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What innovative therapies are there for Endometriosis - a condition that affects up to 10% of women during their reproductive life span, causing severe pelvic pain and reduced fertility.
Mapping cell-to-tissue graphs across human placenta histology whole slide images using deep learning with HAPPY.
Accurate placenta pathology assessment is essential for managing maternal and newborn health, but the placenta's heterogeneity and temporal variability pose challenges for histology analysis. To address this issue, we developed the 'Histology Analysis Pipeline.PY' (HAPPY), a deep learning hierarchical method for quantifying the variability of cells and micro-anatomical tissue structures across placenta histology whole slide images. HAPPY differs from patch-based features or segmentation approaches by following an interpretable biological hierarchy, representing cells and cellular communities within tissues at a single-cell resolution across whole slide images. We present a set of quantitative metrics from healthy term placentas as a baseline for future assessments of placenta health and we show how these metrics deviate in placentas with clinically significant placental infarction. HAPPY's cell and tissue predictions closely replicate those from independent clinical experts and placental biology literature.
Is telehealth useful in the management of placenta accreta spectrum in low-resource settings? Results of an exploratory survey.
OBJECTIVE: The optimal management of placenta accreta spectrum (PAS) requires the participation of multidisciplinary teams that are often not locally available in low-resource settings. Telehealth has been increasingly used to manage complex obstetric conditions. Few studies have explored the use of telehealth for PAS management, and we aimed evaluate the usage of telehealth in the management of PAS patients in low-resource settings. METHODS: Between March and April 2023, an observational, survey-based study was conducted, and obstetricians-gynecologists with expertise in PAS management in low- and middle-income countries were contacted to share their opinion on the potential use of telehealth for the diagnosis and management of patients at high-risk of PAS at birth. Participants were identified based on their authorship of at least one published clinical study on PAS in the last 5 years and contacted by email. This is a secondary analysis of the results of that survey. RESULTS: From 158 authors contacted we obtained 65 responses from participants in 27 middle-income countries. A third of the participants reported the use of telehealth during the management obstetric emergencies (38.5%, n = 25) and PAS (36.9%, n = 24). Over 70% of those surveyed indicated that they had used "informal" telemedicine (phone call, email, or text message) during PAS management. Fifty-nine participants (90.8%) reported that recommendations given remotely by expert colleagues were useful for management of patients with PAS in their setting. CONCLUSION: Telehealth has been successfully used for the management of PAS in middle-income countries, and our survey indicates that it could support the development of specialist care in other low resource settings.
Are international guideline recommendations for the management of placenta accreta spectrum applicable in low- and middle-income countries?
OBJECTIVE: The aim of this study was to explore how obstetricians-gynecologists in low- and middle-income countries (LMICs) can apply current international clinical practice guidelines (CPGs) for the management of placenta accreta spectrum (PAS) in limited resource settings. METHODS: This was an observational, survey-based study. Clinicians with expertise in managing patients with PAS in LMICs were contacted for their evaluation of the recommendations included in four PAS clinical practice guidelines. RESULTS: Out of the 158 clinicians contacted, we obtained responses from 65 (41.1%), representing 27 middle income countries (MICs). The results of this survey suggest that the care of PAS patients in middle income countries is very different from what is recommended by international CPGs. Participants in the survey identified that their practice was limited by insufficient availability of hospital infrastructure, low resources of local health systems and lack of trained multidisciplinary teams (MDTs) and this did not enable them to follow CPG recommendations. Two-thirds of the participants surveyed describe the absence of centers of excellence in their country. In over half of the referral hospitals with expertise in managing PAS, there are no MDTs. One-third of patients with intraoperative findings of PAS are managed by the team initially performing the surgery (without additional assistance). CONCLUSION: The care of patients with PAS in middle income countries frequently deviates from established CPG recommendations largely due to limitations in local resources and infrastructure. New practical guidelines and training programs designed for low resource settings are needed.
Cooking with liquefied petroleum gas or biomass and fetal growth outcomes: a multi-country randomised controlled trial.
