Objective: To describe the demographic characteristics, clinical manifestations, and clinical outcomes of hospitalised pregnant and recently pregnant women with COVID-19 in Malawi, a low-income country in Sub-Saharan Africa. This study responds to a critical gap in the global COVID-19 data.
Methods: A national surveillance platform was established in Malawi by the Ministry of Health to record the impact of COVID-19 on pregnant and recently pregnant women and provide real-time data for decision making. We report this facility-based cohort that includes all pregnant and recently pregnant hospitalised women in Malawi suspected of having COVID-19 between 2nd June 2020 and 1st December 2021.
Results: 398 women were admitted to hospital with suspected COVID-19 based on presenting symptoms and were tested; 246 (62%) were confirmed to have COVID-19. In women with COVID-19, the mean age was 27,SD(7) years.
The most common presenting symptoms were cough (74%), breathlessness (45%), Fever (42%), headache (17%), and joint pain (10%). 53% of the women had COVID-19 symptoms severe enough to warrant admission.
31% (76/246) of women admitted with COVID-19 suffered a severe maternal outcome, 47/246 (19%) died, and 29/246 (12%) had a near-miss event. 9/111 (8%) of recorded births were stillbirths, and 12/101 (12%) of the live births resulted in early neonatal death.
Conclusion: A national electronic platform providing real-time information on the characteristics and outcomes of pregnant and recently pregnant women with COVID-19 admitted to Malawian government hospitals. These women had much higher rates of adverse outcomes than those suggested in the current global data. These findings may reflect the differences in the severity of disease required for women to present and be admitted to Malawian hospitals, limited access to intensive care and the pandemic's disruption to the health system.
Background: Over two-thirds of global maternal deaths occur in Sub-Saharan Africa (SSA), with more than 200,000 deaths per year. Maternal sepsis causes 10% of these deaths, twice the proportion observed in high-income countries. In SSA, limited access to diagnostic microbiology facilities poses difficulties in promptly identifying and managing maternal infection and sepsis. This protocol describes a systematic review and meta-analysis that aims to summarize available data on the main bacterial agents causing maternal infections and their antibiotic susceptibility in SSA. Methods: Three electronic databases will be searched: MEDLINE, Embase and African Journals Online. Our search strategy will combine terms relating to laboratory-confirmed bacterial infection, pregnancy, postnatal period and SSA. We will include observational studies describing maternal bacterial infection's aetiology and antimicrobial resistance patterns in SSA. Two authors will perform study selection, data extraction and quality assessment. A third author will be consulted to resolve disagreements if they arise.We will summarize the proportion (and 95% confidence intervals) of samples testing positive for the most common bacteria and, depending on the data's availability and heterogeneity, examine results by country and/or region. If possible, we will describe trends over time and differentiate aetiological organisms and resistance/sensitivities by maternal infection sources. We will also undertake subgroup analyses based on HIV status, the invasive and non-invasive status of the infection, SSA sub-regions and mortality if there is adequate information to make such subgroup analysis feasible. Discussion: Data on the microbiologic outcomes for maternal infections in SSA are likely fragmented and not fully representative due to the limited availability of microbiology diagnostics and geographical differences in clinical and laboratory practices. If this is the case, policies and programme strategies to guide treatment and identify antimicrobial resistance threats in SSA settings will be challenging to target. Our systematic review aims to provide a comprehensive summary of the available data, describe the main organisms causing maternal infection and their sensitivities, and identify areas that require further research. Prospero ID: CRD42021238515
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