Missing data and missed infections: investigating racial and ethnic disparities in SARS-CoV-2 testing and infection rates in Holyoke, Massachusetts.

Routinely collected testing data have been a vital resource for public health response during the COVID-19 pandemic and have revealed the extent to which Black and Hispanic persons have borne a disproportionate burden of SARS-CoV-2 infections and hospitalizations in the United States. However, missing race and ethnicity data and missed infections due to testing disparities limit the interpretation of testing data and obscure the true toll of the pandemic. We investigated potential bias arising from these 2 types of missing data through a case study carried out in Holyoke, Massachusetts, during the prevaccination phase of the pandemic. First, we estimated SARS-CoV-2 testing and case rates by race and ethnicity, imputing missing data using a joint modeling approach. We then investigated disparities in SARS-CoV-2 reported case rates and missed infections by comparing case rate estimates with estimates derived from a COVID-19 seroprevalence survey. Compared with the non-Hispanic White population, we found that the Hispanic population had similar testing rates (476 tested per 1000 vs 480 per 1000) but twice the case rate (8.1% vs 3.7%). We found evidence of inequitable testing, with a higher rate of missed infections in the Hispanic population than in the non-Hispanic White population (79 infections missed per 1000 vs 60 missed per 1000).

Discrete glucose profiles identified using continuous glucose monitoring data and their association with adverse pregnancy outcomes.

BACKGROUND: Continuous glucose monitoring has facilitated the evaluation of dynamic changes in glucose throughout the day and their effect on fetal growth abnormalities in pregnancy. However, studies of multiple continuous glucose monitoring metrics combined and their association with other adverse pregnancy outcomes are limited. OBJECTIVE: This study aimed to (1) use machine learning techniques to identify discrete glucose profiles based on weekly continuous glucose monitoring metrics in pregnant individuals with pregestational diabetes mellitus and (2) investigate their association with adverse pregnancy outcomes. STUDY DESIGN: This study analyzed data from a retrospective cohort study of pregnant patients with type 1 or 2 diabetes mellitus who used Dexcom G6 continuous glucose monitoring and delivered a nonanomalous, singleton pregnancy at a tertiary center between 2019 and 2023. Continuous glucose monitoring data were collapsed into 39 weekly glycemic measures related to centrality, spread, excursions, and circadian cycle patterns. Principal component analysis and k-means clustering were used to identify 4 discrete groups, and patients were assigned to the group that best represented their continuous glucose monitoring patterns during pregnancy. Finally, the association between glucose profile groups and outcomes (preterm birth, cesarean delivery, preeclampsia, large-for-gestational-age neonate, neonatal hypoglycemia, and neonatal intensive care unit admission) was estimated using multivariate logistic regression adjusted for diabetes mellitus type, maternal age, insurance, continuous glucose monitoring use before pregnancy, and parity. RESULTS: Of 177 included patients, 90 (50.8%) had type 1 diabetes mellitus, and 85 (48.3%) had type 2 diabetes mellitus. This study identified 4 glucose profiles: (1) well controlled; (2) suboptimally controlled with high variability, fasting hypoglycemia, and daytime hyperglycemia; (3) suboptimally controlled with minimal circadian variation; and (4) poorly controlled with peak hyperglycemia overnight. Compared with the well-controlled profile, the suboptimally controlled profile with high variability had higher odds of a large-for-gestational-age neonate (adjusted odds ratio, 3.34; 95% confidence interval, 1.15-9.89). The suboptimally controlled with minimal circadian variation profile had higher odds of preterm birth (adjusted odds ratio, 2.59; 95% confidence interval, 1.10-6.24), cesarean delivery (adjusted odds ratio, 2.76; 95% confidence interval, 1.09-7.46), and neonatal intensive care unit admission (adjusted odds ratio, 4.08; 95% confidence interval, 1.58-11.40). The poorly controlled profile with peak hyperglycemia overnight had higher odds of preeclampsia (adjusted odds ratio, 2.54; 95% confidence interval, 1.02-6.52), large-for-gestational-age neonate (adjusted odds ratio, 3.72; 95% confidence interval, 1.37-10.4), neonatal hypoglycemia (adjusted odds ratio, 3.53; 95% confidence interval, 1.37-9.71), and neonatal intensive care unit admission (adjusted odds ratio, 3.15; 95% confidence interval, 1.20-9.09). CONCLUSION: Discrete glucose profiles of pregnant individuals with pregestational diabetes mellitus were identified through joint consideration of multiple continuous glucose monitoring metrics. Prolonged exposure to maternal hyperglycemia may be associated with a higher risk of adverse pregnancy outcomes than suboptimal glycemic control characterized by high glucose variability and intermittent hyperglycemia.

