterm and the remainder were term SGA. Analyses from 12 of the 23 countries with national data (0·6 million stillbirths at ≥22 weeks gestation) showed around 74% of stillbirths were preterm, including 16·0% preterm SGA and approximately one-fifth of term stillbirths were SGA. There are an estimated 1·9 million stillbirths per year associated with similar vulnerability pathways; hence integrating stillbirths to burden assessments and relevant indicators is crucial. Data can be improved by counting, weighing, and assessing the gestational age of every newborn, whether liveborn or stillborn, and classifying small newborns by the three vulnerability types. The use of these more specific types could accelerate prevention and help target care for the most vulnerable babies.

Small vulnerable newborns-big potential for impact

Despite major achievements in child survival, the burden of neonatal mortality has remained high and even increased in some countries since 1990. Currently, most neonatal deaths are attributable to being born preterm, small for gestational age (SGA), or with low birthweight (LBW). Besides neonatal mortality, these conditions are associated with stillbirth and multiple morbidities, with short-term and long-term adverse consequences for the newborn, their families, and society, resulting in a major loss of human capital. Prevention of preterm birth, SGA, and LBW is thus critical for global child health and broader societal development. Progress has, however, been slow, largely because of the global community's failure to agree on the definition and magnitude of newborn vulnerability and best ways to address it, to frame the problem attractively, and to build a broad coalition of actors and a suitable governance structure to implement a change. We propose a new definition and a conceptual framework, bringing preterm birth, SGA, and LBW together under a broader umbrella term of the small vulnerable newborn (SVN). Adoption of the framework and the unified definition can facilitate improved problem definition and improved programming for SVN prevention. Interventions aiming at SVN prevention would result in a healthier start for live-born infants, while also reducing the number of stillbirths, improving maternal health, and contributing to a positive economic and social development in the society.

Machine learning for accurate estimation of fetal gestational age based on ultrasound images

Accurate estimation of gestational age is an essential component of good obstetric care and informs clinical decision-making throughout pregnancy. As the date of the last menstrual period is often unknown or uncertain, ultrasound measurement of fetal size is currently the best method for estimating gestational age. The calculation assumes an average fetal size at each gestational age. The method is accurate in the first trimester, but less so in the second and third trimesters as growth deviates from the average and variation in fetal size increases. Consequently, fetal ultrasound late in pregnancy has a wide margin of error of at least ±2 weeks' gestation. Here, we utilise state-of-the-art machine learning methods to estimate gestational age using only image analysis of standard ultrasound planes, without any measurement information. The machine learning model is based on ultrasound images from two independent datasets: one for training and internal validation, and another for external validation. During validation, the model was blinded to the ground truth of gestational age (based on a reliable last menstrual period date and confirmatory first-trimester fetal crown rump length). We show that this approach compensates for increases in size variation and is even accurate in cases of intrauterine growth restriction. Our best machine-learning based model estimates gestational age with a mean absolute error of 3.0 (95% CI, 2.9-3.2) and 4.3 (95% CI, 4.1-4.5) days in the second and third trimesters, respectively, which outperforms current ultrasound-based clinical biometry at these gestational ages. Our method for dating the pregnancy in the second and third trimesters is, therefore, more accurate than published methods.

Development of a Machine Learning Model for Sonographic Assessment of Gestational Age

IMPORTANCE

Fetal ultrasonography is essential for confirmation of gestational age (GA), and accurate GA assessment is important for providing appropriate care throughout pregnancy and for identifying complications, including fetal growth disorders. Derivation of GA from manual fetal biometry measurements (ie, head, abdomen, and femur) is operator dependent and time-consuming.

OBJECTIVE

To develop artificial intelligence (AI) models to estimate GA with higher accuracy and reliability, leveraging standard biometry images and fly-to ultrasonography videos.

DESIGN, SETTING, AND PARTICIPANTS

To improve GA estimates, this diagnostic study used AI to interpret standard plane ultrasonography images and fly-to ultrasonography videos, which are 5- to 10-second videos that can be automatically recorded as part of the standard of care before the still image is captured. Three AI models were developed and validated: (1) an image model using standard plane images, (2) a video model using fly-to videos, and (3) an ensemble model (combining both image and video models). The models were trained and evaluated on data from the Fetal Age Machine Learning Initiative (FAMLI) cohort, which included participants from 2 study sites at Chapel Hill, North Carolina (US), and Lusaka, Zambia. Participants were eligible to be part of this study if they received routine antenatal care at 1 of these sites, were aged 18 years or older, had a viable intrauterine singleton pregnancy, and could provide written consent. They were not eligible if they had known uterine or fetal abnormality, or had any other conditions that would make participation unsafe or complicate interpretation. Data analysis was performed from January to July 2022.

