Comprehensive pregnancy monitoring with a network of wireless, soft, and flexible sensors in high- and low-resource health settings.

Vital signs monitoring is a fundamental component of ensuring the health and safety of women and newborns during pregnancy, labor, and childbirth. This monitoring is often the first step in early detection of pregnancy abnormalities, providing an opportunity for prompt, effective intervention to prevent maternal and neonatal morbidity and mortality. Contemporary pregnancy monitoring systems require numerous devices wired to large base units; at least five separate devices with distinct user interfaces are commonly used to detect uterine contractility, maternal blood oxygenation, temperature, heart rate, blood pressure, and fetal heart rate. Current monitoring technologies are expensive and complex with implementation challenges in low-resource settings where maternal morbidity and mortality is the greatest. We present an integrated monitoring platform leveraging advanced flexible electronics, wireless connectivity, and compatibility with a wide range of low-cost mobile devices. Three flexible, soft, and low-profile sensors offer comprehensive vital signs monitoring for both women and fetuses with time-synchronized operation, including advanced parameters such as continuous cuffless blood pressure, electrohysterography-derived uterine monitoring, and automated body position classification. Successful field trials of pregnant women between 25 and 41 wk of gestation in both high-resource settings (n = 91) and low-resource settings (n = 485) demonstrate the system's performance, usability, and safety.

Diagnostic Accuracy of an Integrated AI Tool to Estimate Gestational Age From Blind Ultrasound Sweeps.

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.

Data-driven quality improvement in low-and middle-income country health systems: lessons from seven years of implementation experience across Mozambique, Rwanda, and Zambia.

BACKGROUND: Well-functioning health systems need to utilize data at all levels, from the provider, to local and national-level decision makers, in order to make evidence-based and needed adjustments to improve the quality of care provided. Over the last 7 years, the Doris Duke Charitable Foundation's African Health Initiative funded health systems strengthening projects at the facility, district, and/or provincial level to improve population health. Increasing data-driven decision making was a common strategy in Mozambique, Rwanda and Zambia. This paper describes the similar and divergent approaches to increase data-driven quality of care improvements (QI) and implementation challenge and opportunities encountered in these three countries. METHODS: Eight semi-structured in-depth interviews (IDIs) were administered to program staff working in each country. IDIs for this paper included principal investigators of each project, key program implementers (medically-trained support staff, data managers and statisticians, and country directors), as well as Ministry of Health counterparts. IDI data were collected through field notes; interviews were not audio recorded. Data were analyzed using thematic analysis but no systematic coding was conducted. IDIs were supplemented through donor report abstractions, a structured questionnaire, one-on-one phone calls, and email exchanges with country program leaders to clarify and expand on key themes emerging from IDIs. RESULTS: Project successes ranged from over 450 collaborative action-plans developed, implemented, and evaluated in Mozambique, to an increase from <10% to >80% of basic clinical protocols followed in intervention facilities in rural Zambia, and a shift from a lack of awareness of health data among health system staff to collaborative ownership of data and using data to drive change in Rwanda. CONCLUSION: Based on common successes across the country experiences, we recommend future data-driven QI interventions begin with data quality assessments to promote that rapid health system improvement is possible, ensure confidence in available data, serve as the first step in data-driven targeted improvements, and improve staff data analysis and visualization skills. Explicit Ministry of Health collaborative engagement can ensure performance review is collaborative and internally-driven rather than viewed as an external "audit."

Hypertension management in rural primary care facilities in Zambia: a mixed methods study.