BACKGROUND: Household air pollution might lead to fetal growth restriction during pregnancy. We aimed to investigate whether a liquefied petroleum gas (LPG) intervention to reduce personal exposures to household air pollution during pregnancy would alter fetal growth. METHODS: The Household Air Pollution Intervention Network (HAPIN) trial was an open-label randomised controlled trial conducted in ten resource-limited settings across Guatemala, India, Peru, and Rwanda. Pregnant women aged 18-34 years (9-19 weeks of gestation) were randomly assigned in a 1:1 ratio to receive an LPG stove, continuous fuel delivery, and behavioural messaging or to continue usual cooking with biomass for 18 months. We conducted ultrasound assessments at baseline, 24-28 weeks of gestation (the first pregnancy visit), and 32-36 weeks of gestation (the second pregnancy visit), to measure fetal size; we monitored 24 h personal exposures to household air pollutants during these visits; and we weighed children at birth. We conducted intention-to-treat analyses to estimate differences in fetal size between the intervention and control group, and exposure-response analyses to identify associations between household air pollutants and fetal size. This trial is registered with ClinicalTrials.gov (NCT02944682). FINDINGS: Between May 7, 2018, and Feb 29, 2020, we randomly assigned 3200 pregnant women (1593 to the intervention group and 1607 to the control group). The mean gestational age was 14·5 (SD 3·0) weeks and mean maternal age was 25·6 (4·5) years. We obtained ultrasound assessments in 3147 (98·3%) women at baseline, 3052 (95·4%) women at the first pregnancy visit, and 2962 (92·6%) at the second pregnancy visit, through to Aug 25, 2020. Intervention adherence was high (the median proportion of days with biomass stove use was 0·0%, IQR 0·0-1·6) and pregnant women in the intervention group had lower mean exposures to particulate matter with a diameter less than 2·5 μm (PM2·5; 35·0 [SD 37·2] μg/m3vs 103·3 [97·9] μg/m3) than did women in the control group. We did not find differences in averaged post-randomisation Z scores for head circumference (0·30 vs 0·39; p=0·04), abdominal circumference (0·38 vs 0·39; p=0·99), femur length (0·44 vs 0·45; p=0·73), and estimated fetal weight or birthweight (-0·13 vs -0·12; p=0·70) between the intervention and control groups. Personal exposures to household air pollutants were not associated with fetal size. INTERPRETATION: Although an LPG cooking intervention successfully reduced personal exposure to air pollution during pregnancy, it did not affect fetal size. Our findings do not support the use of unvented liquefied petroleum gas stoves as a strategy to increase fetal growth in settings were biomass fuels are used predominantly for cooking. FUNDING: US National Institutes of Health and Bill & Melinda Gates Foundation. TRANSLATIONS: For the Kinyarwanda, Spanish and Tamil translations of the abstract see Supplementary Materials section.
The effect of animal versus plant protein on muscle mass, muscle strength, physical performance and sarcopenia in adults: protocol for a systematic review
Abstract Background The evidence base for the role of dietary protein in maintaining good muscle health in older age is strong; however, the importance of protein source remains unclear. Plant proteins are generally of lower quality, with a less favourable amino acid profile and reduced bioavailability; therefore, it is possible that their therapeutic effects may be less than that of higher quality animal proteins. This review aims to evaluate the effectiveness of plant and animal protein interventions on muscle health outcomes. Methods A robust search strategy was developed to include terms relating to dietary protein with a focus on protein source, for example dairy, meat and soy. These were linked to terms related to muscle health outcomes, for example mass, strength, performance and sarcopenia. Five databases will be searched: MEDLINE, Scopus, Cochrane Central Register of Controlled Trials, Embase and Web of Science. Studies included will be randomised controlled trials with an adult population (≥ 18) living in the community or residential homes for older adults, and only English language articles will be included. Two independent reviewers will assess eligibility of individual studies. The internal validity of included studies will be assessed using Cochrane Risk of Bias 2.0 tool. Results will be synthesised in narrative format. Where applicable, standardised mean differences (SMD) (95% confidence interval [CI]) will be combined using a random-effects meta-analysis, and tests of homogeneity of variance will be calculated. Discussion Dietary guidelines recommend a change towards a plant-based diet that is more sustainable for health and for the environment; however, reduction of animal-based foods may impact protein quality in the diet. High-quality protein is important for maintenance of muscle health in older age; therefore, there is a need to understand whether replacement of animal protein with plant protein will make a significant difference in terms of muscle health outcomes. Findings from this review will be informative for sustainable nutritional guidelines, particularly for older adults and for those following vegan or vegetarian diets. Systematic review registration PROSPERO CRD420201886582
Effects of PROtein enriched MEDiterranean Diet and EXercise on nutritional status and cognition in adults at risk of undernutrition and cognitive decline: the PROMED-EX Randomised Controlled Trial.