MAIN OUTCOMES AND MEASURES

The primary analysis outcome for GA was the mean difference in absolute error between the GA model estimate and the clinical standard estimate, with the ground truth GA extrapolated from the initial GA estimated at an initial examination.

RESULTS

Of the total cohort of 3842 participants, data were calculated for a test set of 404 participants with a mean (SD) age of 28.8 (5.6) years at enrollment. All models were statistically superior to standard fetal biometry-based GA estimates derived from images captured by expert sonographers. The ensemble model had the lowest mean absolute error compared with the clinical standard fetal biometry (mean [SD] difference, -1.51 [3.96] days; 95% CI, -1.90 to -1.10 days). All 3 models outperformed standard biometry by a more substantial margin on fetuses that were predicted to be small for their GA.

CONCLUSIONS AND RELEVANCE

These findings suggest that AI models have the potential to empower trained operators to estimate GA with higher accuracy.

Metabolomics of a neonatal cohort from the Alliance for Maternal and Newborn Health Improvement biorepository: Effect of preanalytical variables on reference intervals

BACKGROUND

The study was conducted to determine reference interval (RI) and evaluate the effect of preanalytical variables on Dried blood spot (DBS)-amino acids, acylcarnitines and succinylacetone of neonates.

METHODOLOGY

DBS samples were collected within 48-72 hours of life. Samples were analyzed for biochemical markers on tandem mass spectrometer at the University of Iowa. Comparison of RI across various categorical variables were performed.

RESULTS

A total of 610 reference samples were selected based on exclusion criteria; 53.2% being females. Mean gestational age (GA) of mothers at the time of delivery was 38.7±1.6 weeks; 24.5% neonates were of low birth weight and 14.3% were preterm. Out of the total 610 neonates, 23.1% were small for GA. Reference intervals were generated for eleven amino acids, thirty-two acylcarnitines and succinylacetone concentrations. Markers were evaluated with respect to the influence of gender, GA, weight and time of sampling and statistically significant minimal differences were observed for some biomarkers.

CONCLUSION

RI for amino acids, succinylacetone and acylcarnitine on DBS has been established for healthy neonates, which could be of use in the clinical practice. Clinically significant effect of GA, weight, gender and time of sampling on these markers were not identified.

Midwife-Led Ultrasound Scanning to Date Pregnancy in Malawi: Development of a Novel Training Program

The use of ultrasound to determine gestational age is fundamental to the optimum management of pregnancy and is recommended for all women by the World Health Organization. However, this modality remains unavailable to many women in low-income countries where trained practitioners are scarce. Although previous initiatives have demonstrated efficacy in training midwives and technicians to perform antenatal ultrasound, these programs have often been too long and too complex to be realistic within the specific constraints of this context, highlighting the need for a novel and pragmatic approach. We describe the development and piloting of a bespoke course to teach midwives 3 fundamental components of early antenatal ultrasound scanning: (1) to identify the number of fetuses, (2) to confirm fetal viability, and (3) to determine gestational age. Having established that 5 days is insufficient, we propose that the minimum duration required to train ultrasound-naive midwives to competency is 10 days. Our completed program therefore consists of one and one-half days of didactic teaching, followed by 8 and one-half days of supervised hands-on practical training in which trainees are assessed on their skills. This package has subsequently been successfully implemented across 6 sites in Malawi, where 28 midwives have achieved competency. By describing the processes involved in our cross-continental collaboration, we explain how unexpected challenges helped shape and improve our program, demonstrating the value of preimplementation piloting and a pragmatic and adaptive approach.

A mobile-optimized artificial intelligence system for gestational age and fetal malpresentation assessment

Background

Fetal ultrasound is an important component of antenatal care, but shortage of adequately trained healthcare workers has limited its adoption in low-to-middle-income countries. This study investigated the use of artificial intelligence for fetal ultrasound in under-resourced settings.

