How COVID-19 Treatment in Pregnancy Reflects Healthcare Utilization During a Pandemic: A Two-Stage Individual Participant Data Meta-Analysis Combining Case-Based Registries

Abstract

Purpose: To describe an international response to the COVID-19 pandemic by estimating the prevalence of medication use for COVID-19 treatment in pregnancy, stratified by hospitalization, trimester of pregnancy, and country.

Methods: We conducted a two-stage individual participant data meta-analysis of proportions from primary data on medications used to treat COVID-19 during pregnancy. A common data model was developed to pool the data from single-country and international registries. Data from pregnant individuals with COVID-19 between February 2020 and October 2022 were included in study platforms across 9 data sources. Patient information was abstracted from medical records.

Results: Among 24 937 pregnant individuals, the pooled prevalences of individuals receiving medications to treat COVID-19 were: 34.7% heparin, 9.8% antibiotics, 4.9% corticosteroids, 2.2% antivirals, 0.8% antimalarials, 0.3% convalescent plasma, 0.2% immunosuppressants, and 0.02% monoclonal antibodies. Prevalence of medication use was higher in hospitalized individuals than in non-hospitalized individuals: 58.4% versus 17.9% for heparin, 26.9% versus 5.7% for antibiotics, 17.5% versus 1.3% for corticosteroids, 10.3% versus 0.3% for antivirals, and 4.5% versus 0.1% for antimalarials. The prevalence of corticosteroid use was lower in the first trimester (0.1%) compared with the second (7.2%) and third (4.9%) trimesters of pregnancy. The prevalence of medications differed widely across countries.

Conclusion: Medication to treat COVID-19 was more frequently used in pregnant individuals hospitalized for COVID-19. Corticosteroids were used less in the first trimester of pregnancy. The differences in use between countries could reflect differences in the clinical management and access to medications for this population at risk of severe disease.

Keywords: CONSIGN group; COVID‐19; medication use; meta‐analysis; pregnancy.

FIGURE 1 |

Flowchart of the search and selection process. N corresponds to the number of data sources. CDC/SET-NET: United States Centers for Disease Control and Prevention/Surveillance for Emerging Threats to Pregnant People and Infants Network, CONSIGN: Covid-19 infectiOn aNd medicineS In preGNancy, GWU PMA: George Washington Prospective Meta-Analysis, Saudi FDA: Saudi Food and Drug Authority. A data source is defined by a dataset on pregnant individuals with COVID-19 collected by the same group of researchers. It can be a single study site (i.e., study sites from GWU PMA and Saudi FDA), a national multi-sites dataset (i.e., SET-NET) or an international multi-site collaboration (e.g., COVI-PREG). The names of the excluded data sources not shown on this flowchart are available in the Table 1 of deliverable 6 published on Zenodo: “Description and characterization of the data sources to be included in the CONSIGN-International meta-analysis” [14]. *Medications were not available for some GWU PMA sites at the time of the meta-analysis, as code was only recently developed.

FIGURE 2 |

Prevalence of antibiotic use among all pregnant individuals with COVID-19, stratified by hospitalization. The proportions are described as binomial proportions (number of medications use/number of participants) and range from 0.00 to 1. A dot indicates that the information regarding the studied medication was missing or excluded in some study sites. The vertical dotted (…) and dashed (−) lines represent the pooled proportions using the random effects and common effect models, respectively. The numbers of medications do not systematically add up to the total, because there were unknown or missing data regarding hospitalization for the COVID-19 event in some study sites. These cases were excluded from the stratification. After subgroup analysis using random effects model, there was a statistical difference for antibiotics use between hospitalized and non-hospitalized pregnant individuals (p = 0.004).

FIGURE 3 |

Prevalence of antiviral use among all pregnant individuals with COVID-19. The proportions are described as binomial proportions (number of medications use/number of participants) and range from 0.00 to 1. A dot indicates that the information regarding the studied medication was missing or excluded in some study sites. The vertical dotted (…) and dashed (−) lines represent the pooled proportion using the random effects and common effect models, respectively.

FIGURE 4 |

Prevalence of corticosteroid use among all pregnant individuals with COVID-19, stratified by trimester of pregnancy. The proportions are described in fractions (number of medications use/number of participants) and range from 0.00 to 1. A dot indicates that the information regarding the studied medication was missing or excluded in some study sites. The vertical dotted (…) and dashed (−) lines represent the pooled proportion using the random effects and common effect models, respectively. The numbers of medications do not systematically add up to the total, because there were unknown or missing data regarding trimester of pregnancy for the COVID-19 event in some study sites. These cases were excluded from the stratification. Subgroup analysis using random effect model found statistical difference for corticosteroids use across trimesters of pregnancy (p = 0.006).