Evidence map›Paper›PMID 35961858›Full record

Observational studyThe Lancet. Digital health2022

Menstrual irregularities and vaginal bleeding after COVID-19 vaccination reported to v-safe active surveillance, USA in December, 2020-January, 2022: an observational cohort study.

Karen K Wong, Charles M Heilig, Anne Hause, Tanya R Myers, Christine K Olson, Julianne Gee, Paige Marquez, Penelope Strid, David K Shay

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in The Lancet. Digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 4 pooled it
9.4field-weighted citation impact, top 1% 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

35 citing papers in PubMed, 4 syntheses or guidelines pooled it, 53 citations in OpenAlex.

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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

9 authors at 1 institution in 1 country.

Karen K WongCDC COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA. Electronic address: kwong@cdc.gov.
Charles M HeiligCDC COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Anne HauseCDC COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Tanya R MyersCDC COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Christine K OlsonCDC COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Julianne GeeCDC COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Paige MarquezCDC COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Penelope StridCDC COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA.
David K ShayCDC COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Centers for Disease Control and Prevention · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnecdotal reports of menstrual irregularities after receiving COVID-19 vaccines have been observed in post-authorisation and post-licensure monitoring. We aimed to identify and classify reports of menstrual irregularities and vaginal bleeding after COVID-19 vaccination submitted to a voluntary active surveillance system.

methodsThis observational cohort study included recipients of a COVID-19 vaccine who were aged 18 years and older and reported their health experiences to v-safe, a voluntary smartphone-based active surveillance system for monitoring COVID-19 vaccine safety in the USA, from Dec 14, 2020, to Jan 9, 2022. Responses to survey questions on reactions after vaccination were extracted, and a pre-trained natural language inference model was used to identify and classify free-text comments related to menstruation and vaginal bleeding in response to an open-ended prompt about any symptoms at intervals after vaccination. Related responses were further categorised into themes of timing, severity, perimenopausal and postmenopausal bleeding, resumption of menses, and other responses. We examined associations between symptom theme and respondent characteristics, including vaccine type and dose number received, solicited local and systemic reactions reported, and health care sought.

findings63 815 respondents reported on menstrual irregularities or vaginal bleeding, which included 62 679 female respondents (1·0% of 5 975 363 female respondents aged ≥18 years). Common themes identified included timing of menstruation (70 981 [83·6%] responses) and severity of menstrual symptoms (56 890 [67·0%] responses). Other themes included menopausal bleeding (3439 [4·0%] responses) and resumption of menses (2378 [2·8%] responses). Respondents submitting reports related to menopausal bleeding were more likely to seek health care than were those submitting reports related to other menstruation and vaginal bleeding themes.

interpretationReports of heterogeneous symptoms related to menstruation or vaginal bleeding after COVID-19 vaccination are being submitted to v-safe, although this study is unable to characterise the relationship of these symptoms to COVID-19 vaccination. Methods that leverage pretrained models to interpret and classify unsolicited signs and symptoms in free-text reports offer promise in the initial evaluation of unexpected adverse events potentially associated with use of newly authorised or licensed vaccines.

fundingCenters for Disease Control and Prevention.

Indexed as

COVID-19COVID-19 VaccinesAdolescentAdultFemaleHumansMenstruation DisturbancesUnited StatesUterine HemorrhageVaccinationWatchful WaitingCOVID-19 Vaccines

Identifiers

PMID35961858
PMCPMC9363036
OpenAlexW4291284361

What OpenQuestion holds

Textmetadata
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.