COVID‐19 pandemic and population‐level pregnancy and neonatal outcomes in general population: A living systematic review and meta‐analysis (Update#2: November 20, 2021)
Bibliographic record
Abstract
INTRODUCTION: Conflicting reports of increases and decreases in rates of preterm birth (PTB) and stillbirth in the general population during the coronavirus disease 2019 (COVID-19) pandemic have surfaced. The objective of our study was to conduct a living systematic review and meta-analyses of studies reporting pregnancy and neonatal outcomes by comparing the pandemic and pre-pandemic periods. MATERIAL AND METHODS: We searched the PubMed and Embase databases and reference lists of articles published up until November 20, 2021, and included English language studies that compared outcomes between the COVID-19 pandemic time period with pre-pandemic time periods. Risk of bias was assessed using the Newcastle-Ottawa scale. We conducted random-effects meta-analysis using the inverse variance method. RESULTS: Fifty-two studies with low-to-moderate risk of bias, reporting on 2 372 521 pregnancies during the pandemic period and 28 518 300 pregnancies during the pre-pandemic period, were included. There was significant reduction in unadjusted estimates of PTB (43 studies, unadjusted odds ratio [uaOR] 0.95, 95% CI 0.93-0.98), but not in adjusted estimates (five studies, adjusted OR [aOR] 0.94, 95% CI 0.74-1.19). This reduction was noted in studies from single centers/health areas (29 studies, uaOR 0.90, 95% CI 0.85-0.94) but not in regional/national studies (14 studies, uaOR 0.99, 95% CI 0.99-1.01). There was reduction in spontaneous PTB (nine studies, uaOR 0.91, 95% CI 0.88-0.94) but not in induced PTB (eight studies, uaOR 0.90, 95% CI 0.79-1.01). There was no difference in the odds of stillbirth between the pandemic and pre-pandemic time periods (32 studies, uaOR 1.07, 95% CI 0.97-1.18 and three studies, aOR 1.18, 95% CI 0.86-1.63). There was an increase in mean birthweight during the pandemic period compared with the pre-pandemic period (nine studies, mean difference 21 g, 95% CI 13-30 g). The odds of maternal mortality were increased (five studies, uaOR 1.15, 95% CI 1.05-1.26); however, only unadjusted estimates were available, and the result was mostly influenced by one study from Mexico. There was significant publication bias for the outcome of PTB. CONCLUSIONS: The COVID-19 pandemic may be associated with a reduction in PTB; however, referral bias cannot be excluded. There was no statistically significant difference in stillbirths between pandemic and pre-pandemic periods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.027 |
| Bibliometrics | 0.008 | 0.008 |
| 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) | 0.004 | 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".