IntroductionUndernutrition leading to unplanned weight loss is common in older age and has been linked to increased dementia risk in later life. Weight loss can precede dementia by a decade or more, providing a unique opportunity for early intervention to correct undernutrition and potentially prevent or delay cognitive impairment. The combined effects of diet and exercise on undernutrition have not yet been evaluated. The objective of this trial is to determine the effect of a protein-enriched Mediterranean diet, with and without exercise, on nutritional status and cognitive performance in older adults at risk of undernutrition and cognitive decline.MethodsOne hundred and five participants aged 60 years and over at risk of undernutrition and with subjective cognitive decline will be recruited to participate in a 6-month, single-blind, parallel-group randomised controlled trial. Participants will be block randomised into one of three groups: group 1—PROMED-EX (diet+exercise), group 2—PROMED (diet only) and group 3—standard care (control). The primary outcome is nutritional status measured using the Mini Nutritional Assessment. Secondary outcomes include cognitive function, nutritional intake, body composition, physical function and quality of life. Mechanistic pathways for potential diet and exercise-induced change in nutritional status and cognition will be explored by measuring inflammatory, metabolic, nutritional and metabolomic biomarkers.Ethics and disseminationThe study is approved by the UK Office for Research Ethics Committee (ref: 21/NW/0215). Written informed consent will be obtained from participants prior to recruitment. Research results will be disseminated to the public via meetings and media and the scientific community through conference presentations and publication in academic journals.Trial registration numberClinicalTrials.gov Registry (NCT05166564).
Machine learning-enabled maternal risk assessment for women with pre-eclampsia (the PIERS-ML model): a modelling study.
BACKGROUND: Affecting 2-4% of pregnancies, pre-eclampsia is a leading cause of maternal death and morbidity worldwide. Using routinely available data, we aimed to develop and validate a novel machine learning-based and clinical setting-responsive time-of-disease model to rule out and rule in adverse maternal outcomes in women presenting with pre-eclampsia. METHODS: We used health system, demographic, and clinical data from the day of first assessment with pre-eclampsia to predict a Delphi-derived composite outcome of maternal mortality or severe morbidity within 2 days. Machine learning methods, multiple imputation, and ten-fold cross-validation were used to fit models on a development dataset (75% of combined published data of 8843 patients from 11 low-income, middle-income, and high-income countries). Validation was undertaken on the unseen 25%, and an additional external validation was performed in 2901 inpatient women admitted with pre-eclampsia to two hospitals in south-east England. Predictive risk accuracy was determined by area-under-the-receiver-operator characteristic (AUROC), and risk categories were data-driven and defined by negative (-LR) and positive (+LR) likelihood ratios. FINDINGS: Of 8843 participants, 590 (6·7%) developed the composite adverse maternal outcome within 2 days, 813 (9·2%) within 7 days, and 1083 (12·2%) at any time. An 18-variable random forest-based prediction model, PIERS-ML, was accurate (AUROC 0·80 [95% CI 0·76-0·84] vs the currently used logistic regression model, fullPIERS: AUROC 0·68 [0·63-0·74]) and categorised women into very low risk (-LR <0·1; eight [0·7%] of 1103 women), low risk (-LR 0·1 to 0·2; 321 [29·1%] women), moderate risk (-LR >0·2 and +LR <5·0; 676 [61·3%] women), high risk (+LR 5·0 to 10·0, 87 [7·9%] women), and very high risk (+LR >10·0; 11 [1·0%] women). Adverse maternal event rates were 0% for very low risk, 2% for low risk, 5% for moderate risk, 26% for high risk, and 91% for very high risk within 48 h. The 2901 women in the external validation dataset were accurately classified as being at very low risk (0% with outcomes), low risk (1%), moderate risk (4%), high risk (33%), or very high risk (67%). INTERPRETATION: The PIERS-ML model improves identification of women with pre-eclampsia who are at lowest and greatest risk of severe adverse maternal outcomes within 2 days of assessment, and can support provision of accurate guidance to women, their families, and their maternity care providers. FUNDING: University of Strathclyde Diversity in Data Linkage Centre for Doctoral Training, the Fetal Medicine Foundation, The Canadian Institutes of Health Research, and the Bill & Melinda Gates Foundation.
