ABSTRACT
BACKGROUND: Accurate HIV point of care testing is the cornerstone of prevention and treatment efforts globally, though false (both negative and positive) results are expected to occur. SETTING: We assessed the spectrum of true and false positive HIV results in a large prospective study of HIV incidence in African women using three contraceptive methods tested longitudinally in Eswatini, Kenya, South Africa, and Zambia. METHODS: HIV serologic testing was conducted quarterly using two parallel rapid HIV tests. When one or both tests were positive, additional confirmatory testing was conducted, including HIV enzyme immunoassay (EIA) and ribonucleic acid (RNA). RESULTS: 7730 women contributed 48,234 visits: true positive results occurred at 412 visits (0.9%) and false positives at 96 visits (0.2%). Of 412 women with HIV seroconversion, 10 had discordant (i.e., one negative and one positive) rapid tests and 13 had undetectable HIV RNA levels. Of 62 women with false positive rapid HIV results, most had discordant rapid testing but six (9.7%) had dually-positive rapid results and four (6.5%) had false positive or indeterminate EIA results. The positive predictive value of dual positive rapid results was 98.3%. CONCLUSION: Although the majority of rapid test results were accurate, false positive results were expected and occurred in this population of initially HIV seronegative individuals tested repeatedly and prospectively. When HIV infection occurred, not all cases had textbook laboratory results. Our findings highlight the importance of confirmatory testing, particularly for individuals undergoing repeat testing and in settings where the point prevalence is expected to be low.
ABSTRACT
Importance: Accurate assessment of gestational age (GA) is essential to good pregnancy care but often requires ultrasonography, which may not be available in low-resource settings. This study developed a deep learning artificial intelligence (AI) model to estimate GA from blind ultrasonography sweeps and incorporated it into the software of a low-cost, battery-powered device. Objective: To evaluate GA estimation accuracy of an AI-enabled ultrasonography tool when used by novice users with no prior training in sonography. Design, Setting, and Participants: This prospective diagnostic accuracy study enrolled 400 individuals with viable, single, nonanomalous, first-trimester pregnancies in Lusaka, Zambia, and Chapel Hill, North Carolina. Credentialed sonographers established the "ground truth" GA via transvaginal crown-rump length measurement. At random follow-up visits throughout gestation, including a primary evaluation window from 14 0/7 weeks' to 27 6/7 weeks' gestation, novice users obtained blind sweeps of the maternal abdomen using the AI-enabled device (index test) and credentialed sonographers performed fetal biometry with a high-specification machine (study standard). Main Outcomes and Measures: The primary outcome was the mean absolute error (MAE) of the index test and study standard, which was calculated by comparing each method's estimate to the previously established GA and considered equivalent if the difference fell within a prespecified margin of ±2 days. Results: In the primary evaluation window, the AI-enabled device met criteria for equivalence to the study standard, with an MAE (SE) of 3.2 (0.1) days vs 3.0 (0.1) days (difference, 0.2 days [95% CI, -0.1 to 0.5]). Additionally, the percentage of assessments within 7 days of the ground truth GA was comparable (90.7% for the index test vs 92.5% for the study standard). Performance was consistent in prespecified subgroups, including the Zambia and North Carolina cohorts and those with high body mass index. Conclusions and Relevance: Between 14 and 27 weeks' gestation, novice users with no prior training in ultrasonography estimated GA as accurately with the low-cost, point-of-care AI tool as credentialed sonographers performing standard biometry on high-specification machines. These findings have immediate implications for obstetrical care in low-resource settings, advancing the World Health Organization goal of ultrasonography estimation of GA for all pregnant people. Trial Registration: ClinicalTrials.gov Identifier: NCT05433519.
