The international Perinatal Outcomes in the Pandemic (iPOP) study: protocol

Impact of COVID-19 pandemic on retinopathy of prematurity services in low resource settings

BACKGROUND AND OBJECTIVES

Retinopathy of prematurity is an increasingly important cause of blindness in children in low- and middle-income countries. Timely screening and treatment greatly reduce blindness. This study assessed the impact of the COVID-19 pandemic on ROP services in low- and middle-income countries.

METHODS

An online survey with closed and open-ended questions in Microsoft Teams was sent to 304 ophthalmologists providing screening, treatment and/or vitreoretinal services (January 15 to March 12 2021). Categories were used to report impact on services. 28 participants were purposively selected for interview.

RESULTS

184/201 completed forms from 32 countries were received. Two thirds of participants worked in government facilities and 45.6% were paediatric ophthalmologists. A moderate to severe impact was reported by 13% for screening, 9% for treatment and 16% for vitreoretinal surgery with some variation between government, private and not-for-profit sectors. 22% thought services would take a year to recover. Fifteen ophthalmologists from 12 countries were interviewed. Many reported fewer neonatal admissions, and several reported more ROP blind infants once restrictions lifted. Themes associated with services continuing included limited lockdown, autonomy and flexibility, commitment, advocacy and technology. Themes associated with a negative impact include fear and panic, closure of facilities, COVID infection or quarantining of health workers and parents, lack of transport and exacerbation of poverty.

CONCLUSIONS

The COVID pandemic had a very variable impact on the provision of ROP services. In some countries where the impact was great, more infants may have become blind from ROP. Lessons can be learnt for planning pandemic preparedness.

Reduction in spontaneous and iatrogenic preterm births in twin pregnancies during COVID-19 lockdown in Melbourne, Australia: a multicenter cohort study

BACKGROUND

Melbourne, Australia, recorded one of the longest and most stringent pandemic lockdowns in 2020, which was associated with an increase in preterm stillbirths among singleton pregnancies. Twin pregnancies may be particularly susceptible to the impacts of pandemic disruptions to maternity care due to their higher background risk of adverse perinatal outcomes.

METHODS

Multicenter retrospective cohort study of all twin pregnancies birthing in public maternity hospitals in Melbourne. Multivariable log-binomial regression models were used to compare perinatal outcomes between a pre-pandemic group to women in whom weeks 20+0 to 40+0 of gestation occurred entirely during one of two lockdown-exposure periods: exposure 1 from 22 March 2020 to 21 March 2021 and exposure 2 from 22 March 2021 to 27 March 2022.

RESULTS

Total preterm births < 37 weeks were significantly lower in exposure 1 compared with the pre-pandemic period (63.1% vs 68.3%; adjusted risk ratio 0.92 95% CI 0.87-0.98, p = 0.01). This was mainly driven by fewer spontaneous preterm births (18.9% vs 20.3%; adjusted risk ratio 0.95 95% CI 0.90-0.99, p = 0.04). There were also lower rates of preterm birth < 34 weeks (19.9% vs 23.0%, adjusted risk ratio 0.93 95% CI 0.89-0.98 p = 0.01) and total iatrogenic births for fetal compromise (13.4% vs 20.4%; adjusted risk ratio 0.94 95% CI 0.89-0.98, p = 0.01). There were fewer special care nursery admissions (38.5% vs 43.4%; adjusted risk ratio 0.91 95% CI 0.87-0.95, p < 0.001) but no significant changes in stillbirth (1.5% vs 1.6%; adjusted risk ratio 1.00 95% CI 0.99-1.01, p = 0.82). Compared with the pre-pandemic period, there were more preterm births < 28 weeks and neonatal intensive care unit admissions in exposure 2.

CONCLUSIONS

Melbourne's first lockdown-exposure period was associated with lower preterm births in twins without significant differences in adverse newborn outcomes. Our findings provide insights into the influences on preterm birth and the optimal timing of delivery for twins.

Before the first breath: why ambient air pollution and climate change should matter to neonatal-perinatal providers

Common outdoor air pollutants present threats to fetal and neonatal health, placing neonatal-perinatal clinical specialists in an important role for harm reduction through patient counseling and advocacy. Climate change is intertwined with air pollution and influences air quality. There is increasing evidence demonstrating the unique vulnerability in the development of adverse health consequences from exposures during the preconception, prenatal, and early postnatal periods, as well as promising indications that policies aimed at addressing these toxicants have improved birth outcomes. Advocacy by neonatal-perinatal providers articulating the potential impact of pollutants on newborns and mothers is essential to promoting improvements in air quality and reducing exposures. The goal of this review is to update neonatal-perinatal clinical specialists on the key ambient air pollutants of concern, their sources and health effects, and to outline strategies for protecting patients and communities from documented adverse health consequences.