A method to isolate syncytiotrophoblast-derived medium-large extracellular vesicle small RNA from maternal plasma
Syncytiotrophoblast-derived extracellular vesicles (STB-EVs) have an important role in placental research: both as mediators of feto-maternal signalling and as liquid biopsies reflecting placental health. Recent evidence highlights the importance of STB-EV RNA. Isolation of STB-EV RNA from maternal blood is therefore an important challenge. We describe a novel technique where we first separate medium-large particles from plasma using centrifugation then use a highly specific bead-bound antibody to placental alkaline phosphatase to separate STB-EVs from other similar-sized particles. We demonstrate the yield and size profile of small RNA obtained from plasma STB-EVs. We present data confirming isolation of placenta-derived micro RNA from maternal plasma using this method. The technique has been successfully applied to validate novel RNA discoveries from placental perfusion models. We propose it could offer new insights through transcriptomic analyses, providing a syncytiotrophoblast-specific signal from maternal blood.
MicroRNA analysis of medium/large placenta extracellular vesicles in normal and preeclampsia pregnancies
BackgroundPreeclampsia (PE) is a hypertensive disorder of pregnancy, affecting 2%–8% of pregnancies worldwide, and is the leading cause of adverse maternal and fetal outcomes. The disease is characterized by oxidative and cellular stress and widespread endothelial dysfunction. While the precise mechanisms are not entirely understood, the pathogenesis of PE is closely linked to placental dysfunction and, to some extent, syncytiotrophoblast extracellular vesicle release (STB-EVs). These vesicles can be divided into the less well-studied medium/large EVs (220–1,000 nm) released in response to stress and small EVs (<220 nm) released as a component of intercellular communication. The previously described production of m/lSTB-EVs in response to cellular stress combined with the overwhelming occurrence of cellular and oxidative stress in PE prompted us to evaluate the microRNAome of PE m/lSTB-EVs. We hypothesized that the microRNAome profile of m/lSTB-EVs is different in PE compared to normal pregnancy (NP), which might permit the identification of potential circulating biomarkers not previously described in PE.Methods/study designWe performed small RNA sequencing on medium/large STB-EVs isolated from PE and NP placentae using dual-lobe ex vivo perfusion. The sequencing data was bioinformatically analyzed to identify differentially regulated microRNAs. Identified microRNAs were validated with quantitative PCR analysis. We completed our analysis by performing an in-silico prediction of STB-EV mechanistic pathways.ResultsWe identified significant differences between PE and NP in the STB-EVs micro ribonucleic acid (microRNA) profiles. We verified the differential expression of hsa-miR-193b-5p, hsa-miR-324-5p, hsa-miR-652-3p, hsa-miR-3196, hsa-miR-9-5p, hsa-miR-421, and hsa-miR-210-3p in the medium/large STB-EVs. We also confirmed the differential abundance of hsa-miR-9-5p in maternal serum extracellular vesicles (S EVs). In addition, we integrated the results of these microRNAs into the previously published messenger RNA (mRNA) data to better understand the relationship between these biomolecules.ConclusionsWe identified a differentially regulated micro-RNA, hsa-miR-9-5p, that may have biomarker potential and uncovered mechanistic pathways that may be important in the pathophysiology of PE.
A cross-sectional analysis of syncytiotrophoblast membrane extracellular vesicles–derived transcriptomic biomarkers in early-onset preeclampsia
BackgroundPreeclampsia (PE) is a pregnancy-specific hypertensive disorder affecting 2%–8% of pregnancies worldwide. Biomarker(s) for the disorder exists, but while these have excellent negative predictive value, their positive predictive value is poor. Extracellular vesicles released by the placenta into the maternal circulation, syncytiotrophoblast membrane extracellular vesicles (STB-EVs), have been identified as being involved in PE with the potential to act as liquid biopsies.ObjectiveThe objective of this study was to identify the difference in the transcriptome of placenta and STB-EVs between preeclampsia and normal pregnancy (NP) and mechanistic pathways.Methods/study designWe performed RNA-sequencing on placental tissue, medium/large and small STB-EVs from PE (n = 6) and NP (n = 6), followed by bioinformatic analysis to identify targets that could be used in the future for EV-based diagnostic tests for preeclampsia. Some of the identified biomarkers were validated with real-time polymerase chain reactions.ResultsOur analysis identified a difference in the transcriptomic STB-EV cargo between PE and NP. We then identified and verified the differential expression of FLNB, COL17A1, SLC45A4, LEP, HTRA4, PAPP-A2, EBI3, HSD17B1, FSTL3, INHBA, SIGLEC6, and CGB3. Our analysis also identified interesting mechanistic processes via an in silico prediction of STB-EV-based mechanistic pathways.ConclusionsIn this study, using comprehensive profiling of differentially expressed/carried genes of three linked sample subtypes in PE, we identified potential biomarkers and mechanistic gene pathways that may be important in the pathophysiology of PE and could be further explored in future studies.