Are populations of postpartum women differentially served by community health worker programs: an observational cohort study from Zanzibar, Tanzania.

BACKGROUND: Although community health worker (CHW) programs focus on improving access to healthcare, some individuals may not receive the intended quality or quantity of an intervention. The objective of this research was to examine if certain populations of pregnant women differentially experience the implementation of a community health worker-led maternal health intervention in Zanzibar. METHODS: We included pregnant women enrolled in the Safer Deliveries (Uzazi Salama) program, which operated in 10 of 11 districts in Zanzibar, Tanzania between January 1, 2017, and June 19, 2019 (N = 33,914). The outcomes of interest were receipt of the entire postpartum intervention (three CHW visits) and time to first postpartum CHW visit (days). Visits by CHWs were done at the women's home, however, a telehealth option existed for women who were unable to be reached in-person. We conducted statistical tests to investigate the bivariate associations between our outcomes and each demographic and health characteristic. We used multivariate logistic regression to estimate the relationships between covariates and the outcomes and multivariate linear regression to estimate the association between covariates and the average time until first postpartum visit. RESULTS: Higher parity (OR = 0.85; P = 0.014; 95%CI: 0.75-0.97), unknown or unreported HIV status (OR = 0.64; p < 0.001; 95%CI: 0.53-0.78), and receipt of phone consultations (OR = 0.77; p < 0.001; 95%CI: 0.69-0.87) were associated with a lower odds of receiving all postpartum visits. Similarly, women with an unknown or unreported HIV status (estimated mean difference of 1.81 days; p < 0.001; 95%CI: 1.03-2.59) and those who received a phone consultation (estimated mean difference of 0.83 days; p < 0.001; 95%CI: 0.43-1.23), on average, experienced delays to first visit. In addition, current delivery at a referral hospital was associated with lower odds of receiving a postpartum visit and longer time to first visit compared to delivery at home, cottage hospital, PHCU + , or district hospital. Women from all other districts received their first visit earlier than women from Kaskazini B. There were no differences in the odds of receiving the entire postpartum intervention by sociodemographic variables, including age, education, and poverty assessment indicators. CONCLUSION: The results indicate no differences in intervention contact across wealth and education levels, suggesting that the program is effectively reaching women regardless of SES. However, women with other characteristics (e.g., higher parity, unknown or unreported HIV status) had lower odds of receiving the complete intervention. Overall, this work generates knowledge on existing disparities in intervention coverage and enables future programs to develop approaches to achieve equity in health care utilization and outcomes.

Evaluation of the implementation of a community health worker-led COVID-19 contact tracing intervention in Chiapas, Mexico, from March 2020 to December 2021.

BACKGROUND: Mexico is one of the countries with the greatest excess death due to COVID-19. Chiapas, the poorest state in the country, has been particularly affected. Faced with an exacerbated shortage of health professionals, medical supplies, and infrastructure to respond to the pandemic, the non-governmental organization Compañeros En Salud (CES) implemented a COVID-19 infection prevention and control program to limit the impact of the pandemic in the region. We evaluated CES's implementation of a community health worker (CHW)-led contact tracing intervention in eight rural communities in Chiapas. METHODS: Our retrospective observational study used operational data collected during the contract tracing intervention from March 2020 to December 2021. We evaluated three outcomes: contact tracing coverage, defined as the proportion of named contacts that were located by CHWs, successful completion of contact tracing, and incidence of suspected COVID-19 among contacts. We described how these outcomes changed over time as the intervention evolved. In addition, we assessed associations between these three main outcomes and demographic characteristics of contacts and intervention period (pre vs. post March 2021) using univariate and multivariate logistic regression. RESULTS: From a roster of 2,177 named contacts, 1,187 (54.5%) received at least one home visit by a CHW and 560 (25.7%) had successful completion of contact tracing according to intervention guidelines. Of 560 contacts with complete contact tracing, 93 (16.6%) became suspected COVID-19 cases. We observed significant associations between sex and coverage (p = 0.006), sex and complete contact tracing (p = 0.049), community of residence and both coverage and complete contact tracing (p < 0.001), and intervention period and both coverage and complete contact tracing (p < 0.001). CONCLUSIONS: Our analysis highlights the promises and the challenges of implementing CHW-led COVID-19 contact tracing programs. To optimize implementation, we recommend using digital tools for data collection with a human-centered design, conducting regular data quality assessments, providing CHWs with sufficient technical knowledge of the data collection system, supervising CHWs to ensure contact tracing guidelines are followed, involving communities in the design and implementation of the intervention, and addressing community member needs and concerns surrounding stigmatization arising from lack of privacy.

