Evidence map›Paper›PMID 36337070›Full record

ReviewClinica e investigacion en ginecologia y obstetricia

[Association of SARS-CoV-2 infection and administration of COVID-19 vaccines with alterations in the menstrual cycle. Literature review].

A Molina-López, O Ocón Hernández, L Baena García

Open access · greenAbstract readEnglish AbstractReview
In one paragraph

Review in Clinica e investigacion en ginecologia y obstetricia. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 44% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 1 institution in 1 country.

A Molina-LópezUGC Ginecología y Obstetricia Hospital Universitario San Cecilio, Granada, España.
O Ocón HernándezUGC Ginecología y Obstetricia Hospital Universitario San Cecilio, Granada, España.
L Baena GarcíaInstituto de Investigación Biosanitaria ibs.GRANADA, Granada, España.
Instituto de Investigación Biosanitaria de Granada · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A number of factors can affect a woman's menstrual cycle, including diseases or drugs, such as COVID-19 disease and vaccinations. The aim of this review is to explore the studies published to date that have studied the presence of alterations that may be related to COVID-19 or vaccination against the SARS-CoV-2 virus.We conducted a review in the PubMed database, selecting 10 articles in which the menstrual cycle of adult women of childbearing age was studied, 3 of them in which the participants had been diagnosed with COVID-19 and 7 in which the participants had been vaccinated against the SARS-CoV-2 virus.Regarding COVID-19-related disturbances, 16%-47.2% of the participants presented a prolongation of their cycle, which was more frequent in those who reported more COVID-19 symptoms, and which normalised after 1-2 cycles.Regarding the alterations described after SARS-CoV-2 vaccination, 45%-78% of participants reported menstrual cycle alterations, with disparate results for the different parameters analysed, except that the alterations resolved in about 2 months.Both COVID-19 disease and vaccination appear to be associated with the occurrence of menstrual disturbances, which are limited in time and not severe. However, studies are scarce to date, and it is important to continue to develop studies that provide scientific evidence.

Indexed as

COVID-19Menstrual cycleSARS-CoV-2Vaccine

Identifiers

PMID36337070
PMCPMC9618423
OpenAlexW4307903936

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.