Unexpected vaginal bleeding and COVID-19 vaccination in nonmenstruating women

Menstrual disturbance associated with COVID-19 vaccines: A comprehensive systematic review and meta-analysis

BACKGROUND

The relationship between COVID-19 vaccines and menstrual disturbance is unclear, in part because researchers have measured different outcomes (e.g., delays vs. changes to cycle length) with various study designs. Menstrual disruption could be a decisive factor in people's willingness to accept the COVID-19 vaccine.

METHODS

We searched Medline, Embase, and Web of Science for studies investigating menstrual cycle length, flow volume, post-menopausal bleeding, and unexpected or intermenstrual bleeding. Data were analyzed using fixed-effects meta-analysis with Shore's adjusted confidence intervals for heterogeneity.

FINDINGS

Seventeen studies with >1·9 million participants were analyzed. We found a 19% greater risk of increase in menstrual cycle length as compared to unvaccinated people or pre-vaccination time-periods (summary relative risk (sRR): 1·19; 95% CI: 1·11-1·26; n = 23,718 participants). The increase in risk was the same for Pfizer-BioNTech (sRR: 1·15; 1·05-1·27; n = 16,595) and Moderna vaccines (sRR: 1·15; 1·05-1·25; n = 7,523), similar for AstraZeneca (sRR: 1·27; 1·02-1·59; n = 532), and higher for the Janssen (sRR: 1·69; 1·14-2·52; n = 751) vaccine. In the first cycle after vaccination, length increased by

INTERPRETATION

We observed a mild increase in the risk of menstrual disturbance associated with COVID-19 vaccines. Such risks are likely clinically unmeaningful. Vaccine recipients should be appropriately counseled.

Collapse

Key Words Collapse

MESH Headings

• Humans
• COVID-19 Vaccines/adverse effects
• Female
• COVID-19/prevention & control
• Menstruation Disturbances/chemically induced
• Menstruation Disturbances/etiology
• SARS-CoV-2
• Vaccination/adverse effects
• Menstrual Cycle/drug effects

Collapse

Grants Collapse

Affiliation(s)

Kunchok Dorjee Center for Tuberculosis and AIDS Research, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
R C Sadoff Center for Tuberculosis and AIDS Research, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
Farima Rahimi Mansour Preventative Gynecology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Sangyal Dorjee Center for Tuberculosis and AIDS Research, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
Eli M Binder Adams County Health Department, Brighton, Colorado, United States of America
Maria Stetson Center for Tuberculosis and AIDS Research, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America Center for Humanitarian Health, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
Regina Yuen Center for Tuberculosis and AIDS Research, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
Hyunju Kim Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America

Collapse

General practitioner consultation for postmenopausal bleeding after COVID-19 vaccination-a self-controlled cohort study

AIMS

The incidence of postmenopausal bleeding (PMB) has been increasing over the past years. Little is known about the risk of PMB after COVID-19 vaccination. Our study aimed to investigate this based on routine general practitioner (GP) healthcare data from the Netherlands.

METHODS

A retrospective self-controlled cohort study was performed, which included women aged ≥50 years who received at least 1 COVID-19 vaccination in 2021 and were registered in the GP databases of Nivel (the Nivel Primary Care Database, Nivel-PCD) or PHARMO by 1 January 2021. GP consultations for PMB in the exposed period (28 days after each COVID-19 vaccination) were compared with the nonexposed period (all-time outside the exposed period). Incidence rate ratios (IRRs) were calculated using Poisson regression, adjusting for SARS-CoV-2 infection during the study follow-up period.

RESULTS

A total of 692 760 COVID-19 vaccinated women aged ≥50 years were included. No increased GP consultations for PMB was observed for all COVID-19 vaccines together, as well as when stratifying the results by vaccine type (mRNA vs. vector) and vaccine brand (Pfizer/BioNTech, Moderna, AstraZeneca, Johnson & Johnson). After the second Moderna dose an adjusted IRR of 1.47 (95% confidence interval: 0.93-2.32) was observed and after the third Pfizer/BioNTech dose an adjusted IRR of 1.33 (95% confidence interval: 0.92-1.93); however, these results were not statistically significant.

CONCLUSION

No increased number of GP consultations for PMB in primary care was observed after COVID-19 vaccination in general, nor for any of the COVID-19 vaccine brands, vaccine doses or potential risk groups.