Childhood immunization during the COVID-19 pandemic: experiences in Haiti, Lesotho, Liberia and Malawi.

OBJECTIVE: To examine changes in vaccination of children younger than 1 year during the coronavirus disease 2019 (COVID-19) pandemic (March 2020-August 2021) in Haiti, Lesotho, Liberia and Malawi. METHODS: We used data from health management information systems on vaccination of children aged 12 months or younger in districts supported by Partners In Health. We used data from January 2016 to February 2020 and a linear model with negative binomial distribution to estimate the expected immunization counts for March 2020-August 2021 with 95% prediction intervals, assuming no pandemic. We compared these expected levels with observed values and estimated the immunization deficits or excesses during the pandemic months. FINDINGS: Baseline vaccination counts varied substantially by country, with Lesotho having the lowest count and Haiti the highest. We observed declines in vaccination administration early in the COVID-19 pandemic in Haiti, Lesotho and Liberia. Continued declines largely corresponded to high rates of COVID-19 infection and discrete stock-outs. By August 2021, vaccination levels had returned to close to or above expected levels in Haiti, Liberia and Lesotho; in Malawi levels remained below expected. CONCLUSION: Patterns of childhood immunization coverage varied by country over the course of the pandemic, with significantly lower than expected vaccination levels seen in one country during subsequent COVID-19 waves. Governments and health-care stakeholders should monitor vaccine coverage closely and consider interventions, such as community outreach, to avoid or combat the disruptions in childhood vaccination.

The impact of the COVID-19 pandemic on abortion care utilization and disparities by age.

BACKGROUND: A variety of state-level restrictions were placed on abortion care in response to the COVID-19 pandemic, leading to drops in utilization and delays in time to abortion. Other pandemic-related factors also may have impacted receipt of abortion care, potentially exacerbating existing barriers to care. Massachusetts is an ideal setting to study the impact of these other pandemic-related factors on abortion care utilization because there was no wide-scale abortion policy change in response to the pandemic. OBJECTIVE: This study aimed to evaluate the impact of the COVID-19 pandemic on abortion care utilization and disparities in utilization by patient age in Massachusetts. STUDY DESIGN: Using the electronic medical records from all abortions that occurred at the Planned Parenthood League of Massachusetts from May 1, 2017 through December 31, 2020 (N=35,411), we performed time series modeling to estimate monthly changes in the number of abortions from the expected counts during the COVID-19 pandemic. We also assessed if legal minors (<18 years) experienced delays in time to abortion, based on gestational age at procedure, and whether minors were differentially impacted by the pandemic. RESULTS: There were 1725 less abortions than expected, corresponding to a 20% drop, from March 2020 to December 2020 (95% prediction interval, -2025 to -1394) with 888 less (20% reduction) abortions among adults, 792 (20% reduction) less among young adults, and 45 (27% reduction) among minors. Adults and young adults experienced significant reductions in the number of abortions beginning in March 2020, whereas decreases among minors did not begin until July 2020. The rate of abortions occurring ≥12 weeks gestational age was unchanged during the COVID-19 pandemic among minors (adjusted rate ratio, 0.92; 95% confidence interval, 0.55-1.51) and among adults (adjusted rate ratio, 0.92; 95% confidence interval, 0.78-1.09). Young adults had a lower rate of second trimester abortion during the pandemic (adjusted rate ratio, 0.79; 95% confidence interval, 0.66-0.95). CONCLUSION: Despite uninterrupted abortion service provision, abortion care utilization decreased markedly in Massachusetts during the pandemic. There was no evidence of an increase in second trimester abortions in any age group. Further research is needed to determine if a decline in the pregnancy rate or other factors, such as financial and travel barriers, fear of infection, or privacy concerns, may have contributed to this decline.

Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in Haiti.

BACKGROUND: Lot Quality Assurance Sampling (LQAS), a tool used for monitoring health indicators in low resource settings resulting in "high" or "low" classifications, assumes that determination of the trait of interest is perfect. This is often not true for diagnostic tests, with imperfect sensitivity and specificity. Here, we develop Lot Quality Assurance Sampling for Imperfect Tests (LQAS-IMP) to address this issue and apply it to a COVID-19 serosurveillance study design in Haiti. METHODS: We first derive a modified procedure, LQAS-IMP, that accounts for the sensitivity and specificity of a diagnostic test to yield correct classification errors. We then apply the novel LQAS-IMP to design an LQAS system to classify prevalence of SARS-CoV-2 antibodies among healthcare workers at eleven Zanmia Lasante health facilities in Haiti. Finally, we show the performance of the LQAS-IMP procedure in a simulation study. RESULTS: We found that when an imperfect diagnostic test is used, the classification errors in the standard LQAS procedure are larger than specified. In the modified LQAS-IMP procedure, classification errors are consistent with the specified maximum classification error. We then utilized the LQAS-IMP procedure to define valid systems for sampling at eleven hospitals in Haiti. CONCLUSION: The LQAS-IMP procedure accounts for imperfect sensitivity and specificity in system design; if the accuracy of a test is known, the use of LQAS-IMP extends LQAS to applications for indicators that are based on laboratory tests, such as SARS-CoV-2 antibodies.

Service delivery reform for maternal and newborn health in Kakamega County, Kenya: study protocol for a prospective impact evaluation and implementation science study.

BACKGROUND: Maternal and neonatal mortality remain elevated in low and middle income countries, and progress is slower than needed to achieve the Sustainable Development Goals. Existing strategies appear to be insufficient. One proposed alternative strategy, Service Delivery Redesign for Maternal and Neonatal Health (SDR), centers on strengthening higher level health facilities to provide rapid, definitive care in case of delivery and post-natal complications, and then promoting delivery in these hospitals, rather than in primary care facilities. However to date, SDR has not been piloted or evaluated. METHODS: We will use a prospective, non-randomized stepped-wedge design to evaluate the effectiveness and implementation of Service Delivery Redesign for Maternal and Neonatal Health in Kakamega County, Kenya. DISCUSSION: This protocol describes a hybrid effectiveness/implementation evaluation study with an adaptive design. The impact evaluation ("effectiveness") study focuses on maternal and newborn health outcomes, and will be accompanied by an implementation evaluation focused on program reach, adoption, and fidelity.

Caregiver parenting practices, dietary diversity knowledge, and association with early childhood development outcomes among children aged 18-29 months in Zanzibar, Tanzania: a cross-sectional survey.

BACKGROUND: Many children in low- and middle-income countries fail to reach their cognitive potential, with experiences before age 3 critical in shaping long-term development. Zanzibar's Jamii ni Afya program is the first national, digitally enabled community health volunteer (CHV) program promoting early childhood development (ECD) following the Nurturing Care Framework within an integrated maternal and child healthcare package. Using program baseline data, we explored home environment, caregivers' parenting, health and nutrition knowledge and practices, and ECD outcomes in Zanzibar. METHODS: We conducted a national household survey among 499 children aged 18-29 months using two-stage cluster sampling in February 2019. The primary outcome was child development score measured using the Caregiver Reported Early Developmental Index (CREDI), with higher scores representing higher levels of child development. We analyzed CREDI scores, along with MICS questions on parenting knowledge, practices, and characteristics of the home environment. We developed multivariate regression models to assess associations between caregiver-child interactions, knowledge of dietary diversity, and ECD. RESULTS: Ten percent of children had overall CREDI z-scores 2 standard deviations [SD] or more below the global reference population mean, with 28% of children at risk of developmental delay with z-scores 1 SD or more below the mean. Cognitive and language domains were of highest concern (10.2 and 12.7% with z-score < - 2 SD). In 3-day recall, 75% of children engaged in ≥4 early stimulating activities with all caregivers averaging 3 total hours of play. CREDI scores were positively associated with greater frequency of caregivers' engagement (ß = 0.036, p = 0.002, 95%CI = [0.014, 0.058]), and dietary diversity knowledge (ß = 0.564, p < 0.001, 95%CI = [0.281, 0.846]). CONCLUSIONS: Our findings demonstrate a positive association between both the frequency of caregiver child interactions and knowledge of adequate dietary diversity, and ECD outcomes. This aligns with global evidence that promoting early stimulation, play and learning opportunities, and dietary diversity can improve developmental outcomes. Further study is needed to establish causal relationships and assess the impact of ECD programming in Zanzibar.

