Evidence map›Paper›PMID 38736777›Full record

ArticleJournal of family medicine and primary care2024

Maternal and neonatal outcomes during COVID-19 pandemic and pre-pandemic in an urban slum in North India - A community-based ambispective cohort study.

Saranya Rajavel, M Sathiabalan, Tarundeep Singh

Abstract read
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Article in Journal of family medicine and primary care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Saranya RajavelDepartment of Community Medicine, ESIC Medical College and PGIMSR, Rajaji Nagar, Bengaluru, Karnataka, India.
M SathiabalanDepartment of Community Medicine, ESIC Medical College and PGIMSR, Rajaji Nagar, Bengaluru, Karnataka, India.
Tarundeep SinghDepartment of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Coronavirus disease 2019 (COVID-19) has affected millions of people globally since its first case reported on December 2019 in Wuhan, China. The maternal and neonatal outcomes during COVID-19 pandemic were not much reported in low- and middle-income countries. Therefore, we aimed to assess the maternal and neonatal outcomes during COVID-19 and compared them with those of the pre-pandemic period (i.e., 2019). Materials and Methods: We obtained data from the cohort of pregnant women who delivered during COVID-19 pandemic and women who delivered in the pre-pandemic period. All registered antenatal mothers resident of the selected dispensary who delivered in health care facilities from January 2019 to June 2019 and from January 2021 to June 2021 were included in the study for assessing the socio-demographic, antenatal, natal, post-natal, and new-born characteristics. A semi-structed questionnaire was used for obtaining details regarding pregnancy and COVID-19 status. The neuro-development assessment of the newborn was done in the community using Trivandrum Developmental Screening Chart (TDSC). Chi-square test and Fischer exact test were used to draw association between the maternal and neonatal outcomes during COVID-19 pandemic and the pre-COVID-19 period. A Results: A total of 158 and 220 women delivered in pre-COVID and during COVID, respectively. Out of them, 83 mothers (47.4%) who delivered in 2019 (pre-COVID) and 158 mothers (76.4%) who delivered in 2021 (during pandemic) were contacted. The mean age was 25 ± 3.9 years. The prevalence of anemia was significantly higher during COVID pandemic. The proportion of Rh-negative mothers and other antenatal investigation reports was similar in both the groups. The proportion of high-risk pregnancy is high among mothers who delivered during COVID than the pre-COVID period. On applying multivariate analysis, developmental delay at 3 months was found to be significant among children who were born during pandemic. Conclusion: A simple tool was used for assessing development milestones, and we have found that newborns delivered during COVID-19 pandemic were reported to have inappropriate developmental milestone at 3 months post-delivery. However, further research needed to assess the neuro-developmental status and follow-up of children born during COVID-19 pandemic for comprehensive neuro-developmental assessment. It is important to identify children with developmental delays associated with the pandemic and provide them with support for learning, socialization, physical and mental health, and family support.

Indexed as

COVID-19maternal outcomesneonatal outcomesneuro-developmentpregnancy

Identifiers

PMID38736777
PMCPMC11086783

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.