ABSTRACT
BACKGROUND: The Multi-Omics for Mothers and Infants consortium aims to improve birth outcomes. Preterm birth is a major obstetrical complication globally and causes significant infant and childhood morbidity and mortality. OBJECTIVE: We analyzed placental samples (basal plate, placenta or chorionic villi, and the chorionic plate) collected by the 5 Multi-Omics for Mothers and Infants sites, namely The Alliance for Maternal and Newborn Health Improvement Bangladesh, The Alliance for Maternal and Newborn Health Improvement Pakistan, The Alliance for Maternal and Newborn Health Improvement Tanzania, The Global Alliance to Prevent Prematurity and Stillbirth Bangladesh, and The Global Alliance to Prevent Prematurity and Stillbirth Zambia. The goal was to analyze the morphology and gene expression of samples collected from preterm and uncomplicated term births. STUDY DESIGN: The teams provided biopsies from 166 singleton preterm (<37 weeks' gestation) and 175 term (≥37 weeks' gestation) deliveries. The samples were fixed in formalin and paraffin embedded. Tissue sections from these samples were stained with hematoxylin and eosin and subjected to morphologic analyses. Other placental biopsies (n=35 preterm, 21 term) were flash frozen, which enabled RNA purification for bulk transcriptomics. RESULTS: The morphologic analyses revealed a surprisingly high rate of inflammation that involved the basal plate, placenta or chorionic villi, and the chorionic plate. The rate of inflammation in chorionic villus samples, likely attributable to chronic villitis, ranged from 25% (Pakistan site) to 60% (Zambia site) of cases. Leukocyte infiltration in this location vs in the basal plate or chorionic plate correlated with preterm birth. Our transcriptomic analyses identified 267 genes that were differentially expressed between placentas from preterm vs those from term births (123 upregulated, 144 downregulated). Mapping the differentially expressed genes onto single-cell RNA sequencing data from human placentas suggested that all the component cell types, either singly or in subsets, contributed to the observed dysregulation. Consistent with the histopathologic findings, gene ontology analyses highlighted the presence of leukocyte infiltration or activation and inflammatory responses in both the fetal and maternal compartments. CONCLUSION: The relationship between placental inflammation and preterm birth is appreciated in developed countries. In this study, we showed that this link also exists in developing geographies. In addition, among the participating sites, we found geographic- and population-based differences in placental inflammation and preterm birth, suggesting the importance of local factors.
ABSTRACT
Postpartum depression (PPD) affects nearly 20% of postpartum women in Sub-Saharan Africa (SSA), where HIV prevalence is high. Depression is associated with worse HIV outcomes in non-pregnant adults and mental health disorders may worsen HIV outcomes for postpartum women and their infants. PPD is effectively treated with psychosocial or pharmacologic interventions; however, few studies have evaluated the acceptability of treatment modalities in SSA. We analyzed interviews with 23 postpartum women with HIV to assess the acceptability of two depression treatments provided in the context of a randomized trial. Most participants expressed acceptability of treatment randomization and study visit procedures. Participants shared perceptions of high treatment efficacy of their assigned intervention. They reported ongoing HIV and mental health stigma in their communities and emphasized the importance of social support from clinic staff. Our findings suggest a full-scale trial of PPD treatment will be acceptable among women with HIV in Zambia.
Subject(s)
Depression, Postpartum , Depressive Disorder , HIV Infections , Adult , Female , Humans , Pregnancy , Depression/therapy , Depression, Postpartum/epidemiology , Depressive Disorder/complications , HIV Infections/complications , HIV Infections/epidemiology , HIV Infections/psychology , Postpartum Period , Treatment Outcome , Randomized Controlled Trials as TopicABSTRACT
OBJECTIVE: Low-cost devices have made obstetric sonography possible in settings where it was previously unfeasible, but ensuring quality and consistency at scale remains a challenge. In the present study, we sought to create a tool to reduce substandard fetal biometry measurement while minimizing care disruption. METHODS: We developed a deep learning artificial intelligence (AI) model to estimate gestational age (GA) in the second and third trimester from fly-to cineloops-brief videos acquired during routine ultrasound biometry-and evaluated its performance in comparison to expert sonographer measurement. We then introduced random error into fetal biometry measurements and analyzed the ability of the AI model to flag grossly inaccurate measurements such as those that might be obtained by a novice. RESULTS: The mean absolute error (MAE) of our model (±standard error) was 3.87 ± 0.07 days, compared to 4.80 ± 0.10 days for expert biometry (difference -0.92 days; 95% CI: -1.10 to -0.76). Based on simulated novice biometry with average absolute error of 7.5%, our model reliably detected cases where novice biometry differed from expert biometry by 10 days or more, with an area under the receiver operating characteristics curve of 0.93 (95% CI: 0.92, 0.95), sensitivity of 81.0% (95% CI: 77.9, 83.8), and specificity of 89.9% (95% CI: 88.1, 91.5). These results held across a range of sensitivity analyses, including where the model was provided suboptimal truncated fly-to cineloops. CONCLUSIONS: Our AI model estimated GA more accurately than expert biometry. Because fly-to cineloop videos can be obtained without any change to sonographer workflow, the model represents a no-cost guardrail that could be incorporated into both low-cost and commercial ultrasound devices to prevent reporting of most gross GA estimation errors.