Methods

Blind sweep ultrasounds, consisting of six freehand ultrasound sweeps, were collected by sonographers in the USA and Zambia, and novice operators in Zambia. We developed artificial intelligence (AI) models that used blind sweeps to predict gestational age (GA) and fetal malpresentation. AI GA estimates and standard fetal biometry estimates were compared to a previously established ground truth, and evaluated for difference in absolute error. Fetal malpresentation (non-cephalic vs cephalic) was compared to sonographer assessment. On-device AI model run-times were benchmarked on Android mobile phones.

Results

Here we show that GA estimation accuracy of the AI model is non-inferior to standard fetal biometry estimates (error difference -1.4 ± 4.5 days, 95% CI -1.8, -0.9, n = 406). Non-inferiority is maintained when blind sweeps are acquired by novice operators performing only two of six sweep motion types. Fetal malpresentation AUC-ROC is 0.977 (95% CI, 0.949, 1.00, n = 613), sonographers and novices have similar AUC-ROC. Software run-times on mobile phones for both diagnostic models are less than 3 s after completion of a sweep.

Conclusions

The gestational age model is non-inferior to the clinical standard and the fetal malpresentation model has high AUC-ROCs across operators and devices. Our AI models are able to run on-device, without internet connectivity, and provide feedback scores to assist in upleveling the capabilities of lightly trained ultrasound operators in low resource settings.

Measurement of symphysis fundal height for gestational age estimation in low-to-middle-income countries: A systematic review and meta-analysis

In low- and middle-income countries (LMIC), measurement of symphysis fundal height (SFH) is often the only available method of estimating gestational age (GA) in pregnancy. This systematic review aims to summarize methods of SFH measurement and assess the accuracy of SFH for the purpose of GA estimation. We searched PubMed, EMBASE, Cochrane, Web of Science, POPLINE, and WHO Global Health Libraries from January 1980 through November 2021. For SFH accuracy, we pooled the variance of the mean difference between GA confirmed by ultrasound versus SFH. Of 1,003 studies identified, 37 studies were included. Nineteen different SFH measurement techniques and 13 SFH-to-GA conversion methods were identified. In pooled analysis of five studies (n = 5838 pregnancies), 71% (95% CI: 66-77%) of pregnancies dated by SFH were within ±14 days of ultrasound confirmed dating. Using the 1 cm SFH = 1wk assumption, SFH underestimated GA compared with ultrasound-confirmed GA (mean bias: -14.0 days) with poor accuracy (95% limits of agreement [LOA]: ±42.8 days; n = 3 studies, 2447 pregnancies). Statistical modeling of three serial SFH measurements performed better, but accuracy was still poor (95% LOA ±33 days; n = 4 studies, 4391 pregnancies). In conclusion, there is wide variation in SFH measurement and SFH-to-GA conversion techniques. SFH is inaccurate for estimating GA and should not be used for GA dating. Increasing access to quality ultrasonography early in pregnancy should be prioritized to improve gestational age assessment in LMIC.

Second and third trimester estimation of gestational age using ultrasound or maternal symphysis-fundal height measurements: A systematic review

Many vulnerable women seek antenatal care late in pregnancy. How should gestational age be determined? We examine all available studies estimating GA >20 weeks. Ultrasound is much better than fundal height, and using cerebellar measurement appears to be the most accurate.

Linked article: This article is commented on by Philip J. Steer, pp. 1459 in this issue. To view this minicommentary visit https://doi.org/10.1111/1471‐0528.17127 .

Leveraging Artificial Intelligence to Improve Pregnancy Dating in Low-Resource Settings

For practicing obstetricians and pediatricians, accurate gestational age (GA) is a cornerstone of quality care during pregnancy and the newborn period. GA determines prenatal management decisions, such as eligibility for antenatal glucocorticoids if preterm delivery is anticipated or timing of delivery in complicated pregnancies to avoid stillbirth or maternal morbidity. Knowledge of GA for women in labor also allows for transfer to facilities capable of handling preterm infants and guides postnatal resuscitation practices and specialized newborn care.