Changes in birth outcomes and utilization of prenatal care during the COVID-19 pandemic in 2020: a secondary analysis of vital statistics in Colombia

BACKGROUND

Birth outcomes could have been affected by the COVID-19 pandemic through changes in access to prenatal services and other pathways. The aim of this study was to examine the effects of the COVID-19 pandemic on fetal death, birth weight, gestational age, number of prenatal visits, and caesarean delivery in 2020 in Colombia.

METHODS

We conducted a secondary analysis of data on 3,140,010 pregnancies and 2,993,534 live births from population-based birth certificate and fetal death certificate records in Colombia between 2016 and 2020. Outcomes were compared separately for each month during 2020 with the same month in 2019 and pre-pandemic trends were examined in regression models controlling for maternal age, educational level, marital status, type of health insurance, place of residence (urban/rural), municipality of birth, and the number of pregnancies the mother has had before last pregnancy.

RESULTS

We found some evidence for a decline in miscarriage risk in some months after the pandemic start, while there was an apparent lagging increase in stillbirth risk, although not statistically significant after correction for multiple comparisons. Birth weight increased during the onset of the pandemic, a change that does not appear to be driven by pre-pandemic trends. Specifically, mean birth weight was higher in 2020 than 2019 for births in April through December by about 12 to 21 g (p < 0.01). There was also a lower risk of gestational age at/below 37 weeks in 2020 for two months following the pandemic (April, June), but a higher risk in October. Finally, there was a decline in prenatal visits in 2020 especially in June-October, but no evidence of a change in C-section delivery.

CONCLUSIONS

The study findings suggest mixed early effects of the pandemic on perinatal outcomes and prenatal care utilization in Colombia. While there was a significant decline in prenatal visits, other factors may have had counter effects on perinatal health including an increase in birth weight on average.

Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries

Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from -90% to +30%, were reported in many countries following early COVID-19 pandemic response measures ('lockdowns'). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95-0.98, P value <0.0001), second (0.96, 0.92-0.99, 0.03) and third (0.97, 0.94-1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96-1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88-1.14, 0.98), third (0.99, 0.88-1.12, 0.89) and fourth (1.01, 0.87-1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02-1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03-1.15, 0.002), third (1.10, 1.03-1.17, 0.003) and fourth (1.12, 1.05-1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways.

Double jeopardy-pregnancy and birth during a catastrophic bushfire event followed by a pandemic lockdown, a natural experiment

BACKGROUND

From November 2019 to January 2020, eastern Australia experienced the worst bushfires in recorded history. Two months later, Sydney and surrounds were placed into lockdown for six weeks due to the COVID-19 pandemic, followed by ongoing restrictions. Many pregnant women at this time were exposed to both the bushfires and COVID-19 restrictions.

OBJECTIVE

To assess the impact of exposure to bushfires and pandemic restrictions on perinatal outcomes.

METHODS

The study included 60 054 pregnant women who gave birth between November 2017 and December 2020 in South Sydney. Exposure cohorts were based on conception and birthing dates: 1) bushfire late pregnancy, born before lockdown; 2) bushfires in early-mid pregnancy, born during lockdown or soon after; 3) conceived during bushfires, lockdown in second trimester; 4) conceived after bushfires, pregnancy during restrictions. Exposure cohorts were compared with pregnancies in the matching periods in the two years prior. Associations between exposure cohorts and gestational diabetes, preeclampsia, hypertension, stillbirth, mode of birth, birthweight, preterm birth and small for gestational age were assessed using generalised estimating equations, adjusting for covariates.

RESULTS

A decrease in low birth weight was observed for cohort 1 (aOR 0.81, 95%CI 0.69, 0.95). Conversely, cohort 2 showed an increase in low birth weight, and increases in prelabour rupture of membranes, and caesarean sections (aOR 1.18, 95%CI 1.03, 1.37; aOR 1.21, 95%CI 1.07, 1.37; aOR 1.10 (1.02, 1.18) respectively). Cohort 3 showed an increase in unplanned caesarean sections and high birth weight babies (aOR 1.15, 95%CI 1.04, 1.27 and aOR 1.16, 95%CI 1.02, 1.31 respectively), and a decrease in gestational diabetes mellitus was observed for both cohorts 3 and 4.

CONCLUSION

Pregnancies exposed to both severe climate events and pandemic disruptions appear to have increased risk of adverse perinatal outcomes beyond only experiencing one event, but further research is needed.