BACKGROUND: Improved primary health care is needed in developing countries to effectively manage the growing burden of hypertension. Our objective was to evaluate hypertension management in Zambian rural primary care clinics using process and outcome indicators to assess the screening, monitoring, treatment and control of high blood pressure. METHODS: Better Health Outcomes through Mentoring and Assessment (BHOMA) is a 5-year, randomized stepped-wedge trial of improved clinical service delivery underway in 46 rural Zambian clinics. Clinical data were collected as part of routine patient care from an electronic medical record system, and reviewed for site performance over time according to hypertension related indicators: screening (blood pressure measurement), management (recorded diagnosis, physical exam or urinalysis), treatment (on medication), and control. Quantitative data was used to develop guides for qualitative in-depth interviews, conducted with health care providers at a proportional sample of half (20) of clinics. Qualitative data was iteratively analyzed for thematic content. RESULTS: From January 2011 to December 2014, 318,380 visits to 46 primary care clinics by adults aged ≥ 25 years with blood pressure measurements were included. Blood pressure measurement at vital sign screening was initially high at 89.1% overall (range: 70.1-100%), but decreased to 62.1% (range: 0-100%) by 48 months after intervention start. The majority of hypertensive patients made only one visit to the clinics (57.8%). Out of 9022 patients with at least two visits with an elevated blood pressure, only 49.3% had a chart recorded hypertension diagnosis. Process indicators for monitoring hypertension were <10% and did not improve with time. In in-depth interviews, antihypertensive medication shortages were common, with 15/20 clinics reporting hydrochlorothiazide-amiloride stockouts. Principal challenges in hypertension management included 1) equipment and personnel shortages, 2) provider belief that multiple visits were needed before official management, 3) medication stock-outs, leading to improper prescriptions and 4) poor patient visit attendance. CONCLUSIONS: Our findings suggest that numerous barriers stand in the way of hypertension diagnosis and management in Zambian primary health facilities. Future work should focus on performance indicator development and validation in low resource contexts, to facilitate regular and systematic data review to improve patient outcomes. TRIAL REGISTRATION: ClinicalTrials.gov, Identifier NCT01942278 . Date of Registration: September 2013.

Prevalence of hypertension and its treatment among adults presenting to primary health clinics in rural Zambia: analysis of an observational database.

BACKGROUND: Hypertension constitutes a growing burden of illness in developing countries like Zambia. Adequately screening and treating hypertension could greatly reduce the complications of stroke and coronary disease. Our objective was to determine the prevalence of hypertension and identify current treatment practices among adult patients presenting for routine care to rural health facilities in the Better Health Outcomes through Mentoring and Assessments (BHOMA) project. METHODS: We conducted a retrospective analysis of routinely collected clinical data from 46 rural government clinics in Zambia. Our analysis cohort comprised patients ≥ 25 years with recorded blood pressure measurements, who sought care at primary health centers. Consistent with prior research, in our primary analysis, we only included data from first visits. Hypertension was defined as a systolic blood pressure ≥140 mmHg, or diastolic blood pressure ≥90 mmHg, or reported use of antihypertensive medication. A sensitivity analysis was performed using median blood pressure for individuals with multiple visits. RESULTS AND DISCUSSION: From January 2011 to December 2014, 116,130 first visits by adult patients met eligibility criteria. The crude prevalence of hypertension by onsite measurement or reported use of antihypertensive medication was 23.1% [95% CI: 22.8-23.3] (23.6% in females, 22.3% in males). The age standardized prevalence of hypertension across participating sites was 28.0 [95% CI: 27.7-28.3] (29.7% in females, 25.8% in males). Sensitivity analysis revealed a similar prevalence using data from all visits. Only 5.6% of patients had a diagnosis of hypertension documented in their medical record. Among patients with hypertension, only 18.0% had any antihypertensive drug prescribed, with nifedipine (8.9%), furosemide (8.3%), and propranolol (2.4%) as the most common. CONCLUSIONS: Age standardized prevalence of hypertension in rural primary health clinics in Zambia was high compared to other studies in rural Africa; however, we diagnosed hypertension with only one measurement and this may have biased our findings. Future efforts to improve hypertension control should focus on population preventive care and primary healthcare provider education on individual management.

A mobile phone-based, community health worker program for referral, follow-up, and service outreach in rural Zambia: outcomes and overview.

BACKGROUND: Mobile health (m-health) utilizes widespread access to mobile phone technologies to expand health services. Community health workers (CHWs) provide first-level contact with health facilities; combining CHW efforts with m-health may be an avenue for improving primary care services. As part of a primary care improvement project, a pilot CHW program was developed using a mobile phone-based application for outreach, referral, and follow-up between the clinic and community in rural Zambia. MATERIALS AND METHODS: The program was implemented at six primary care sites. Computers were installed at clinics for data entry, and data were transmitted to central servers. In the field, using a mobile phone to send data and receive follow-up requests, CHWs conducted household health surveillance visits, referred individuals to clinic, and followed up clinic patients. RESULTS: From January to April 2011, 24 CHWs surveyed 6,197 households with 33,304 inhabitants. Of 15,539 clinic visits, 1,173 (8%) had a follow-up visit indicated and transmitted via a mobile phone to designated CHWs. CHWs performed one or more follow-ups on 74% (n=871) of active requests and obtained outcomes on 63% (n=741). From all community visits combined, CHWs referred 840 individuals to a clinic. CONCLUSIONS: CHWs completed all planned aspects of surveillance and outreach, demonstrating feasibility. Components of this pilot project may aid clinical care in rural settings and have potential for epidemiologic and health system applications. Thus, m-health has the potential to improve service outreach, guide activities, and facilitate data collection in Zambia.

