Global maternal mortality associated with SARS-CoV-2 infection: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Pregnant and recently pregnant women infected with SARS-CoV-2 are at increased risk of death and serious complications than those without the infection. The extent of variation in mortality rates in pregnant women with SARS-CoV-2 infection across regions, and the causes of death are not known. We systematically reviewed all available evidence on the variation in mortality rates in pregnant women with SARS-CoV-2 infection across geographical and country income groups, and the reported cause of death. METHODS: We searched major databases (December 2019-January 2023) including Medline, LILACS, BIREME and Embase. We included studies that reported deaths in at least 10 consecutive pregnant or recently pregnant women with confirmed SARS-CoV-2 infection and assessed the studies' risk of bias. We calculated the summary estimates of any cause of death as proportions with 95% CIs using a multilevel random-effects logistic regression model. Subgroup analyses were performed by geographical region and country income groups. We used International Statistical Classification of Diseases and Related Health Problems-Maternal Mortality to categorise the reported cause of death. FINDINGS: From 1 326 315 citations, we included 169 studies (319 172 women with confirmed SARS-CoV-2 infection; 4253 women died). The overall rate of unspecified maternal death was 0.87% (95% CI 0.64% to 1.16%). There were significant differences between geographical regions in rates of maternal mortality, with the highest rates in Sub-Saharan Africa (3.48%; 95% CI 0.66% to 16.42%) and Latin America and the Caribbean (3.16%, 95% CI 1.53% to 6.43%). Rates of maternal mortality varied by country income groups, with the highest rates in low-income countries (4.66%, 95% CI 0.75% to 24.07%). Among women with reported cause of death, 98.6% (2,390/2,423) of deaths were attributable to COVID-19. INTERPRETATION: Rates of deaths in pregnant and recently pregnant women with SARS-CoV-2 infection vary significantly across regions and by country income groups, with the highest burden in Sub-Saharan Africa and low-income countries. COVID-19 is the main reported cause of death. PROSPERO REGISTRATION NUMBER: CRD42020224120.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.003 |
| Bibliometrics | 0.000 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".