The impact of COVID-19 first wave national lockdowns on perinatal outcomes: a rapid review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Since the emergence of COVID-19, preventative public health measures, including lockdown strategies, were declared in most countries to control viral transmission. Recent studies and anecdotes have reported changes in the prevalence of perinatal outcomes during national COVID-19lockdowns.The objective of this rapid review was to evaluate the impact of COVID-19 lockdowns on the incidence of low birth weight (LBW), preterm birth (PTB), and stillbirth. METHODS: Two reviewers searched EMBASE, CORD-19, LitCovid (PubMed), WHO Global research on corona virus disease (COVID-19), and MedRxiv for studies published in English from the first reports on COVID-19 until 17 July 2021. Perinatal outcomes of interest included LBW (< 2500 g), PTB (< 37 weeks), and stillbirth. RESULTS: Of the 1967 screened articles, 17 publications met the inclusion criteria (14 cohort studies, 1 case control and 2 cross-sectional studies). Studies included data from Denmark, UK, Ireland, Nepal, Italy, Israel, Botswana, Australia, China, Netherlands, Saudi Arabia, Austria, Zimbabwe, India, and Spain. The total sample size ranged from 3399 to 1,599,547 pregnant women. Thirteen studies examined PTB with conflicting results, reporting both an increase and a decrease in PTB incidence, with odds ratios [95% CI] ranging from 0.09 [0.01, 0.40] to 1.93 [0.76, 4.79]. Three studies found a decrease in LBW rates during lockdowns, one of which was statistically significant, with a rate ratio of 3.77 [1.21, 11.75]. Ten studies examined stillbirth rates, including four studies reporting a statistically significant increase in stillbirth rates, with adjusted relative risk ranging from 1.46 [1.13, 1.89] to 3.9 [1.83, 12.0]. Fourteen studies contained data that could be combined in a meta-analysis comparing perinatal outcomes before and during lockdown. We found that lockdown measures were associated with a significant risk of stillbirth with RR = 1.33 [95% CI 1.04, 1.69] when compared to before lockdown period. However, lockdown measures were not associated with a significant risk of PTB, LBW and VLBW compared to prepandemic periods. CONCLUSIONS: This review provides clues about the severity of the indirect influence of COVID-19 lockdown implementation; however, the criteria that lead to unexpected changes in LBW, PTB, and stillbirth remains unclear. Large studies showed conflicting results, reporting both increases and decreases in selected perinatal outcomes. Pooled results show a significant association between lockdown measures and stillbirth rates, but not low birth weight rates. Further studies examining the differences in other countries' lockdowns and sociodemographic groups from low to middle-income countries are needed. Exploration of perinatal outcomes during COVID-19 lockdown poses an opportunity to learn from and make changes to promote the reduction of the leading causes of childhood mortality worldwide.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.024 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".