Subject(s)
Deep Learning , Gestational Age , Ultrasonography, Prenatal , Humans , Ultrasonography, Prenatal/standards , Ultrasonography, Prenatal/methods , Pregnancy , Female , Quality Control , Video Recording , Biometry/methods , Pregnancy Trimester, Third , Pregnancy Trimester, SecondABSTRACT
BACKGROUND: Sputum is the most widely used sample to diagnose active tuberculosis, but many people living with HIV are unable to produce sputum. Urine, in contrast, is readily available. We hypothesised that sample availability influences the diagnostic yield of various tuberculosis tests. METHODS: In this systematic review and meta-analysis of individual participant data, we compared the diagnostic yield of point-of-care urine-based lipoarabinomannan tests with that of sputum-based nucleic acid amplification tests (NAATs) and sputum smear microscopy (SSM). We used microbiologically confirmed tuberculosis based on positive culture or NAAT from any body site as the denominator and accounted for sample provision. We searched PubMed, Web of Science, Embase, African Journals Online, and clinicaltrials.gov from database inception to Feb 24, 2022 for randomised controlled trials, cross-sectional studies, and cohort studies that assessed urine lipoarabinomannan point-of-care tests and sputum NAATs for active tuberculosis detection in participants irrespective of tuberculosis symptoms, HIV status, CD4 cell count, or study setting. We excluded studies in which recruitment was not consecutive, systematic, or random; provision of sputum or urine was an inclusion criterion; less than 30 participants were diagnosed with tuberculosis; early research assays without clearly defined cutoffs were tested; and humans were not studied. We extracted study-level data, and authors of eligible studies were invited to contribute deidentified individual participant data. The main outcomes were the tuberculosis diagnostic yields of urine lipoarabinomannan tests, sputum NAATs, and SSM. Diagnostic yields were predicted using Bayesian random-effects and mixed-effects meta-analyses. This study is registered with PROSPERO, CRD42021230337. FINDINGS: We identified 844 records, from which 20 datasets and 10â202 participants (4561 [45%] male participants and 5641 [55%] female participants) were included in the meta-analysis. All studies assessed sputum Xpert (MTB/RIF or Ultra, Cepheid, Sunnyvale, CA, USA) and urine Alere Determine TB LAM (AlereLAM, Abbott, Chicago, IL, USA) in people living with HIV aged 15 years or older. Nearly all (9957 [98%] of 10â202) participants provided urine, and 82% (8360 of 10â202) provided sputum within 2 days. In studies that enrolled unselected inpatients irrespective of tuberculosis symptoms, only 54% (1084 of 1993) of participants provided sputum, whereas 99% (1966 of 1993) provided urine. Diagnostic yield was 41% (95% credible interval [CrI] 15-66) for AlereLAM, 61% (95% Crl 25-88) for Xpert, and 32% (95% Crl 10-55) for SSM. Heterogeneity existed across studies in the diagnostic yield, influenced by CD4 cell count, tuberculosis symptoms, and clinical setting. In predefined subgroup analyses, all tests had higher yields in symptomatic participants, and AlereLAM yield was higher in those with low CD4 counts and inpatients. AlereLAM and Xpert yields were similar among inpatients in studies enrolling unselected participants who were not assessed for tuberculosis symptoms (51% vs 47%). AlereLAM and Xpert together had a yield of 71% in unselected inpatients, supporting the implementation of combined testing strategies. INTERPRETATION: AlereLAM, with its rapid turnaround time and simplicity, should be prioritised to inform tuberculosis therapy among inpatients who are HIV-positive, regardless of symptoms or CD4 cell count. The yield of sputum-based tuberculosis tests is undermined by people living with HIV who cannot produce sputum, whereas nearly all participants are able to provide urine. The strengths of this meta-analysis are its large size, the carefully harmonised denominator, and the use of Bayesian random-effects and mixed-effects models to predict yields; however, data were geographically restricted, clinically diagnosed tuberculosis was not considered in the denominator, and little information exists on strategies for obtaining sputum samples. FUNDING: FIND, the Global Alliance for Diagnostics.
