ArticleNature communications2025
The potential bidirectional relationship between long COVID and menstruation.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Unveiling the genitourinary phenotype of long COVID: a systematic review and meta-analysis.International urology and nephrology · 2026Pooled it
- The Impact of Long COVID on the Female Reproductive System: A Narrative Review.International journal of molecular sciences · 2026Review
- Menstrual cycle patterns during acute and long COVID-19 infection among a cohort of individuals with regular menstrual cycles.American journal of obstetrics and gynecology · 2026Article
- Financial burden of menstrual and menopausal symptoms: productivity loss from absenteeism and presenteeism among working-age women.Reproductive health · 2026Article
- Cortisol-resistant CAR-NK cells overcome steroid-induced immunosuppression in lung cancer.Signal transduction and targeted therapy · 2026Article
- Post-COVID fatigue disproportionately affects women: evidence from the DEFEAT Corona cohort.Frontiers in public health · 2026Article
- Post-COVID conditions: co-occurrence of symptoms and challenges for comprehensive care.Revista da Escola de Enfermagem da U S P · 2026Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Women have reported menstrual changes following SARS-CoV-2 infection and variation in long COVID symptoms across the menstrual cycle. We examined (i) whether COVID is linked to abnormal uterine bleeding (AUB), (ii) if long COVID symptoms vary with the menstrual cycle, and (iii) potential underlying mechanisms. Here we show long COVID was associated with AUB in a UK population. When compared to those never infected (n = 9423), long COVID participants (n = 1048) reported increased menstrual volume, duration and intermenstrual bleeding, while those who recovered from acute COVID (n = 1,716) reported minimal menstrual disruption. Long COVID symptoms examined in 54 women across the menstrual cycle revealed that severity was highest during the perimenstrual and proliferative phases. Serum and endometrial analysis revealed higher serum 5α-dihydrotestosterone and lower endometrial androgen receptors in long COVID versus no COVID. Other ovarian hormones showed no significant differences. Serum cytokine profiling indicated increased menstrual inflammation with long COVID and immune cell aggregates were observed in menstrual endometrium. In conclusion, long COVID was associated with AUB but not impaired ovarian function. Differences in peripheral and endometrial inflammation may contribute to AUB and long COVID symptom severity. We anticipate our findings will instigate exploration of new therapeutic strategies for women with long COVID.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.