Maternal and child surveillance in peri-urban communities: Perceptions of women and community health workers from Pakistan

Community health workers (CHWs) in maternal, newborn, and child health (MNCH) programs play an important role in demographic surveillance activities; however, there is lack of literature regarding the community and CHWs' perceptions about these activities. The purpose of this study was to explore perceptions of married women of reproductive age (MWRA) regarding the role of CHWs involved in maternal and child surveillance and explore facilitators and barriers for CHWs involved in surveillance activities. A qualitative study was conducted in five peri-urban surveillance sites along the coastal belt of Bin Qasim Town, Karachi, Pakistan. In-depth interviews were conducted with 25 randomly selected MWRAs and 15 CHWs. A thematic analysis was performed to explore perceptions, barriers, and facilitators of the study participants about maternal and child surveillance activities. The results showed that MWRAs perceived surveillance CHWs as service providers with regards to standard counselling i.e. importance of antenatal care, nutrition, immunization, and distribution of iron and folic acid tablets to pregnant women, child growth assessment, and referral of sick children to the health facility. Trust in the CHWs was an enabler for MWRAs, whereas lack of incentives was cited as a barrier to share their health data. CHWs perceived themselves as a bridge in liaising community with the primary health care facility. They highlighted an enabling environment such as appreciation, supportive supervision, training, and utilization of digital data collection tools as facilitators for their work. Low health literacy of the communities, lack of provision of incentives by CHWs to the community, and facility-based experiences of the community were reported as barriers. Surveillance CHWs are an integral link between the health facility and MWRAs. Hence an enabling environment may lead to improved health service delivery, translating into meaningful impact for the mother and child.

Training in Ultrasound to Determine Gestational Age (TUDA): Evaluation of a Novel Education Package to Teach Ultrasound-Naive Midwives Basic Obstetric Ultrasound in Malawi

Introduction

Although ultrasound to determine gestational age is fundamental to the optimum management of pregnancy and is recommended for all women by the World Health Organisation, it remains unavailable to many women in low-income countries where trained practitioners are scarce. This study aimed to evaluate a novel, context-specific education package to teach midwives basic obstetric ultrasound, including the determination of gestational age by measurement of fetal femur length.

Methods

The study was conducted across six sites in Malawi in January 2021. Following a virtual "training of the trainers", local teams delivered a 10-day programme encompassing both didactic and "hands on" components. Matched pre and post course tests assessed participants' knowledge of key concepts, with Objective Structured Clinical Examinations used to evaluate practical skills. To achieve a pass, trainees were required to establish the gestational age to within ±7 days of an experienced practitioner and achieve an overall score of >65% on five consecutive occasions. A matched pre and post course survey explored participants' attitudes and confidence in performing ultrasound examinations.

Results

Of the 29 midwives who participated, 28 finished the programme and met the criteria specified to pass. 22 midwives completed the matched knowledge tests, with the mean (SD) score increasing from 10.2 (3.3) to 18 (2.5) after training (P <0.0001). Mean difference 7.9, 95% CI 6.5-9.2. Midwives passed 87% of the Observed Structured Clinical Examinations, establishing the gestational age to within ±7 days of an experienced practitioner in 89% of assessments. Beliefs regarding the importance of antenatal ultrasound increased post course (p = 0.02), as did confidence in performing ultrasound examinations (p <0.0001).

Conclusion

This study demonstrates not only that ultrasound-naive practitioners can be taught to perform basic obstetric ultrasound dating scans, confidently and competently, after 10 days of training, but also that local teams can be orientated to successfully deliver the programme virtually. Previous ultrasound training initiatives, while often more comprehensive in their syllabus, have been of considerably longer duration and this is likely to be a barrier to upscaling opportunities. We propose that this focused training increases the potential for widescale and sustainable implementation.

Training in Ultrasound to Determine Gestational Age in Low- and Middle- Income Countries: A Systematic Review

Introduction

Establishing an accurate gestational age is essential for the optimum management of pregnancy, delivery and neonatal care, with improved estimates of gestational age considered a public health priority by the World Health Organization (WHO). Although ultrasound is considered the most precise method to achieve this, it is unavailable to many women in low- and middle- income countries (LMICs), where the lack of trained practitioners is considered a major barrier. This systematic review explores what initiatives have previously been undertaken to train staff to date pregnancies using ultrasound, which were successful and what barriers and facilitators influenced training.

Methods

The systematic review was conducted according to PRISMA guidelines and the protocol registered (PROSPERO CRD42019154619). Searches were last performed in July 2021. Studies were screened independently by two assessors, with data extracted by one and verified by the other. Both reviewers graded the methodological quality using the Mixed Methods Assessment Tool. Results were collated within prespecified domains, generating a narrative synthesis.