Opioid Use After Laparoscopic Surgery for Endometriosis and Pelvic Pain.

STUDY OBJECTIVE: The primary objective was to quantify postoperative opioid use after laparoscopic surgery for endometriosis or pelvic pain. The secondary objective was to identify patient characteristics associated with greater postoperative opioid requirements. DESIGN: Prospective, survey-based study in which subjects completed 1 preoperative and 7 postoperative surveys within 28 days of surgery regarding medication usage and pain control. SETTING: Tertiary care, academic center. PATIENTS: A total of 100 women with endometriosis or pelvic pain. INTERVENTIONS: Laparoscopic same-day discharge surgery by fellowship-trained minimally invasive gynecologists. MEASUREMENTS AND MAIN RESULTS: A total of 100 patients were recruited and 8 excluded, for a final sample size of 92 patients. All patients completed the preoperative survey. Postoperative response rates ranged from 70.7% to 80%. The mean number of pills (5 mg oxycodone tablets) taken by day 28 was 6.8. The average number of pills prescribed was 10.2, with a minimum of 4 (n = 1) and maximum of 20 (n = 3). Previous laparoscopy for pelvic pain was associated with a significant increase in postoperative narcotic use (8.2 vs 5.6; p = .044). Hysterectomy was the only surgical procedure associated with a significant increase in postoperative narcotic use (9.7 vs 5.4; p = .013). There were no difference in number of pills taken by presence of deep endometriosis or pathology-confirmed endometriosis (all p >.36). There was a trend of greater opioid use in patients with diagnoses of self-reported chronic pelvic pain, anxiety, and depression (7.9 vs 5.7, p = .051; 7.7 vs 5.2, p = .155; 8.1 vs 5.6, p = .118). CONCLUSION: Most patients undergoing laparoscopic surgery for endometriosis and pelvic pain had a lower postoperative opioid requirement than prescribed, suggesting surgeons can prescribe fewer postoperative narcotics in this population. Patients with a previous surgery for pelvic pain, self-reported chronic pelvic pain syndrome, anxiety, and depression may represent a subset of patients with increased postoperative opioid requirements.

Identifying Programmatic Factors that Increase Likelihood of Health Facility Delivery: Results from a Community Health Worker Program in Zanzibar.

INTRODUCTION: Community health worker (CHW) interventions have been utilized to address barriers that prevent pregnant women from delivering in health facilities in low- and middle-income countries (LMICs). The objective of this research was to assess the programmatic factors that increase the likelihood of health facility delivery within a large digital health-supported CHW program in Zanzibar, Tanzania. METHODS: This study included 36,693 women who were enrolled in the Safer Deliveries program with a live birth between January 1, 2017 and July 31, 2019. We assessed whether long-term enrollment, recency of CHW pregnancy visit prior to delivery, and number of routine home pregnancy visits were associated with an increased likelihood of health facility delivery compared to home delivery. We used Chi-squared tests to assess bivariate relationships and performed logistic regression analyses to assess the association between each programmatic variable and health facility delivery, adjusting for relevant confounders. RESULTS: We found that long-term enrollment was significantly associated with increased likelihood of health facility delivery, with the strongest relationship among women with a previous home delivery (OR = 1.4, 95%CI [1.0,1.7]). Among first-time mothers, two or more pregnancy visits by a CHW was positively associated with health facility delivery (OR = 1.8, 95%CI [1.2, 2.7]). Recent pregnancy visit by a CHW was positively associated with health facility delivery, but was not significant at the α = 0.05 level. DISCUSSION: In this program, we found evidence that at least two routine home pregnancy visits, longer length of enrollment in the program, and recency of home visit to the delivery date were strategies to increase health facility delivery rates among enrolled mothers. Maternal and child health programs should undertake similar evaluations to improve program delivery.

