Evidence map›Paper›PMID 34178302›Full record

ArticleTherapeutic advances in drug safety2021

Vaccine Safety Datalink infrastructure enhancements for evaluating the safety of maternal vaccination.

Allison L Naleway, Bradley Crane, Stephanie A Irving, Don Bachman, Kimberly K Vesco, Matthew F Daley, Darios Getahun, Sungching C Glenn, Simon J Hambidge, Lisa A Jackson and 9 more

Open access · goldAbstract read
In one paragraph

Article in Therapeutic advances in drug safety, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 44 citations in OpenAlex.

  1. Association Between COVID-19 Vaccination During Pregnancy and Safety Among Infants.Journal of the Pediatric Infectious Diseases Society · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors at 8 institutions in 1 country.

Allison L NalewayCenter for Health Research, Kaiser Permanente Northwest, 3800 N. Interstate Ave, Portland, OR 97227, USA.
Bradley CraneCenter for Health Research, Kaiser Permanente Northwest, Portland, OR, USA.
Stephanie A IrvingCenter for Health Research, Kaiser Permanente Northwest, Portland, OR, USA.ORCID https://orcid.org/0000-0001-7437-6797
Don BachmanCenter for Health Research, Kaiser Permanente Northwest, Portland, OR, USA.
Kimberly K VescoCenter for Health Research, Kaiser Permanente Northwest, Portland, OR, USA.
Matthew F DaleyKaiser Permanente Colorado, Denver, CO, USA.
Darios GetahunKaiser Permanente Southern California, Pasadena, CA, USA.
Sungching C GlennKaiser Permanente Southern California, Pasadena, CA, USA.
Simon J HambidgeDenver Health, Denver, CO, USA.
Lisa A JacksonKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Nicola P KleinKaiser Permanente Vaccine Study Center, Oakland, CA, USA.
Natalie L McCarthyCenters for Disease Control and Prevention, Atlanta, GA, USA.
David L McClureMarshfield Clinic Research Institute, Marshfield, WI, USA.
Lakshmi PanagiotakopoulosCenters for Disease Control and Prevention, Atlanta, GA, USA.
Catherine A PanozzoHarvard Pilgrim Health Care Institute, Boston, MA, USA.
Gabriela Vazquez-BenitezHealthPartners Institute, Minneapolis, MN, USA.
Eric S WeintraubCenters for Disease Control and Prevention, Atlanta, GA, USA.
Ousseny ZerboKaiser Permanente Vaccine Study Center, Oakland, CA, USA.
Elyse O KharbandaHealthPartners Institute, Minneapolis, MN, USA.
Kaiser Permanente · USKaiser Permanente Center for Health Research · USCenters for Disease Control and Prevention · USHealthPartners · USDenver Health Medical Center · USHarvard Pilgrim Health Care · USKaiser Permanente Washington Health Research Institute · USMarshfield Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIdentifying pregnancy episodes and accurately estimating their beginning and end dates are imperative for observational maternal vaccine safety studies using electronic health record (EHR) data.

methodsWe modified the Vaccine Safety Datalink (VSD) Pregnancy Episode Algorithm (PEA) to include both the International Classification of Disease, ninth revision (ICD-9 system) and ICD-10 diagnosis codes, incorporated additional gestational age data, and validated this enhanced algorithm with manual medical record review. We also developed the new Dynamic Pregnancy Algorithm (DPA) to identify pregnancy episodes in real time.

resultsAround 75% of the pregnancy episodes identified by the enhanced VSD PEA were live births, 12% were spontaneous abortions (SABs), 10% were induced abortions (IABs), and 0.4% were stillbirths (SBs). Gestational age was identified for 99% of live births, 89% of SBs, 69% of SABs, and 42% of IABs. Agreement between the PEA-assigned and abstractor-identified pregnancy outcome and outcome date was 100% for live births, but was lower for pregnancy losses. When gestational age was available in the medical record, the agreement was higher for live births (97%), but lower for pregnancy losses (75%). The DPA demonstrated strong concordance with the PEA and identified pregnancy episodes ⩾6 months prior to the outcome date for 89% of live births.

conclusionThe enhanced VSD PEA is a useful tool for identifying pregnancy episodes in EHR databases. The DPA improves the timeliness of pregnancy identification and can be used for near real-time maternal vaccine safety studies. PLAIN LANGUAGE SUMMARY:

Indexed as

algorithmimmunizationpregnancysafety

Identifiers

PMID34178302
PMCPMC8207278
OpenAlexW3167507776

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.