Subject(s)
HIV Infections , Mycobacterium tuberculosis , Tuberculosis , Humans , Male , Female , Sputum/microbiology , Bayes Theorem , Cross-Sectional Studies , Tuberculosis/diagnosis , Tuberculosis/drug therapy , Lipopolysaccharides/urine , HIV Infections/complications , HIV Infections/diagnosis , Sensitivity and SpecificityABSTRACT
Preterm birth (PTB) is the leading cause of death in children under five, yet comprehensive studies are hindered by its multiple complex etiologies. Epidemiological associations between PTB and maternal characteristics have been previously described. This work used multiomic profiling and multivariate modeling to investigate the biological signatures of these characteristics. Maternal covariates were collected during pregnancy from 13,841 pregnant women across five sites. Plasma samples from 231 participants were analyzed to generate proteomic, metabolomic, and lipidomic datasets. Machine learning models showed robust performance for the prediction of PTB (AUROC = 0.70), time-to-delivery (r = 0.65), maternal age (r = 0.59), gravidity (r = 0.56), and BMI (r = 0.81). Time-to-delivery biological correlates included fetal-associated proteins (e.g., ALPP, AFP, and PGF) and immune proteins (e.g., PD-L1, CCL28, and LIFR). Maternal age negatively correlated with collagen COL9A1, gravidity with endothelial NOS and inflammatory chemokine CXCL13, and BMI with leptin and structural protein FABP4. These results provide an integrated view of epidemiological factors associated with PTB and identify biological signatures of clinical covariates affecting this disease.
Subject(s)
Premature Birth , Infant, Newborn , Pregnancy , Child , Humans , Female , Premature Birth/epidemiology , Developing Countries , Multiomics , Proteomics , Chemokines, CCABSTRACT
Few longitudinal studies have measured contraceptive continuation past one year in sub-Saharan Africa. We surveyed 674 women who had been randomized to receive the three-month intramuscular contraceptive injectable (DMPA-IM), levonorgestrel (LNG) implant, or copper intrauterine device (IUD) during the Evidence for Contraceptive Options and HIV Outcomes (ECHO) trial in South Africa and Zambia and were subsequently followed for two additional years to explore method continuation, reasons for discontinuation, and access to implant and IUD removal services. We also conducted in-depth qualitative interviews with 39 participants. We estimated cumulative discontinuation probabilities using Kaplan-Meier estimates and assessed factors associated with discontinuation using Cox-proportional hazards models. The LNG implant continuation rate over the maximum 44-month study period was 60 percent, while rates for the copper IUD and DMPA-IM were 52 percent and 44 percent, respectively. Reasons for method discontinuation included side effects, particularly menstrual changes, and method stock-outs. Most implant and IUD users who sought removal were able to access services; however, room for improvement exists. In this cohort originally randomized to receive a contraceptive method and attend regular study visits, implants and IUDs continued to be highly acceptable over an additional two years, but facilities should continue to ensure that insertions and removals are available as requested.
Subject(s)
Contraceptive Agents, Female , Intrauterine Devices, Copper , Female , Humans , Levonorgestrel/adverse effects , Intrauterine Devices, Copper/adverse effects , South Africa , Zambia , Contraception/methods , Contraceptive Agents, Female/adverse effectsABSTRACT
OBJECTIVE: To illustrate the difference between exposure effects and population attributable effects. METHODS: We examined the effect of mid-pregnancy short cervical length (<25 mm) on preterm birth using data from a prospective cohort of pregnant women in Lusaka, Zambia. Preterm birth was live birth or stillbirth before 37 weeks of pregnancy. For estimation, we used multivariable regression and parametric g-computation. RESULTS: Among 1409 women included in the analysis, short cervix was rare (2.4%); 13.6% of births were preterm. Exposure effect estimates were large (marginal risk ratio 2.86, 95% confidence interval [CI] 1.80-4.54), indicating that the preterm birth risk was substantially higher among women with a short cervix compared with women without a short cervix. However, the population attributable effect estimates were close to the null (risk ratio 1.06, 95% CI 1.02-1.10), indicating that an intervention to counteract the impact of short cervix on preterm birth would have minimal effect on the population risk of preterm birth. CONCLUSION: Although authors often refer to "the" effect, there are actually different types of effects, as we have illustrated here. In planning research, it is important to consider which effect to estimate to ensure that the estimate aligns with the research objective.