Deep learning to estimate gestational age from fly-to cineloop videos: A novel approach to ultrasound quality control.

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.

Protocol-driven primary care and community linkages to improve population health in rural Zambia: the Better Health Outcomes through Mentoring and Assessment (BHOMA) project.

INTRODUCTION: Zambia's under-resourced public health system will not be able to deliver on its health-related Millennium Development Goals without a substantial acceleration in mortality reduction. Reducing mortality will depend not only upon increasing access to health care but also upon improving the quality of care that is delivered. Our project proposes to improve the quality of clinical care and to improve utilization of that care, through a targeted quality improvement (QI) intervention delivered at the facility and community level. DESCRIPTION OF IMPLEMENTATION: The project is being carried out 42 primary health care facilities that serve a largely rural population of more than 450,000 in Zambia's Lusaka Province. We have deployed six QI teams to implement consensus clinical protocols, forms, and systems at each site. The QI teams define new clinical quality expectations and provide tools needed to deliver on those expectations. They also monitor the care that is provided and mentor facility staff to improve care quality. We also engage community health workers to actively refer and follow up patients. EVALUATION DESIGN: Project implementation occurs over a period of four years in a stepped expansion to six randomly selected new facilities every three months. Three annual household surveys will determine population estimates of age-standardized mortality and under-5 mortality in each community before, during, and after implementation. Surveys will also provide measures of childhood vaccine coverage, pregnancy care utilization, and general adult health. Health facility surveys will assess coverage of primary health interventions and measures of health system effectiveness. DISCUSSION: The patient-provider interaction is an important interface where the community and the health system meet. Our project aims to reduce population mortality by substantially improving this interaction. Our success will hinge upon the ability of mentoring and continuous QI to improve clinical service delivery. It will also be critical that once the quality of services improves, increasing proportions of the population will recognize their value and begin to utilize them.

AI Estimation of Gestational Age from Blind Ultrasound Sweeps in Low-Resource Settings.

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.).

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.

Integration of HIV Prevention With Sexual and Reproductive Health Services: Evidence for Contraceptive Options and HIV Outcomes Study Experience of Integrating Oral Pre-exposure HIV Prophylaxis in Family Planning Services in Lusaka, Zambia.

The WHO guideline on the integration of family planning (FP) and pre-exposure HIV prophylaxis (PrEP) to enhance the health of women and adolescent girls is reflected in the Zambia Consolidated Guidelines for Treatment and Prevention of HIV Infection, 2020. There is however a dearth of data on the integration of PrEP and FP in Zambia. We describe the integration of oral PrEP in FP services using the Evidence for Contraceptive Options and HIV Outcomes (ECHO) study experience at Kamwala District Health Center in Lusaka, Zambia. The provision of oral PrEP at Kamwala started in October 2017, lasting for ~11 months, and utilized the model where initial processes to offer PrEP were on-site followed by off-site referral to laboratory and PrEP provider services. The characteristics of 658 women who enrolled in ECHO at Kamwala are representative of women accessing FP services in Lusaka. About 644 of the enrollees were offered oral PrEP. The proportion of women accepting PrEP was low at 1.08% and the proportion of study visits at which PrEP was requested was also low at 0.57%. Those who accepted PrEP were above 20 years old, married, with at least primary education, sexual behavior, and risk comparable to decliners. The ECHO study experience indicates that the setup and integration of oral PrEP and FP services are feasible in the setting. However, uptake of PrEP was very low. Possible contributory factors were as follows: (1) timing of introduction of PrEP midway in the study, (2) PrEP being a new intervention, (3) challenges of autonomy of young women to include a daily pill into their lives and anticipated challenges to adherence because of fear of adverse events, (4) possible underdetermined risk due to use of an unvalidated risk assessment tool and assessment by health care provider vs. self-assessment, and (5) extra layer of challenges to negotiate due to needing for off-site referrals. Following these findings, we conclude that further research through demonstration projects of integration of oral PrEP and FP may provide solutions to low uptake. This information is critical for scaling up of integration HIV prevention services and sexual and reproductive health (SRH) services.