Data capture and sharing in the COVID-19 pandemic: a cause for concern

Routine health care and research have been profoundly influenced by digital-health technologies. These technologies range from primary data collection in electronic health records (EHRs) and administrative claims to web-based artificial-intelligence-driven analyses. There has been increased use of such health technologies during the COVID-19 pandemic, driven in part by the availability of these data. In some cases, this has resulted in profound and potentially long-lasting positive effects on medical research and routine health-care delivery. In other cases, high profile shortcomings have been evident, potentially attenuating the effect of-or representing a decreased appetite for-digital-health transformation. In this Series paper, we provide an overview of how facets of health technologies in routinely collected medical data (including EHRs and digital data sharing) have been used for COVID-19 research and tracking, and how these technologies might influence future pandemics and health-care research. We explore the strengths and weaknesses of digital-health research during the COVID-19 pandemic and discuss how learnings from COVID-19 might translate into new approaches in a post-pandemic era.

Increase in preterm stillbirths in association with reduction in iatrogenic preterm births during COVID-19 lockdown in Australia: a multicenter cohort study

Background

The COVID-19 pandemic has been associated with a worsening of perinatal outcomes in many regions around the world. Melbourne, Australia, had one of the longest and most stringent lockdowns worldwide in 2020 while recording only rare instances of COVID-19 infection in pregnant women.

Objective

This study aimed to compare the stillbirth and preterm birth rates in women who were exposed or unexposed to lockdown restrictions during pregnancy.

Study Design

This was a retrospective, multicenter cohort study of perinatal outcomes in Melbourne before and during the COVID-19 lockdown. The lockdown period was defined as the period from March 23, 2020 to March 14, 2021. Routinely-collected maternity data on singleton pregnancies ≥24 weeks gestation without congenital anomalies were obtained from all the 12 public hospitals in Melbourne. We defined the lockdown-exposed cohort as those women for whom weeks 20 to 40 of gestation occurred during the lockdown and the unexposed control group as women from the corresponding calendar periods 12 and 24 months before. The main outcome measures were stillbirth, preterm birth, fetal growth restriction (birthweight < third centile), and iatrogenic preterm birth for fetal compromise. We performed multivariable logistic regression analysis to compare the odds of stillbirth, preterm birth, fetal growth restriction, and iatrogenic preterm birth for fetal compromise, adjusting for multiple covariates.

Results

There were 24,817 births in the exposed group and 50,017 births in the control group. There was a significantly higher risk of preterm stillbirth in the exposed group than the control group (0.26% vs 0.18%; adjusted odds ratio, 1.49; 95% confidence interval, 1.08–2.05; P=.015). There was also a significant reduction in the preterm birth of live infants <37 weeks (5.68% vs 6.07%; adjusted odds ratio, 0.93; 95% confidence interval, 0.87–0.99; P=.02), which was largely mediated by a significant reduction in iatrogenic preterm birth (3.01% vs 3.27%; adjusted odds ratio, 0.91; 95% confidence interval, 0.83–0.99; P=.03), including iatrogenic preterm birth for fetal compromise (1.25% vs 1.51%; adjusted odds ratio, 0.82; 95% confidence interval, 0.71–0.93; P=.003). There were also significant reductions in special care nursery admissions during lockdown (11.53% vs 12.51%; adjusted odds ratio, 0.90; 95% confidence interval, 0.86–0.95; P<.0001). There was a trend to fewer spontaneous preterm births <37 weeks in the exposed group of a similar magnitude to that reported in other countries (2.69% vs 2.82%; adjusted odds ratio, 0.95; 95% confidence interval, 0.87–1.05; P=.32).

Conclusion

Lockdown restrictions in Melbourne, Australia were associated with a significant reduction in iatrogenic preterm birth for fetal compromise and a significant increase in preterm stillbirths. This raises concerns that pandemic conditions in 2020 may have led to a failure to identify and appropriately care for pregnant women at an increased risk of antepartum stillbirth. Further research is required to understand the relationship between these 2 findings and to inform our ongoing responses to the pandemic.

Collaborative maternity and newborn dashboard (CoMaND) for the COVID-19 pandemic: a protocol for timely, adaptive monitoring of perinatal outcomes in Melbourne, Australia

BACKGROUND

The COVID-19 pandemic has resulted in a range of unprecedented disruptions to maternity care with documented impacts on perinatal outcomes such as stillbirth and preterm birth. Metropolitan Melbourne has endured one of the longest and most stringent lockdowns in globally. This paper presents the protocol for a multicentre study to monitor perinatal outcomes in Melbourne, Australia, during the COVID-19 pandemic.