Subject(s)
Premature Birth , Female , Pregnancy , Infant, Newborn , Humans , Premature Birth/epidemiology , Premature Birth/etiology , Cervix Uteri/diagnostic imaging , Prospective Studies , Cervical Length Measurement , Zambia/epidemiologyABSTRACT
OBJECTIVE: To compare the performance of mid upper arm circumference (MUAC) and body mass index (BMI) for prediction of small for gestational age (SGA) in Zambia. METHODS: This is a secondary analysis of an ongoing clinical cohort that included women with a single gestation and MUAC measured before 24 weeks of pregnancy. We assessed relationships between maternal MUAC and birth weight centile using regression. The performance of MUAC and BMI to predict SGA was compared using receiver operating characteristic curves and the effect of maternal HIV was investigated in sub-group analyses. RESULTS: Of 1117 participants, 847 (75%) were HIV-negative (HIV-) and 270 (24%) were HIV-positive (HIV+). Seventy-four (7%) delivered severe SGA infants (<3rd centile), of whom 56 (76%) were HIV- and 18 (24%) were HIV+ (odds ratio [OR] 1.01, 95% confidence interval [CI] 0.58-1.75). MUAC was associated with higher birth weight centile (+1.2 centile points, 95% CI 0.7-1.6; P < 0.001); this relationship was stronger among HIV+ women (+1.7 centile points, 95% CI 0.8-2.6; P < 0.001) than HIV- women (+0.9 centile points, 95% CI 0.4-1.4; P = 0.001). The discriminatory power was similar, albeit poor (area under the curve [AUC] < 0.7), between MUAC and BMI for the prediction of SGA. In stratified analysis, MUAC and BMI showed excellent discrimination predicting severe SGA among HIV+ (AUC 0.83 and 0.81, respectively) but not among HIV- women (AUC 0.64 and 0.63, respectively). CONCLUSION: Maternal HIV infection increased the discrimination of both early pregnancy MUAC and BMI for prediction of severe SGA in Zambia. CLINICAL TRIAL NUMBER: ClinicalTrials.gov (NCT02738892).
Subject(s)
HIV Infections , Infant, Newborn, Diseases , Female , Humans , Infant , Infant, Newborn , Pregnancy , Anthropometry , Arm/anatomy & histology , Birth Weight , Fetal Growth Retardation , Gestational Age , HIV Infections/complications , ZambiaABSTRACT
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.
ABSTRACT
The IPOP trial demonstrated a reduced risk of severe small for gestational age among infants born to women with HIV who received weekly intramuscular 17 alpha-hydroxyprogesterone caproate. This secondary analysis examined the 17P treatment effect in subgroups of maternal BMI, parity, timing of antiretroviral therapy (ART) initiation, and ART regimen. We found that 17P was more effective among nulliparous women, women who started ART before pregnancy, and those taking protease inhibitors.