Weekly 17 alpha-hydroxyprogesterone caproate to prevent preterm birth among women living with HIV: a randomised, double-blind, placebo-controlled trial.

BACKGROUND: Women with HIV face an increased risk of preterm birth. 17 alpha-hydroxyprogesterone caproate (17P) has been shown in some trials to reduce early delivery among women with a history of spontaneous preterm birth. We investigated whether 17P would reduce this risk among women with HIV. METHODS: We did a randomised, double-blind, placebo-controlled trial in pregnant women with HIV at the University Teaching Hospital and Kamwala District Health Centre in Lusaka, Zambia. Eligible patients were women aged 18 years or older with confirmed HIV-1 infection, viable intrauterine singleton pregnancy at less than 24 weeks of gestation, and were receiving or intending to commence antiretroviral therapy during pregnancy. Exclusion criteria were major uterine or fetal anomaly; planned or in situ cervical cerclage; evidence of threatened miscarriage, preterm labour, or ruptured membranes at screening; medical contraindication to 17P; previous participation in the trial; or history of spontaneous preterm birth. Eligible participants provided written informed consent and were randomly assigned (1:1) to receive 250 mg intramuscular 17P or placebo once per week, starting between 16 and 24 weeks of gestation until delivery, stillbirth, or reaching term (37 weeks). Participants and study staff were masked to assignment, except for pharmacy staff who did random assignment and prepared injections but did not interact with participants. The primary outcome was a composite of delivery before 37 weeks or stillbirth at any gestational age. Patients attended weekly visits for study drug injections and antenatal care. We estimated the absolute and relative difference in risk of the primary outcome and safety events between treatment groups by intention to treat. This trial is registered with ClinicalTrials.gov, NCT03297216, and is complete. FINDINGS: Between Feb 7, 2018 and Jan 13, 2020, we assessed 1042 women for inclusion into the study. 242 women were excluded after additional assessments, and 800 eligible patients were enrolled and randomly assigned to receive intramuscular 17P (n=399) or placebo (n=401). Baseline characteristics were similar between groups. Adherence to study drug injections was 98% in both groups, no patients were lost to follow-up, and the final post-partum visit was on Aug 6, 2020. 36 (9%) of 399 participants assigned to 17P had preterm birth or stillbirth, compared with 36 (9%) of 401 patients assigned to placebo (risk difference 0·1, 95% CI -3·9 to 4·0; relative risk 1·0, 95% CI 0·6 to 1·6; p=0·98). Intervention-related adverse events were reported by 140 (18%) of 800 participants and occurred in similar proportions in both randomisation groups. No serious adverse events were reported. INTERPRETATION: Although 17P seems to be safe and acceptable to participants, available data do not support the use of the drug to prevent preterm birth among women whose risk derives solely from HIV infection. The low risk of preterm birth in both randomisation groups warrants further investigation. FUNDING: US National Institutes of Health and the Bill and Melinda Gates Foundation.

Field performance evaluation of dual rapid HIV and syphilis tests in three antenatal care clinics in Zambia.

This cross-sectional study of 3212 pregnant women assessed the field performance, acceptability, and feasibility of two dual HIV/syphilis rapid diagnostic tests, the Chembio DPP HIV-syphilis Assay and the SD Bioline HIV/syphilis Duo in antenatal clinics. Sensitivity and specificity for HIV and syphilis were calculated compared to the rapid Determine HIV-1/2 with Uni-Gold to confirm positive results for HIV and the Treponema pallidum particle agglutination assay for syphilis. RPR titers ≥1:4 were used to define active syphilis detection. Acceptability and feasibility were assessed using self-reported questionnaires. For Chembio, the HIV sensitivity was 90.6% (95%CI = 87.4, 93.0) and specificity was 97.2% (95%CI = 96.2, 97.8); syphilis sensitivity was 68.6% (95%CI = 61.9, 74.6) and specificity was 98.5% (95%CI = 97.8, 98.9). For SD Bioline, HIV sensitivity was 89.4% (95%CI = 86.1, 92.0) and specificity was 96.3% (95%CI = 95.3, 97.1); syphilis sensitivity was 66.2% (95%CI = 59.4, 72.4) and specificity was 97.2% (95%CI = 96.4, 97.9). Using the reference for active syphilis, syphilis sensitivity was 84.7% (95%CI = 76.1, 90.6) for Chembio and 81.6% (95%CI = 72.7, 88.1) for SD Bioline. Both rapid diagnostic tests were assessed as highly acceptable and feasible. In a field setting, the performance of both rapid diagnostic tests was comparable to other published field evaluations and each was rated highly acceptable and feasible. These findings can be used to guide further research and proposed scale up in antenatal clinic settings.