Broad-Spectrum Adverse Events of Special Interests Based on Immune Response Following COVID-19 Vaccination: A Large-Scale Population-Based Cohort Study

Background/Objectives: Current studies on adverse events related to the COVID-19 vaccine have predominantly focused on severe, life-threatening side effects. However, numerous less severe but common adverse events (AEs) remain underreported and insufficiently investigated despite their potential impact. Methods: This population-based cohort study investigated the cumulative incidence rate (cIR) and risk of the broad-spectrum AEs of special interests (AESIs) based on immune response, including gynecological, dermatological, ophthalmological, otologic, and dental problems, following COVID-19 vaccination. Results: Among 4,203,887 individuals in Seoul, South Korea, the final analysis included 1,458,557 vaccinated subjects and 289,579 non-vaccinated subjects after the exclusion of underlying diseases. The cIR of AESIs for three months was significantly higher in vaccinated subjects than in non-vaccinated subjects, except for endometriosis. The vaccination significantly increased the risks of all the AESIs except for visual impairment. The risk of alopecia showed the highest HRs (HR [95% CI] = 2.40 [1.90-3.03]) among the AESIs following COVID-19 vaccination. Among the vaccinated subjects, heterologous vaccination was associated with the increased risk of most of the AESIs. Conclusions: Our findings suggest that clinicians should closely recognize and follow up on various COVID-19 vaccine-related AEs due to their unknown impact, even if they may not be serious at present.

Artificial intelligence models predicting abnormal uterine bleeding after COVID-19 vaccination

The rapid deployment of COVID-19 vaccines has necessitated the ongoing surveillance of adverse events, with abnormal uterine bleeding (AUB) emerging as a reported concern in vaccinated females. We aimed to develop a machine learning (ML) model to predict post-vaccination AUB in women aged less than 50 years. A large-scale national cohort, the Korean Nationwide Cohort (K-COV-N cohort), was utilized, comprising over 7 million participants. The study employed advanced ML techniques, including ensemble models combining gradient boosting machine and logistic regression, and conducted feature importance analysis. The dataset was meticulously curated, focusing on relevant demographics and variables, and balanced using Synthetic Minority Over-sampling Technique. Using a national cohort of over 2 million COVID-19 vaccinated cases in South Korea, we developed a ML model for AUB prediction. Our study is the first to develop a predictive model for post-vaccination AUB, employing feature importance analysis to identify the key contributing factors. The analysis revealed three primary predictive features: COVID-19 vaccination frequency, NVX-CoV2373 (Novavax) COVID-19 vaccination count, and hemoglobin levels. These findings provide valuable insights into predicting the risk AUB following COVID-19 vaccination, potentially enhancing post-vaccination monitoring strategies.

Reports of Batch-Dependent Suspected Adverse Events of the BNT162b2 mRNA COVID-19 Vaccine: Comparison of Results from Denmark and Sweden

Background and Objective: An unexpected batch-dependent safety signal for the BNT162b2 mRNA COVID-19 vaccine was recently identified in a nationwide study from Denmark, but the generalizability of this finding is unknown. Therefore, we compared batch-dependent rates of suspected adverse events (SAEs) reported to national authorities in Denmark and Sweden. Materials and Methods: SAE and vaccine batch data were received from national authorities in Denmark and Sweden, and analyses of heterogeneity in the relationship between numbers of vaccine doses and SAEs per batch were performed, along with comparison of SAE rates and severities for batches that were shared between the two countries. Results: Significant batch-dependent heterogeneity was found in the number of SAEs per 1000 doses for both countries, with batches associated with high SAE rates detected in the early phase of the vaccination campaign and positive correlations observed between the two countries for the severity of SAEs from vaccine batches that they shared. Mild SAEs predominated in the batches used in the early part of the vaccination roll-out, where markedly higher SAE rates per 1000 doses in Denmark for the batches that were shared between the two countries suggested that a large proportion of these SAEs were under-reported in Sweden. Conclusions: The batch-dependent safety signal observed in Denmark and now confirmed in Sweden suggests that early commercial batches of BNT162b2 may have differed from those used later on, and these preliminary and hypothesis-generating results warrant further study.

Abnormal uterine bleeding diagnoses and care following COVID-19 vaccination

BACKGROUND

There is evidence suggesting that COVID-19 vaccination may be associated with small, transitory effects on uterine bleeding, possibly including menstrual timing, flow, and duration, in some individuals. However, changes in health care seeking, diagnosis, and workup for abnormal uterine bleeding in the COVID-19 vaccine era are less clear.

OBJECTIVE

This study aimed to assess the impact of COVID-19 vaccination on incident abnormal uterine bleeding diagnosis and diagnostic evaluation in a large integrated health system.