Subject(s)
17 alpha-Hydroxyprogesterone Caproate , HIV Infections , Premature Birth , Female , Humans , Infant , Pregnancy , 17 alpha-Hydroxyprogesterone Caproate/adverse effects , 17-alpha-Hydroxyprogesterone , Gestational Age , HIV Infections/drug therapy , Hydroxyprogesterones , Pregnant Women , ZambiaABSTRACT
INTRODUCTION: Postpartum depression (PPD) is a prevalent and debilitating disease that may affect medication adherence and thus maternal health and vertical transmission among women with HIV. We assessed the feasibility of a trial of interpersonal psychotherapy (IPT) versus antidepressant medication (ADM) to treat PPD and/or anxiety among postpartum women with HIV in Lusaka, Zambia. METHODS: Between 29 October 2019 and 8 September 2020, we pre-screened women 6-8 weeks after delivery with the Edinburgh Postnatal Depression Scale (EPDS) and diagnosed PPD or anxiety with the Mini International Neuropsychiatric Interview. Consenting participants were randomized 1:1 to up to 11 sessions of IPT or daily self-administered sertraline and followed for 24 weeks. We assessed EPDS score, Clinical Global Impression-Severity of Illness (CGI-S) and medication side effects at each visit and measured maternal HIV viral load at baseline and final study visit. Retention, visit adherence, change in EPDS, CGI-S and log viral load were compared between groups with t-tests and Wilcoxon signed rank tests; we report mean differences, relative risks and 95% confidence intervals. A participant satisfaction survey assessed trial acceptability. RESULTS: 78/80 (98%) participants were retained at the final study visit. In the context of the COVID-19 pandemic, visit adherence was greater among women allocated to ADM (9.9 visits, SD 2.2) versus IPT (8.9 visits, SD 2.4; p = 0.06). EPDS scores decreased from baseline to final visit overall, though mean change was greater in the IPT group (-13.8 points, SD 4.7) compared to the ADM group (-11.4 points, SD 5.5; p = 0.04). Both groups showed similar changes in mean log viral load from baseline to final study visit (mean difference -0.43, 95% CI -0.32, 1.18; p = 0.48). In the IPT group, viral load decreased significantly from baseline (0.9 log copies/ml, SD 1.7) to final visit (0.2 log copies/ml, SD 0.9; p = 0.01). CONCLUSIONS: This pilot study demonstrates that a trial of two forms of PPD treatment is feasible and acceptable among women with HIV in Zambia. IPT and ADM both improved measures of depression severity; however, a full-scale trial is required to determine whether treatment of PPD and anxiety improves maternal-infant HIV outcomes.
Subject(s)
Anxiety , Depression, Postpartum , HIV Infections , Antidepressive Agents/therapeutic use , Anxiety/diagnosis , Anxiety/drug therapy , Depression, Postpartum/diagnosis , Depression, Postpartum/drug therapy , Feasibility Studies , Female , HIV Infections/complications , HIV Infections/drug therapy , HIV Infections/epidemiology , Humans , Pandemics , Pilot Projects , Zambia/epidemiologyABSTRACT
A Lactobacillus-deficient, anaerobe-rich vaginal microbiome has been associated with local inflammation and spontaneous preterm birth (sPTB), but few studies have assessed this association in the setting of HIV. We performed metagenomic sequencing and inflammatory marker assays on vaginal swabs collected in pregnancy. We grouped samples into 7 metagenomic clusters (mgClust) using the non-redundant VIRGO catalogue, and derived inflammatory scores by factor analysis. Of 221 participants, median Shannon diversity index (SDI) was highest in HIV+ with detectable viral load (1.31, IQR: 0.85-1.66; p < 0.001) and HIV+ with undetectable virus (1.17, IQR: 0.51-1.66; p = 0.01) compared to HIV- (0.74, IQR: 0.35-1.26). Inflammatory scores positively correlated with SDI (+ 0.66, 95%CI 0.28, 1.03; p = 0.001), highest among anaerobe-rich mgClust2-mgClust6. HIV was associated with predominance of anaerobe-rich mgClust5 (17% vs. 6%; p = 0.02) and mgClust6 (27% vs. 11%; p = 0.002). Relative abundance of a novel Gardnerella metagenomic subspecies > 50% predicted sPTB (RR 2.6; 95%CI: 1.1, 6.4) and was higher in HIV+ (23% vs. 10%; p = 0.001). A novel Gardnerella metagenomic subspecies more abundant in women with HIV predicted sPTB. The risk of sPTB among women with HIV may be mediated by the vaginal microbiome and inflammation, suggesting potential targets for prevention.