Predicting risk of preterm birth in singleton pregnancies using machine learning algorithms
We aimed to develop, train, and validate machine learning models for predicting preterm birth (<37 weeks' gestation) in singleton pregnancies at different gestational intervals. Models were developed based on complete data from 22,603 singleton pregnancies from a prospective population-based cohort study that was conducted in 51 midwifery clinics and hospitals in Wenzhou City of China between 2014 and 2016. We applied Catboost, Random Forest, Stacked Model, Deep Neural Networks (DNN), and Support Vector Machine (SVM) algorithms, as well as logistic regression, to conduct feature selection and predictive modeling. Feature selection was implemented based on permutation-based feature importance lists derived from the machine learning models including all features, using a balanced training data set. To develop prediction models, the top 10%, 25%, and 50% most important predictive features were selected. Prediction models were developed with the training data set with 5-fold cross-validation for internal validation. Model performance was assessed using area under the receiver operating curve (AUC) values. The CatBoost-based prediction model after 26 weeks' gestation performed best with an AUC value of 0.70 (0.67, 0.73), accuracy of 0.81, sensitivity of 0.47, and specificity of 0.83. Number of antenatal care visits before 24 weeks' gestation, aspartate aminotransferase level at registration, symphysis fundal height, maternal weight, abdominal circumference, and blood pressure emerged as strong predictors after 26 completed weeks. The application of machine learning on pregnancy surveillance data is a promising approach to predict preterm birth and we identified several modifiable antenatal predictors.
Cognitive function and skeletal size and mineral density at age 6-7 years: Findings from the Southampton Women's Survey.
INTRODUCTION: Poor cognitive function and osteoporosis commonly co-exist in later life. In women, this is often attributed to post-menopausal estrogen loss. However, a common early life origin for these conditions and the associations between cognitive function and bone mineral density (BMD) in childhood have not previously been explored. We examined these relationships at age 6-7 years in the Southampton Women's Survey (SWS) mother-offspring cohort. METHODS: Child occipitofrontal circumference (OFC), a proxy for brain volume, intelligence quotient (IQ) [Wechsler Abbreviated Scale of Intelligence] and visual recognition and working memory [CANTAB® Delayed Matching to Sample (DMS) and Spatial Span Length (SSP), respectively] were assessed. Whole-body-less-head (WBLH) and lumbar spine dual-energy X-ray absorptiometry [Hologic Discovery] (DXA) were performed to measure bone area (BA), bone mineral content (BMC), BMD and bone mineral apparent density (BMAD). Linear regression was used to examine associations between age and sex standardized variables (β represent standard deviation (SD) difference per SD of cognitive function). RESULTS: DXA was performed in 1331 children (mean (SD) age 6.8 (0.33) years, 51.5 % male), with OFC, IQ, DMS and SSP assessed in 1250, 551, 490 and 460, respectively. OFC (β = 0.25 SD/SD, 95%CI 0.20,0.30), IQ (β = 0.11 SD/SD, 95%CI 0.02,0.19), and DMS (β = 0.11, SD/SD, 95%CI 0.01,0.20) were positively associated with WBLH BA, with similar associations for lumbar spine BA. OFC and DMS were also positively associated with WBLH BMC, but only OFC was associated with BMD (WBLH: β = 0.38 SD/SD, 95%CI 0.33,0.43; LS: β = 0.19 SD/SD, 95%CI 0.13,0.24). CONCLUSION: Childhood brain volume was positively associated with measures of skeletal size and BMD, whereas IQ and memory were associated only with skeletal size. These findings suggest that common early life determinants for skeletal growth and BMD and cognitive function should be explored to identify potential early-life approaches to preventing osteoporosis and cognitive decline.
