The study revealed that catching the virus can lead to some changes in a woman's period. But vaccines do not cause disruption for most.
But the study also found that the vaccine appears to have no effect when vaccinated and unvaccinated people are compared.in the UK, in March 2021.While 6.2% reported more disruption during their period cycles and 1.6% reported less disruption.
The study also observed 1,802 unvaccinated women who had the virus in the past and 5,788 women who were neither vaccinated nor previously diagnosed with COVID-19.The results found that vaccination alone did not lead to increased changes to periods.
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Post-COVID dyspnea: prevalence, predictors, and outcomes in a longitudinal, prospective cohort - BMC Pulmonary MedicineBackground The pathophysiology, evolution, and associated outcomes of post-COVID dyspnea remain unknown. The aim of this study was to determine the prevalence, severity, and predictors of dyspnea 12 months following hospitalization for COVID-19, and to describe the respiratory, cardiac, and patient-reported outcomes in patients with post-COVID dyspnea. Methods We enrolled a prospective cohort of all adult patients admitted to 2 academic hospitals in Vancouver, Canada with PCR-confirmed SARS-CoV-2 during the first wave of COVID between March and June 2020. Dyspnea was measured 3, 6, and 12 months after initial symptom onset using the University of California San Diego Shortness of Breath Questionnaire. Results A total of 76 patients were included. Clinically meaningful dyspnea (baseline score | 10 points) was present in 49% of patients at 3 months and 46% at 12 months following COVID-19. Between 3 and 12 months post-COVID-19, 24% patients had a clinically meaningful worsening in their dyspnea, 49% had no meaningful change, and 28% had a clinically meaningful improvement in their dyspnea. There was worse sleep, mood, quality of life, and frailty in patients with clinically meaningful dyspnea at 12 months post-COVID infection compared to patients without dyspnea. There was no difference in PFT findings, troponin, or BNP comparing patients with and without clinically meaningful dyspnea at 12 months. Severity of dyspnea and depressive symptoms at 3 months predicted severity of dyspnea at 12 months. Conclusions Post-COVID dyspnea is common, persistent, and negatively impacts quality of life. Mood abnormalities may play a causative role in post-COVID dyspnea in addition to potential cardiorespiratory abnormalities. Dyspnea and depression at initial follow-up predict longer-term post-COVID dyspnea, emphasizing that standardized dyspnea and mood assessment following COVID-19 may identify patients at high risk of post-COVID dyspnea and facilitating early and effective managem
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An artificial intelligence approach for predicting death or organ failure after hospitalization for COVID-19: development of a novel risk prediction tool and comparisons with ISARIC-4C, CURB-65, qSOFA, and MEWS scoring systems - Respiratory ResearchBackground We applied machine learning (ML) algorithms to generate a risk prediction tool [Collaboration for Risk Evaluation in COVID-19 (CORE-COVID-19)] for predicting the composite of 30-day endotracheal intubation, intravenous administration of vasopressors, or death after COVID-19 hospitalization and compared it with the existing risk scores. Methods This is a retrospective study of adults hospitalized with COVID-19 from March 2020 to February 2021. Patients, each with 92 variables, and one composite outcome underwent feature selection process to identify the most predictive variables. Selected variables were modeled to build four ML algorithms (artificial neural network, support vector machine, gradient boosting machine, and Logistic regression) and an ensemble model to generate a CORE-COVID-19 model to predict the composite outcome and compared with existing risk prediction scores. The net benefit for clinical use of each model was assessed by decision curve analysis. Results Of 1796 patients, 278 (15%) patients reached primary outcome. Six most predictive features were identified. Four ML algorithms achieved comparable discrimination (P | 0.827) with c-statistics ranged 0.849–0.856, calibration slopes 0.911–1.173, and Hosmer–Lemeshow P | 0.141 in validation dataset. These 6-variable fitted CORE-COVID-19 model revealed a c-statistic of 0.880, which was significantly (P | 0.04) higher than ISARIC-4C (0.751), CURB-65 (0.735), qSOFA (0.676), and MEWS (0.674) for outcome prediction. The net benefit of the CORE-COVID-19 model was greater than that of the existing risk scores. Conclusion The CORE-COVID-19 model accurately assigned 88% of patients who potentially progressed to 30-day composite events and revealed improved performance over existing risk scores, indicating its potential utility in clinical practice.
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Study shows frequent COVID testing of nursing home staff protected residents, saved livesA new study, appearing today in the New England Journal of Medicine, shows that nursing homes that conducted staff surveillance testing more regularly during the COVID-19 pandemic experienced significantly lower rates of COVID infections and deaths among residents.
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Daily Step Counts Before and After the COVID-19 PandemicThis cohort study of US adults examines changes in physical activity following the onset of the COVID-19 pandemic.
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Research reveals substantial human cost of international COVID-19 travel and border restrictionsNew research being presented at this year's European Congress of Clinical Microbiology & Infectious Diseases (ECCMID) in Copenhagen, Denmark (April 15-18) reveals the high human costs and negative impacts of border restrictions and travel bans during the COVID-19 pandemic on citizens stranded abroad.
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Loss of smell following COVID-19 recovery: How long could it last?In a recent study posted to the Preprints with The Lancet* server, researchers in China conducted a multi-center, retrospective study to gather data on the prevalence of olfactory dysfunction (OD) after three years of recovering from coronavirus disease 2019 (COVID-19).
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