STUDY DESIGN

Using segmented regression, we assessed whether the availability of COVID-19 vaccines was associated with changes in monthly, population-based rates of incident abnormal uterine bleeding diagnoses relative to the prepandemic period in health system members aged 16 to 44 years who were not menopausal. We also compared clinical and demographic characteristics of patients diagnosed with incident abnormal uterine bleeding between December 2020 and October 13, 2021 by vaccination status (never vaccinated, vaccinated in the 60 days before diagnosis, vaccinated >60 days before diagnosis). Furthermore, we conducted detailed chart review of patients diagnosed with abnormal uterine bleeding within 1 to 60 days of COVID-19 vaccination in the same time period.

RESULTS

In monthly populations ranging from 79,000 to 85,000 female health system members, incidence of abnormal uterine bleeding diagnosis per 100,000 person-days ranged from 8.97 to 19.19. There was no significant change in the level or trend in the incidence of abnormal uterine bleeding diagnoses between the prepandemic (January 2019-January 2020) and post-COVID-19 vaccine (December 2020-December 2021) periods. A comparison of clinical characteristics of 2717 abnormal uterine bleeding cases by vaccination status suggested that abnormal bleeding among recently vaccinated patients was similar or less severe than abnormal bleeding among patients who had never been vaccinated or those vaccinated >60 days before. There were also significant differences in age and race of patients with incident abnormal uterine bleeding diagnoses by vaccination status (Ps<.02). Never-vaccinated patients were the youngest and those vaccinated >60 days before were the oldest. The proportion of patients who were Black/African American was highest among never-vaccinated patients, and the proportion of Asian patients was higher among vaccinated patients. Chart review of 114 confirmed postvaccination abnormal uterine bleeding cases diagnosed from December 2020 through October 13, 2021 found that the most common symptoms reported were changes in timing, duration, and volume of bleeding. Approximately one-third of cases received no diagnostic workup; 57% had no etiology for the bleeding documented in the electronic health record. In 12% of cases, the patient mentioned or asked about a possible link between their bleeding and their recent COVID-19 vaccine.

CONCLUSION

The availability of COVID-19 vaccination was not associated with a change in incidence of medically attended abnormal uterine bleeding in our population of over 79,000 female patients of reproductive age. In addition, among 2717 patients with abnormal uterine bleeding diagnoses in the period following COVID-19 vaccine availability, receipt of the vaccine was not associated with greater bleeding severity.

Immune Cells, Gut Microbiota, and Vaccines: A Gender Perspective

The development of preventive and therapeutic vaccines has played a crucial role in preventing infections and treating chronic and non-communicable diseases, respectively. For a long time, the influence of sex differences on modifying health and disease has not been addressed in clinical and preclinical studies. The interaction of genetic, epigenetic, and hormonal factors plays a role in the sex-related differences in the epidemiology of diseases, clinical manifestations, and the response to treatment. Moreover, sex is one of the leading factors influencing the gut microbiota composition, which could further explain the different predisposition to diseases in men and women. In the same way, differences between sexes occur also in the immune response to vaccines. This narrative review aims to highlight these differences, focusing on the immune response to vaccines. Comparative data about immune responses, vaccine effectiveness, and side effects are reviewed. Hence, the intricate interplay between sex, immunity, and the gut microbiota will be discussed for its potential role in the response to vaccination. Embracing a sex-oriented perspective in research may improve the efficacy of the immune response and allow the design of tailored vaccine schedules.

No one listens to us, we know this, so we participated: Qualitative evidence from menstruation research during the COVID-19 pandemic

BACKGROUND

We created a survey to assess menstrual side effects after COVID-19 vaccination when we noticed news stories that denied or discounted the experiences of tens of thousands of menstruating and formerly menstruating people who reported experiencing bleeding changes. This survey had an unprecedented response hundreds of times higher than we had anticipated (n = 101,824).

OBJECTIVES

We investigated what motivated our sample to participate without remuneration to understand both general motivations for survey participation as well as why this survey captured the interest of so many.

DESIGN

We used open-ended responses from our online, mixed-method survey collected from April to October 2021.

METHODS

Using computer-assisted qualitative data analysis tools in R, we conducted a thematic analysis on open-ended responses. We used topic modeling to cluster the data, synthesize responses across 22,737 participants, and inform the themes summarizing the responses to "What is your interest in this project?" We compared and contrasted responses across groups (racial identity, ethnicity, gender) to examine whether the themes were representative across the demographic groups in our study.

RESULTS

The themes that characterized participants' interest in participating were vaccine effects and women's/people's health, personal experience related to the vaccine, and a love for science and data. We compared responses among demographic subgroups to avoid an overfocus on majority group responses and found the themes were reflected across each group. Lastly, we found our themes reflected multiple types of altruism.

CONCLUSION

These results were important in showing how emergent research that focuses on the concerns of potential participants can encourage high response rates from both marginalized and majority communities. Inclusive practices and familiarity with the research team built credibility that engendered trust with the public.