METHODS

Multicentre observational study analysing monthly deidentified maternal and newborn outcomes from births >20 weeks at all 12 public maternity services in Melbourne. Data will be merged centrally to analyse outcomes and create run charts according to established methods for detecting non-random 'signals' in healthcare. Perinatal outcomes will include weekly rates of total births, stillbirths, preterm births, neonatal intensive care admissions, low Apgar scores and fetal growth restriction. Maternal outcomes will include weekly rates of: induced labour, caesarean section, births before arrival to hospital, postpartum haemorrhage, length of stay, general anaesthesia for caesarean birth, influenza and COVID-19 vaccination status, and gestation at first antenatal visit. A prepandemic median for all outcomes will be calculated for the period of January 2018 to March 2020. A significant shift is defined as ≥6 consecutive weeks, all above or below the prepandemic median. Additional statistical analyses such as regression, time series and survival analyses will be performed for an in-depth examination of maternal and perinatal outcomes of interests.

ETHICS AND DISSEMINATION

Ethics approval for the collaborative maternity and newborn dashboard project has been obtained from the Austin Health (HREC/64722/Austin-2020) and Mercy Health (ref. 2020-031).

TRIAL REGISTRATION NUMBER

ACTRN12620000878976; Pre-results.

Changes in obstetric interventions and preterm birth during COVID-19: A nationwide study from Iceland

INTRODUCTION

Previous evidence has been conflicting regarding the effect of coronavirus disease 2019 (COVID-19) pandemic lockdowns on obstetric intervention and preterm birth rates. The literature to date suggests potentially differential underlying mechanisms based on country economic setting. We aimed to study these outcomes in an Icelandic population where uniform lockdown measures were implemented across the country.

MATERIAL AND METHODS

The study included all singleton births (n = 20 680) during 2016-2020 identified from the population-based Icelandic Medical Birth Register. We defined two lockdown periods during March-May and October-December in 2020 according to government implemented nationwide lockdown. We compared monthly rates of cesarean section, induction of labor and preterm birth during lockdown with the same time periods in the 4 previous years (2016-2019) using logit binomial regression adjusted for confounders.

RESULTS

Our results indicated a reduction in the overall cesarean section rate, which was mainly evident for elective cesarean section, both during the first (adjusted odd ratio [aOR] 0.71, 95% CI 0.51-0.99) and second (aOR 0.72, 95% CI 0.52-0.99) lockdown periods, and not for emergency cesarean section. No change during lockdown was observed in induction of labor. Our results also suggested a reduction in the overall preterm birth rate during the first lockdown (aOR 0.69, 95% CI 0.49-0.97) and in the months immediately following the lockdown (June-September) (aOR 0.67, 95% CI 0.49-0.89). The reduction during the first lockdown was mainly evident for medically indicated preterm birth (although not statistically significant) and the reduction during June-September was mainly evident for spontaneous preterm birth.

CONCLUSIONS

This study suggested a reduction in elective cesarean section during COVID-19 lockdown, possibly reflecting changes in prioritization of non-urgent health care during lockdown. We also found a reduction in overall preterm birth during the first lockdown and spontaneous preterm birth following the first lockdown, but further research is needed to shed light on the underlying mechanisms for these findings.

Data-driven risk stratification for preterm birth in Brazil: a population-based study to develop of a machine learning risk assessment approach

Background

Preterm birth (PTB) is a growing health issue worldwide, currently considered the leading cause of newborn deaths. To address this challenge, the present work aims to develop an algorithm capable of accurately predicting the week of delivery supporting the identification of a PTB in Brazil.

Methods

This a population-based study analyzing data from 3,876,666 mothers with live births distributed across the 3,929 Brazilian municipalities. Using indicators comprising delivery characteristics, primary care work processes, and physical infrastructure, and sociodemographic data we applied a machine learning-based approach to estimate the week of delivery at the point of care level. We tested six algorithms: eXtreme Gradient Boosting, Elastic Net, Quantile Ordinal Regression - LASSO, Linear Regression, Ridge Regression and Decision Tree. We used the root-mean-square error (RMSE) as a precision.

Findings

All models obtained RMSE indexes close to each other. The lower levels of RMSE were obtained using the eXtreme Gradient Boosting approach which was able to estimate the week of delivery within a 2.09 window 95%IC (2.090-2.097). The five most important variables to predict the week of delivery were: number of previous deliveries through Cesarean-Section, number of prenatal consultations, age of the mother, existence of ultrasound exam available in the care network, and proportion of primary care teams in the municipality registering the oral care consultation.

Interpretation

Using simple data describing the prenatal care offered, as well as minimal characteristics of the pregnant, our approach was capable of achieving a relevant predictive performance regarding the week of delivery.

Funding

Bill and Melinda Gates Foundation, and National Council for Scientific and Technological Development - Brazil, (Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPQ acronym in portuguese) Support of the research project named: Data-Driven Risk Stratification for Preterm Birth in Brazil: Development of a Machine Learning-Based Innovation for Health Care- Grant: OPP1202186.