Adverse birth outcomes and their clinical phenotypes in an urban Zambian cohort.

Background: Few cohort studies of pregnancy in sub-Saharan Africa use rigorous gestational age dating and clinical phenotyping. As a result, incidence and risk factors of adverse birth outcomes are inadequately characterized. Methods: The Zambian Preterm Birth Prevention Study (ZAPPS) is a prospective observational cohort established to investigate adverse birth outcomes at a referral hospital in urban Lusaka. This report describes ZAPPS phase I, enrolled August 2015 to September 2017. Women were followed through pregnancy and 42 days postpartum. At delivery, study staff assessed neonatal vital status, birthweight, and sex, and assigned a delivery phenotype. Primary outcomes were: (1) preterm birth (PTB; delivery <37 weeks), (2) small-for-gestational-age (SGA; <10 th percentile weight-for-age at birth), and (3) stillbirth (SB; delivery of an infant without signs of life). Results: ZAPPS phase I enrolled 1450 women with median age 27 years (IQR 23-32). Most participants (68%) were multiparous, of whom 41% reported a prior PTB and 14% reported a prior stillbirth. Twins were present in 3% of pregnancies, 3% of women had short cervix (<25mm), 24% of women were HIV seropositive, and 5% were syphilis seropositive. Of 1216 (84%) retained at delivery, 15% were preterm, 18% small-for-gestational-age, and 4% stillborn. PTB risk was higher with prior PTB (aRR 1.88; 95%CI 1.32-2.68), short cervix (aRR 2.62; 95%CI 1.68-4.09), twins (aRR 5.22; 95%CI 3.67-7.43), and antenatal hypertension (aRR 2.04; 95%CI 1.43-2.91). SGA risk was higher with twins (aRR 2.75; 95%CI 1.81-4.18) and antenatal hypertension (aRR 1.62; 95%CI 1.16-2.26). SB risk was higher with short cervix (aRR 6.42; 95%CI 2.56-16.1). Conclusio ns: This study confirms high rates of PTB, SGA, and SB among pregnant women in Lusaka, Zambia. Accurate gestational age dating and careful ascertainment of delivery data are critical to understanding the scope of adverse birth outcomes in low-resource settings.

The Zambian Preterm Birth Prevention Study (ZAPPS): Cohort characteristics at enrollment.

Background:Sub-Saharan Africa bears a disproportionate burden of preterm birth and other adverse outcomes. A better understanding of the demographic, clinical, and biologic underpinnings of these adverse outcomes is urgently needed to plan interventions and inform new discovery.  Methods:The Zambian Preterm Birth Prevention Study (ZAPPS) is a prospective observational cohort established at the Women and Newborn Hospital (WNH) in Lusaka, Zambia. We recruit pregnant women from district health centers and the WNH and offer ultrasound examination to determine eligibility. Participants receive routine obstetrical care, lab testing, midtrimester cervical length measurement, and serial fetal growth monitoring. At delivery, we assess gestational age, birthweight, vital status, and sex and assign a delivery phenotype. We collect blood, urine, and vaginal swab specimens at scheduled visits and store them in an on-site biorepository. In September 2017, enrollment of the ZAPPS Phase 1 - the subject of this report - was completed. Phase 2 - which is limited to HIV-uninfected women - reopened in January 2018.  Results:Between August 2015 and September 2017, we screened 1784 women, of whom 1450 (81.2%) met inclusion criteria and were enrolled. The median age at enrollment was 27 years (IQR 23-32) and thee median gestational age was 16 weeks (IQR 13-18). Among parous women (N=866; 64%), 21% (N=182) reported a prior miscarriage, 49% (N=424) reported a prior preterm birth, and 13% (N=116) reported a prior stillbirth. The HIV seroprevalence was 24%. Discussion:We have established a large cohort of pregnant women and newborns at the WHN to characterize the determinants of adverse birth outcomes in Lusaka, Zambia. Our overarching goal is to elucidate biological mechanisms in an effort to identify new strategies for early detection and prevention of adverse outcomes. We hope that findings from this cohort will help guide future studies, clinical care, and policy.