Discussion on "Causal mediation of semicompeting risks" by Yen-Tsung Huang.

Huang proposes a method for assessing the impact of a point treatment on mortality either directly or mediated by occurrence of a nonterminal health event, based on data from a prospective cohort study in which the occurrence of the nonterminal health event may be preemptied by death but not vice versa. The author uses a causal mediation framework to formally define causal quantities known as natural (in)direct effects. The novelty consists of adapting these concepts to a continuous-time modeling framework based on counting processes. In an effort to posit "scientifically interpretable estimands," statistical and causal assumptions are introduced for identification. In this commentary, we argue that these assumptions are not only difficult to interpret and justify, but are also likely violated in the hepatitis B motivating example and other survival/time to event settings as well.

Pain and Quality of Life after Laparoscopic Excision of Endometriosis.

STUDY OBJECTIVE: To evaluate the long-term impact of laparoscopic excision of endometriosis on quality of life through pain reduction as measured by the Endometriosis Health Profile-30 (EHP-30) in uterine-sparing (preservation of the uterus and at least 1 ovary) and nonuterine-sparing (removal of the uterus) surgery. DESIGN: Cohort study. SETTING: Academic medical center. PATIENTS: Sixty-one women who had undergone laparoscopic excision of endometriosis for pelvic pain were enrolled in a tissue-procurement study. INTERVENTIONS: Patients who had previously completed an EHP-30 preoperatively and at 4 weeks postoperatively were mailed a copy of the EHP-30 2.6 to 6.8 years after their index surgery. MEASUREMENTS AND MAIN RESULTS: The primary outcome was quality of life as measured by changes in the EHP-30 scores before their index surgery and those measured weeks and years later. The secondary outcome was a comparison of the EHP-30 scores between patients who underwent excision of endometriosis alone and those who underwent excision of endometriosis with hysterectomy +/- oophorectomy. From 2011 to 2015, 61 women underwent laparoscopic excision of endometriosis for pelvic pain. Forty-six of the 61 patients completed the EHP-30 for a response rate of 75%. The patients demonstrated significant improvement in all 5 scales of the EHP-30 (pain, control and powerlessness, emotional well-being, social support, and self-image) at 4 weeks postoperatively (p <.001), which persisted for up to 6.8 years in follow-up (p <.001) when compared with their baseline scores. The improvement in EHP-30 scores did not differ by American Society for Reproductive Medicine staging or index surgery. Definitive surgery (total laparoscopic hysterectomy/bilateral salpingo-oophorectomy) was not associated with improved outcomes when compared with uterine-sparing surgery. CONCLUSION: Laparoscopic excision of endometriosis offers improvement in all quality-of-life domains as measured by the EHP-30, including a reduction in pain, an effect that may persist for up to 6.8 years. These findings suggest that laparoscopic excision of endometriosis with uterine preservation can be considered as an option for discussion during counseling for treatment of endometriosis.

Errors in estimated gestational ages reduce the likelihood of health facility deliveries: results from an observational cohort study in Zanzibar.

BACKGROUND: Most maternal health programs in low- and middle- income countries estimate gestational age to provide appropriate antenatal care at the correct times throughout the pregnancy. Although various gestational dating methods have been validated in research studies, the performance of these methods has not been evaluated on a larger scale, such as within health systems. The objective of this research was to investigate the magnitude and impact of errors in estimated delivery dates on health facility delivery among women enrolled in a maternal health program in Zanzibar. METHODS: This study included 4225 women who were enrolled in the Safer Deliveries program and delivered before May 31, 2017. The exposure of interest was error in estimated delivery date categorized as: severe overestimate, when estimated delivery date (EDD) was 36 days or more after the actual delivery date (ADD); moderate overestimate, when EDD was 15 to 35 days after ADD; accurate, when EDD was 6 days before to 14 days after ADD; and underestimate, when EDD was 7 days or more before ADD. We used Chi-squared tests to identify factors associated with errors in estimated delivery dates. We performed logistic regression to assess the impact of errors in estimated delivery dates on health facility delivery adjusting for age, district of residence, HIV status, and occurrence of past home delivery. RESULTS: In our data, 28% of the estimated delivery dates were a severe overestimate, 23% moderate overestimate, 41% accurate, and 8% underestimate. Compared to women with an accurate delivery date, women with a moderate or severe overestimate were significantly less likely to deliver in a health facility (OR = 0.71, 95% CI: [0.59, 0.86]; OR = 0.74, 95% CI: [0.61, 0.91]). When adjusting for multiple confounders, women with moderate overestimates were significantly less likely to deliver in a health facility (AOR = 0.76, 95% CI: [0.61, 0.93]); the result moved slightly towards null for women with severe overestimates (AOR = 0.84, 95% CI: [0.69, 1.03]). CONCLUSIONS: The overestimation of women's EDDs reduces the likelihood of health facility delivery. To address this, maternal health programs should improve estimation of EDD or attempt to curb the effect of these errors within their programs.

