2023
DOI: 10.1002/ijgo.14843
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Standardizing case definitions for monitoring the safety of maternal vaccines globally: GAIA definitions, a review of progress to date

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Cited by 4 publications
(3 citation statements)
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“…Although our study used a validated claims-based algorithm to identify women with live births and to estimate pregnancy start date, errors or biases in the algorithm may affect the results. However, the algorithm has been commonly used in previous studies and has acceptable sensitivity and specificity . Furthermore, given the claim-based analysis, our study could not comprehensively account for all other potential confounders owing to unavailability and underrepresentation, such as body mass index, parity, and prenatal vitamin and aspirin use, and so forth.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Although our study used a validated claims-based algorithm to identify women with live births and to estimate pregnancy start date, errors or biases in the algorithm may affect the results. However, the algorithm has been commonly used in previous studies and has acceptable sensitivity and specificity . Furthermore, given the claim-based analysis, our study could not comprehensively account for all other potential confounders owing to unavailability and underrepresentation, such as body mass index, parity, and prenatal vitamin and aspirin use, and so forth.…”
Section: Discussionmentioning
confidence: 99%
“…However, the algorithm has been commonly used in previous studies and has acceptable sensitivity and specificity. 47 , 48 Furthermore, given the claim-based analysis, our study could not comprehensively account for all other potential confounders owing to unavailability and underrepresentation, such as body mass index, parity, and prenatal vitamin and aspirin use, and so forth. Future research, especially those using linked databases, should aim to investigate a broader set of confounding variables.…”
Section: Discussionmentioning
confidence: 99%
“…A pharmaco‐vigilance network which identifies and addresses possible adverse events in pregnant women and their newborns is essential to build confidence in vaccines. Standardized case definitions developed by the Brighton Collaboration assist with harmonization of maternal immunization data across diverse settings, and have been field tested in high‐income countries, but there is a paucity of testing in low‐ and middle‐income country (LMIC) settings 16 . In a prospective cohort of Taiwanese pregnant women, mild, self‐limiting adverse events including headache and muscle aches were reported more frequently in (mRNA COVID‐19) vaccinated compared to unvaccinated women, but no serious adverse events in women or their infants were detected 17 .…”
Section: Maternal Immunizationmentioning
confidence: 99%