Results

25/1,262 studies were eligible for inclusion, all of which were programme evaluations. Eighteen were undertaken in Africa, three in South-East Asia, one in South America, and three across multiple sites, including those in Africa, Asia, and South America. Five programs specified criteria to pass, and within these 96% of trainees did so. Trainee follow up was undertaken in 18 studies. Ten met recommendations for training outlined by the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) but only 1 met the current standards set by the WHO.

Discussion

This systematic review is the first to evaluate this topic and has uncovered major inconsistencies in the delivery and reporting of basic obstetric ultrasound training in LMICs, with the majority of programs not meeting minimum recommendations. By identifying these issues, we have highlighted key areas for improvement and made recommendations for reporting according to the RE-AIM framework. With an increasing focus on the importance of improving estimates of gestational age in LMICs, we believe these findings will be of significance to those seeking to develop and expand the provision of sustainable obstetric ultrasound in LMICs.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019154619, PROSPERO CRD42019154619.

High Prevalence of Low Birth Weight Babies Born to Pregnant Women Referred to a District Hospital in Rural Zambia

OBJECTIVES

Low birthweight (LBW) is a significant public health problem in sub-Saharan Africa and LBW in rural Zambia is high. Our study explored the prevalence of LBW for newborns whose mothers were referred from a rural health center to a district referral hospital in Lundazi, Zambia.

METHODS

A five-month retrospective record review of Ministry of Health data was performed to examine birthweight characteristics of a convenience sample of newborns from ten facilities referring to one district hospital (n = 234).

RESULTS

Among all cases, 21% (n = 49) of newborns were LBW. For LBW newborns, 73% (n = 36) were preterm with mothers having a pregnancy duration of less than 37 weeks. Newborns whose mothers experienced twin pregnancies (p = .021) and prolonged labor (p = .033) were more often LBW. However, regression models demonstrated no difference among newborns with and without LBW for prolonged labor (p = .344) and twin pregnancies (p = .324) when controlling for variables that could interact with the maternal-newborn delivery outcomes.

CONCLUSIONS

for Practice Healthcare providers and policy makers need to address the short and long-term effects of LBW throughout the lifecycle in rural Zambia. More maternal-newborn health research is needed to understand the underlying socioeconomic, social, and cultural determinants influencing LBW in rural Zambia.

A review of fetal cardiac monitoring, with a focus on low- and middle-income countries

There is limited evidence regarding the utility of fetal monitoring during pregnancy, particularly during labor and delivery. Developed countries rely on consensus ‘best practices’ of obstetrics and gynecology professional societies to guide their protocols and policies. Protocols are often driven by the desire to be as safe as possible and avoid litigation, regardless of the cost of downstream treatment. In high-resource settings, there may be a justification for this approach. In low-resource settings, in particular, interventions can be costly and lead to adverse outcomes in subsequent pregnancies. Therefore, it is essential to consider the evidence and cost of different fetal monitoring approaches, particularly in the context of treatment and care in low-to-middle income countries.

This article reviews the standard methods used for fetal monitoring, with particular emphasis on fetal cardiac assessment, which is a reliable indicator of fetal well-being. An overview of fetal monitoring practices in low-to-middle income counties, including perinatal care access challenges, is also presented. Finally, an overview of how mobile technology may help reduce barriers to perinatal care access in low-resource settings is provided.

Beyond Newborn Resuscitation: Essential Care for Every Baby and Small Babies

Helping Babies Breathe (HBB) addresses a major cause of newborn mortality by teaching basic steps of neonatal resuscitation and improving survival rates of infants affected by intrapartum-related events or asphyxia. Addressing the additional top causes of mortality (infection and prematurity) requires more comprehensive education, including content on thermal and nutritional support, breastfeeding, and alternative feeding strategies, as well as recognition and treatment of infection. Essential Care for Every Baby (ECEB) and Essential Care for Small Babies (ECSB) use educational principles developed with HBB as a model for teaching basic newborn care. These programs complement the content provided with HBB, further integrate counseling of families, and advance the agenda of providing quality care to all infants at birth. ECEB and ECSB have further demonstrated that engagement of individuals through active participation in their education empowers providers at all levels. With added experience teaching and implementing ECEB and ECSB, the next generation of newborn educational programs will likely incorporate bedside teaching and clinical exposure, multimedia platforms for demonstrating clinical content, and added efforts toward quality improvement. Through ECEB and ECSB, the attention brought to the newborn health agenda with HBB has only grown. Although current global health issues pose new challenges in implementing this agenda, these programs together provide a critical framework to both educate and advocate for optimal care of every newborn.