Estimation of Natural Indirect Effects Robust to Unmeasured Confounding and Mediator Measurement Error.

The use of causal mediation analysis to evaluate the pathways by which an exposure affects an outcome is widespread in the social and biomedical sciences. Recent advances in this area have established formal conditions for identification and estimation of natural direct and indirect effects. However, these conditions typically involve stringent assumptions of no unmeasured confounding and that the mediator has been measured without error. These assumptions may fail to hold in many practical settings where mediation methods are applied. The goal of this article is two-fold. First, we formally establish that the natural indirect effect can in fact be identified in the presence of unmeasured exposure-outcome confounding provided there is no additive interaction between the mediator and unmeasured confounder(s). Second, we introduce a new estimator of the natural indirect effect that is robust to both classical measurement error of the mediator and unmeasured confounding of both exposure-outcome and mediator-outcome relations under certain no interaction assumptions. We provide formal proofs and a simulation study to illustrate our results. In addition, we apply the proposed methodology to data from the Harvard President's Emergency Plan for AIDS Relief (PEPFAR) program in Nigeria.

Heritability of fetal hemoglobin, white cell count, and other clinical traits from a sickle cell disease family cohort.

Sickle cell disease (SCD) is the most common monogenic disorder in the world. Notably, there is extensive clinical heterogeneity in SCD that cannot be fully accounted for by known factors, and in particular, the extent to which the phenotypic diversity of SCD can be explained by genetic variation has not been reliably quantified. Here, in a family-based cohort of 449 patients with SCD and 755 relatives, we first show that 5 known modifiers affect 11 adverse outcomes in SCD to varying degrees. We then utilize a restricted maximum likelihood procedure to estimate the heritability of 20 hematologic traits, including fetal hemoglobin (HbF) and white blood cell count (WBC), in the clinically relevant context of inheritance from healthy carriers to SCD patients. We report novel estimations of heritability for HbF at 31.6% (±5.4%) and WBC at 41.2% (±6.8%) in our cohort. Finally, we demonstrate shared genetic bases between HbF, WBC, and other hematologic traits, but surprisingly little overlap between HbF and WBC themselves. In total, our analyses show that HbF and WBC have significant heritable components among individuals with SCD and their relatives, demonstrating the value of using family-based studies to better understand modifiers of SCD.

Mediation Analysis for Censored Survival Data Under an Accelerated Failure Time Model.

Recent advances in causal mediation analysis have formalized conditions for estimating direct and indirect effects in various contexts. These approaches have been extended to a number of models for survival outcomes including accelerated failure time models, which are widely used in a broad range of health applications given their intuitive interpretation. In this setting, it has been suggested that under standard assumptions, the "difference" and "product" methods produce equivalent estimates of the indirect effect of exposure on the survival outcome. We formally show that these two methods may produce substantially different estimates in the presence of censoring or truncation, due to a form of model misspecification. Specifically, we establish that while the product method remains valid under standard assumptions in the presence of independent censoring, the difference method can be biased in the presence of such censoring whenever the error distribution of the accelerated failure time model fails to be collapsible upon marginalizing over the mediator. This will invariably be the case for most choices of mediator and outcome error distributions. A notable exception arises in case of normal mediator-normal outcome where we show consistency of both difference and product estimators in the presence of independent censoring. These results are confirmed in simulation studies and two data applications.

hCG trends after mifepristone and misoprostol for undesired pregnancy of unknown location.