Detection of Germline Mosaicism for Robertsonian Translocation 14;14: A Case Report
Background: Chromosomal structural rearrangements can lead to fertility problems and recurrent miscarriages. The intricate interplay of genetics during human development can lead to subtle anomalies that may affect reproduction. Case Presentation: A 33-year-old woman sought fertility treatment after experiencing six miscarriages. Products of conception from the final pregnancy loss had been karyotyped, revealing a Robertsonian translocation (RT), involving chromosome 14. Fertility investigations showed low anti-Mullerian hormone (AMH) levels but otherwise normal female characteristics with normal sperm parameters of her husband were observed and both partners having a normal karyotype. Two embryos were transferred in an IVF cycle but neither resulted in a successful pregnancy. Subsequently, preimplantation genetic testing for aneuploidy (PGT-A) was applied to trophectoderm biopsy specimens from 4 embryos, which revealed abnormalities involving chromosome 14. Sperm aneuploidy testing failed to detect any increase in the incidence of aneuploidy affecting chromosome 14. Further embryos genetic testing indicated that all identified chromosome 14 abnormalities in the embryos had a maternal (oocyte) origin. Conclusion: This case underscores challenges in diagnosing and managing germline mosaicism in fertility. A maternal 14;14 Robertsonian translocation, undetected in the patient's blood but impacting oocytes, likely explains recurrent miscarriage and observed embryo aneuploidies. Genetic mosaicism in reproductive medicine highlights the necessity for advanced testing and personalized treatments. Data integration from various genetic analyses could enhance managing treatment expectations and improving fertility experiences.
Comparative risk of adverse perinatal outcomes associated with classes of antiretroviral therapy in pregnant women living with HIV: systematic review and meta-analysis.
BACKGROUND: Integrase strand transfer inhibitor (INSTI) dolutegravir (DTG)-based antiretroviral therapy (ART) is recommended by World Health Organisation as preferred first-line regimen in pregnant women living with human immunodeficiency virus (HIV) (WLHIV). Non-nucleoside reverse transfer inhibitor (NNRTI)-based ART and protease inhibitor (PI)-based ART are designated as alternative regimens. The impact of different ART regimens on perinatal outcomes is uncertain. We aimed to assess the comparative risk of adverse perinatal outcomes in WLHIV receiving different classes of ART. MATERIALS AND METHODS: A systematic literature review was conducted by searching PubMed, CINAHL, Global Health, and EMBASE for studies published between Jan 1, 1980, and July 14, 2023. We included studies reporting on the association of pregnant WLHIV receiving different classes of ART with 11 perinatal outcomes: preterm birth (PTB), very PTB, spontaneous PTB, low birthweight (LBW), very LBW, term LBW, preterm LBW, small for gestational age (SGA), very SGA (VSGA), stillbirth, and neonatal death. Pairwise random-effects meta-analyses compared the risk of each adverse perinatal outcome among WLHIV receiving INSTI-ART, NNRTI-ART, PI-ART, and nucleoside reverse transfer inhibitor (NRTI)-based ART, and compared specific "third drugs" from different ART classes. Subgroup and sensitivity analyses were conducted based on country income status and study quality. RESULTS: Thirty cohort studies published in 2006-2022, including 222,312 pregnant women, met the eligibility criteria. Random-effects meta-analyses found no evidence that INSTI-ART is associated with adverse perinatal outcomes compared to NNRTI-ART and PI-ART. We found that PI-ART is associated with a significantly increased risk of SGA (RR 1.28, 95% confidence interval (95% CI) [1.09, 1.51], p = 0.003) and VSGA (RR 1.41, 95% CI [1.08, 1.83], p = 0.011), compared to NNRTI-ART. Specifically, lopinavir/ritonavir (LPV/r) was associated with an increased risk of SGA (RR 1.40, 95% CI [1.18, 1.65], p = 0.003) and VSGA (RR 1.84, 95% CI [1.37, 2.45], p = 0.002), compared to efavirenz, but not compared to nevirapine. We found no evidence that any class of ART or specific "third drug" was associated with an increased risk of PTB. CONCLUSION: Our findings support the recommendation of INSTI-ART as first-line ART regimen for use in pregnant WLHIV. However, the increased risks of SGA and VGSA associated with PI-ART, compared to NNRTI-ART, may impact choice of second- and third-line ART regimens in pregnancy.Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42021248987.