Subject(s)
HIV Infections , Microbiota , Premature Birth , Bacteria, Anaerobic , Female , Gardnerella , HIV Infections/complications , Humans , Infant, Newborn , Inflammation/complications , Microbiota/genetics , Pregnancy , Vagina , Zambia/epidemiologyABSTRACT
Assessment of gestational age (GA) is key to provide optimal care during pregnancy. However, its accurate determination remains challenging in low- and middle-income countries, where access to obstetric ultrasound is limited. Hence, there is an urgent need to develop clinical approaches that allow accurate and inexpensive estimations of GA. We investigated the ability of urinary metabolites to predict GA at time of collection in a diverse multi-site cohort of healthy and pathological pregnancies (n = 99) using a broad-spectrum liquid chromatography coupled with mass spectrometry (LC-MS) platform. Our approach detected a myriad of steroid hormones and their derivatives including estrogens, progesterones, corticosteroids, and androgens which were associated with pregnancy progression. We developed a restricted model that predicted GA with high accuracy using three metabolites (rho = 0.87, RMSE = 1.58 weeks) that was validated in an independent cohort (n = 20). The predictions were more robust in pregnancies that went to term in comparison to pregnancies that ended prematurely. Overall, we demonstrated the feasibility of implementing urine metabolomics analysis in large-scale multi-site studies and report a predictive model of GA with a potential clinical value.
Subject(s)
Metabolomics , Ultrasonography, Prenatal , Chromatography, Liquid , Cohort Studies , Female , Gestational Age , Humans , Infant, Newborn , PregnancyABSTRACT
OBJECTIVE: To evaluate the effect of HIV co-infection on non-treponemal titers during pregnancy in women with syphilis. METHODS: This is a secondary analysis of pregnant women with syphilis in the prospective, observational Zambian Preterm Birth Prevention Study (ZAPPS). Treponemal (Treponema pallidum particle agglutination) and non-treponemal (rapid plasma reagin; RPR) testing were performed on serum biospecimens, resulting in 47 participants with serologically confirmed syphilis (27 HIV-positive, 20 HIV-negative). The primary outcome, achievement of RPR titer seroreduction during pregnancy, was analyzed by logistic regression. Secondary outcomes included overall titer reduction, seroreduction rate, serologic cure, and adverse pregnancy outcomes. RESULTS: Seroreduction of RPR titer occurred in 78% (21/27) of women with HIV versus 45% (9/20) of women without (adjusted odds ratio 4.66; 95% confidence interval [CI] 1.14 - 19.08). Overall RPR titer reduction, rate of seroreduction per week, and the proportion achieving serologic cure each trended higher among women with HIV compared with those without HIV. There was a trend toward decreased stillbirth incidence in participants achieving seroreduction (odds ratio 0.15, 95% CI 0.01-1.58). CONCLUSION: HIV co-infection in this cohort of Zambian women with syphilis was associated with greater odds of RPR titer seroreduction during pregnancy. Pregnant women with syphilis and HIV may not be at increased risk for a delayed syphilis treatment response compared with women without HIV.
Subject(s)
Coinfection , HIV Infections , Pregnancy Complications, Infectious , Premature Birth , Syphilis , Coinfection/epidemiology , Female , HIV Infections/complications , HIV Infections/epidemiology , Humans , Infant, Newborn , Pregnancy , Pregnancy Complications, Infectious/epidemiology , Pregnancy Outcome/epidemiology , Prospective Studies , Reagins , Syphilis/complications , Syphilis/epidemiology , Syphilis Serodiagnosis/methodsABSTRACT
BACKGROUND: A trial of progesterone to prevent preterm birth among HIV-infected Zambian women [Improving Pregnancy Outcomes with Progesterone (IPOP)] found no treatment effect, but the risk of the primary outcome was among the lowest ever documented in women with HIV. In this secondary analysis, we compare the risks of preterm birth (<37 weeks), stillbirth, and a composite primary outcome comprising the two in IPOP versus an observational pregnancy cohort [Zambian Preterm Birth Prevention Study (ZAPPS)] in Zambia, to evaluate reasons for the low risk in IPOP. METHODS: Both studies enrolled women before 24 gestational weeks, during August 2015-September 2017 (ZAPPS) and February 2018-January 2020 (IPOP). We used linear probability and log-binomial regression to estimate risk differences and risk ratios (RR), before and after restriction and standardization with inverse probability weights. RESULTS: The unadjusted risk of composite outcome was 18% in ZAPPS (N = 1450) and 9% in IPOP (N = 791) (RR = 2.0; 95% CI = 1.6, 2.6). After restricting and standardizing the ZAPPS cohort to the distribution of IPOP baseline characteristics, the risk remained higher in ZAPPS (RR = 1.6; 95% CI = 1.0, 2.4). The lower risk of preterm/stillbirth in IPOP was only partially explained by measured risk factors. CONCLUSIONS: Possible benefits in IPOP of additional monetary reimbursement, more frequent visits, and group-based care warrant further investigation.