OBJECTIVES: To describe human chorionic gonadotropin (hCG) trends for patients with a pregnancy of unknown location (PUL) presenting for medication abortion by management strategy and outcome. STUDY DESIGN: This retrospective cohort study included patients presenting for medication abortion with a PUL at ≤42 days gestation managed with either (1) immediate mifepristone with serial hCG follow-up (same-day-start) or (2) hCG testing every 48 to 72 hours ± ultrasonography to confirm pregnancy location followed by treatment (delay-for-diagnosis). The primary outcome was percent hCG change over time between presentation and diagnosis, summarized using a multivariate regression model. RESULTS: Of the 55 same-day-start patients, none were treated for ectopic. The eight who eventually required suction curettage had median hCG percent changes (interquartile range) on days 3, 4, and 5 of +57% (-14 to 127; n = 2), +292% (226-353; n = 4), and +392% (n = 1), while the 41 successful medication abortions had declines of -64% (n = 1), -65% (-75 to -27; n = 17), and -77% (-85 to -68; n = 13). Of the 380 delay-for-diagnosis patients, the 30 ectopic pregnancies had day 3, 4, and 5 changes of +38% (-17 to 56; n = 14), +50% (17-71; n = 7), and +115% (87-177; n = 4). None of the ectopic pregnancies declined ≥50% by days 3 to 5. The hCG trend for ectopic pregnancies differed from successful medication abortions (p < 0.01), but not medication abortions with retained intrauterine pregnancies (p = 0.41). CONCLUSIONS: Serum hCG trends can help differentiate ectopic pregnancy from successful medication abortion, but cannot distinguish between ectopic and retained intrauterine pregnancy. IMPLICATIONS: Serial serum hCG testing is effective for confirming successful medication abortion and identifying patients requiring further follow-up among patients undergoing medication abortion for an undesired PUL.

Impact of Remote Blood Pressure Monitoring Device Connectivity on Engagement Among Pregnant Individuals Enrolled in the Delfina Care Platform: Observational Study.

Unlabelled: User engagement with remote blood pressure monitoring during pregnancy is critical to optimize the associated benefits of blood pressure control and early detection of hypertensive disorders of pregnancy. In our study population of pregnant individuals, we found that connected blood pressure cuffs, which automatically sync measures to a monitoring platform or health record, increase engagement (2.13 [95% CI 1.36-3.35] times more measures per day) with remote blood pressure monitoring compared to unconnected cuffs that require manual entry of measures.

Using machine learning to predict the risk of developing hypertensive disorders of pregnancy using a contemporary nulliparous cohort.

Background: Hypertensive disorders of pregnancy (HDP) are significant drivers of maternal and neonatal morbidity and mortality. Current management strategies include early identification and initiation of risk mitigating interventions facilitated by a rules-based checklist. Advanced analytic techniques, such as machine learning, can potentially offer improved and refined predictive capabilities. Objective: To develop and internally validate a machine learning prediction model for hypertensive disorders of pregnancy (HDP) when initiating prenatal care. Study Design: We developed a prediction model using data from the prospective multisite cohort Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b) among low-risk individuals without a prior history of aspirin utilization for preeclampsia prevention. The primary outcome was the development of HDP. Random forest modeling was utilized to develop predictive models. Recursive feature elimination (RFE) was employed to create a reduced model for each outcome. Area under the curve (AUC), 95% confidence intervals (CI), and calibration curves were utilized to assess discrimination and accuracy. Sensitivity analyses were conducted to compare the sensitivity and specificity of the reduced model compared to existing risk factor-based algorithms. Results: Of 9,124 assessed low risk nulliparous individuals, 21% (n=1,927) developed HDP. The prediction model for HDP had satisfactory discrimination with an AUC of 0.73 (95% CI: 0.70, 0.75). After RFE, a parsimonious reduced model with 30 features was created with an AUC of 0.71 (95% CI: 0.68, 0.74). Variables included in the model after RFE included body mass index at the first study visit, pre-pregnancy weight, first trimester complete blood count results, and maximum systolic blood pressure at the first visit. Calibration curves for all models revealed relatively stable agreement between predicted and observed probabilities. Sensitivity analysis noted superior sensitivity (AUC 0.80 vs 0.65) and specificity (0.65 vs 0.53) of the model compared to traditional risk factor-based algorithms. Conclusion: In cohort of low-risk nulliparous pregnant individuals, a prediction model may accurately predict HDP diagnosis at the time of initiating prenatal care and aid employment of close interval monitoring and prophylactic measures earlier in pregnancy.