Geospatial Distribution of Prenatally and Postnatally Diagnosed Congenital Heart Disease: Implications for Equitable Care from a Fetal Heart Society Research Collaborative Study.

OBJECTIVE: To characterize patterns in the geospatial distribution of pre- and postnatally diagnosed congenital heart disease (CHD) across 6 surgical centers. STUDY DESIGN: A retrospective, multicenter case series from the Fetal Heart Society identified patients at 6 centers from 2012 through 2016 with prenatally (PrND) or postnatally (PoND) diagnosed hypoplastic left heart syndrome (HLHS) or d-transposition of the great arteries (TGA). Geospatial analysis for clustering was done by the average nearest neighbor (ANN) tool or optimized hot spot tool, depending on spatial unit and data type. Both point location and county case rate per 10 000 live births were assessed for geographic clustering or dispersion. RESULTS: Of the 453 CHD cases, 26% were PoND (n = 117), and 74% were PrND (n = 336). PrND cases, in all but one center, displayed significant geographic clustering by the ANN. Conversely, PoND cases tended toward geographic dispersion. Dispersion of PoND HLHS occurred in 2 centers (ANN = 1.59, P < .001; and 1.47, P = .016), and PoND TGA occurred in 2 centers (ANN = 1.22, P < .05; and ANN = 1.73, P < .001). Hot spot analysis of all CHD cases (TGA and HLHS combined) revealed clustering near areas of high population density and the tertiary surgical center. Hot spot analysis of county-level case rate, accounting for population density, found variable clustering patterns. CONCLUSION: Geographic dispersion among postnatally detected CHD highlights the need for a wider reach of prenatal cardiac diagnosis tailored to the specific needs of a community. Geospatial analysis can support centers in improving the equitable delivery of prenatal care.

A deep learning framework for noninvasive fetal ECG signal extraction.

Introduction: The availability of proactive techniques for health monitoring is essential to reducing fetal mortality and avoiding complications in fetal wellbeing. In harsh circumstances such as pandemics, earthquakes, and low-resource settings, the incompetence of many healthcare systems worldwide in providing essential services, especially for pregnant women, is critical. Being able to continuously monitor the fetus in hospitals and homes in a direct and fast manner is very important in such conditions. Methods: Monitoring the health of the baby can potentially be accomplished through the computation of vital bio-signal measures using a clear fetal electrocardiogram (ECG) signal. The aim of this study is to develop a framework to detect and identify the R-peaks of the fetal ECG directly from a 12 channel abdominal composite signal. Thus, signals were recorded noninvasively from 70 pregnant (healthy and with health conditions) women with no records of fetal abnormalities. The proposed model employs a recurrent neural network architecture to robustly detect the fetal ECG R-peaks. Results: To test the proposed framework, we performed both subject-dependent (5-fold cross-validation) and independent (leave-one-subject-out) tests. The proposed framework achieved average accuracy values of 94.2% and 88.8%, respectively. More specifically, the leave-one-subject-out test accuracy was 86.7% during the challenging period of vernix caseosa layer formation. Furthermore, we computed the fetal heart rate from the detected R-peaks, and the demonstrated results highlight the robustness of the proposed framework. Discussion: This work has the potential to cater to the critical industry of maternal and fetal healthcare as well as advance related applications.

Variation in prenatal surveillance and management of anti-SSA/Ro autoantibody positive pregnancies.

OBJECTIVE: To describe international surveillance and treatment strategies for managing anti-SSA/Ro autoantibody positive pregnancies. STUDY DESIGN: An electronic REDCap questionnaire was distributed to Fetal Heart Society and North American Fetal Therapy Network members which queried institution-based risk stratification, surveillance methods/frequency, conduction abnormality treatments, and postnatal anti-SSA/Ro pregnancy assessment. RESULTS: 101 responses from 59 centers (59% US, 17% international) were collected. Most (79%) do not risk stratify pregnancies by anti-SSA/Ro titer; those that do use varied cutoff values. Many pregnant rheumatology patients are monitored for cardiac abnormalities regardless of maternal anti-SSA/Ro status. Surveillance strategies were based on maternal factors (anti-SSA/Ro status 85%, titer 25%, prior affected child 79%) and monitoring durations varied. Most respondents treat 2° and 3° fetal atrioventricular block, commonly with dexamethasone and/or IVIG. CONCLUSIONS: Wide variation exists in current fetal cardiac surveillance and treatment for anti-SSA/Ro autoantibody positive pregnancies, highlighting the need for evidence-based protocols to optimize care.

Direct-to-patient telemedicine: Expanding access to regional pediatric specialty care.

Telemedicine is seen as a useful tool in reducing gaps in health care but this technology-enabled care can also exacerbate health inequity if not implemented with a focus on inclusivity. Though many studies have reported improvements as well as exacerbation of disparities in access to care in their telehealth programs, there does not exist a common evaluation tool to assess these programs. To mitigate the impact of COVID-19 on health care workers and protect medically vulnerable children, in March 2020 we expanded our pre-established specialty and subspecialty direct-to-patient pediatric telemedicine program in a high volume urban pediatric health system. Our program aimed to prevent disparities in pediatric health care. In this study, using a "Pillars of Access" approach as a model to evaluate impact and access to care of our direct-to-patient telemedicine program, we analyzed the patients that were seen pre-COVID versus post-COVID. Our study demonstrated an increase in telemedicine visits for patients from diverse socioeconomic and racial backgrounds, and geographically underserved communities. We also observed an increase in telemedicine visits for mental health complaints and for certain categories of high-risk patients. This study was not designed to identify language and cultural barriers to telemedicine. Future identification of these specific barriers is needed. The tool to evaluate telehealth impact/access to care through a "Pillars of Access" approach presented here could serve as a model for implementation of telehealth programs. Our study highlights telemedicine programs as a mechanism to address healthcare inequity and overcome barriers to care.