Subject(s)
HIV Infections , Pregnancy Complications , Premature Birth , Female , HIV Infections/drug therapy , HIV Infections/epidemiology , Humans , Infant, Newborn , Pregnancy , Pregnancy Outcome/epidemiology , Pregnant Women , Premature Birth/epidemiology , Premature Birth/prevention & control , Zambia/epidemiologyABSTRACT
Background: Each year, nearly 300,000 women and 5 million fetuses or neonates die during childbirth or shortly thereafter, a burden concentrated disproportionately in low- and middle-income countries. Identifying women and their fetuses at risk for intrapartum-related morbidity and death could facilitate early intervention. Methods: The Limiting Adverse Birth Outcomes in Resource-Limited Settings (LABOR) Study is a multi-country, prospective, observational cohort designed to exhaustively document the course and outcomes of labor, delivery, and the immediate postpartum period in settings where adverse outcomes are frequent. The study is conducted at four hospitals across three countries in Ghana, India, and Zambia. We will enroll approximately 12,000 women at presentation to the hospital for delivery and follow them and their fetuses/newborns throughout their labor and delivery course, postpartum hospitalization, and up to 42 days thereafter. The co-primary outcomes are composites of maternal (death, hemorrhage, hypertensive disorders, infection) and fetal/neonatal adverse events (death, encephalopathy, sepsis) that may be attributed to the intrapartum period. The study collects extensive physiologic data through the use of physiologic sensors and employs medical scribes to document examination findings, diagnoses, medications, and other interventions in real time. Discussion: The goal of this research is to produce a large, sharable dataset that can be used to build statistical algorithms to prospectively stratify parturients according to their risk of adverse outcomes. We anticipate this research will inform the development of new tools to reduce peripartum morbidity and mortality in low-resource settings.
ABSTRACT
BACKGROUND: Ultrasound is indispensable to gestational age estimation and thus to quality obstetrical care, yet high equipment cost and the need for trained sonographers limit its use in low-resource settings. METHODS: From September 2018 through June 2021, we recruited 4695 pregnant volunteers in North Carolina and Zambia and obtained blind ultrasound sweeps (cineloop videos) of the gravid abdomen alongside standard fetal biometry. We trained a neural network to estimate gestational age from the sweeps and, in three test data sets, assessed the performance of the artificial intelligence (AI) model and biometry against previously established gestational age. RESULTS: In our main test set, the mean absolute error (MAE) (±SE) was 3.9±0.12 days for the model versus 4.7±0.15 days for biometry (difference, -0.8 days; 95% confidence interval [CI], -1.1 to -0.5; P<0.001). The results were similar in North Carolina (difference, -0.6 days; 95% CI, -0.9 to -0.2) and Zambia (-1.0 days; 95% CI, -1.5 to -0.5). Findings were supported in the test set of women who conceived by in vitro fertilization (MAE of 2.8±0.28 vs. 3.6±0.53 days for the model vs. biometry; difference, -0.8 days; 95% CI, -1.7 to 0.2) and in the set of women from whom sweeps were collected by untrained users with low-cost, battery-powered devices (MAE of 4.9±0.29 vs. 5.4±0.28 days for the model vs. biometry; difference, -0.6; 95% CI, -1.3 to 0.1). CONCLUSIONS: When provided blindly obtained ultrasound sweeps of the gravid abdomen, our AI model estimated gestational age with accuracy similar to that of trained sonographers conducting standard fetal biometry. Model performance appears to extend to blind sweeps collected by untrained providers in Zambia using low-cost devices. (Funded by the Bill and Melinda Gates Foundation.).