New York City and a big part of the country are quickly coming back to almost normal, as case numbers, hospitalizations and deaths from COVID-19 are quickly dropping. There is still some fear mongering going on, especially when it comes to the so-called new strains of the virus, which are now dominating. The good news, however, is the newest research data suggest that the immunity obtained from Pfeizer and Moderna vaccines are also protective against the new strains. That does not mean that the SARS-CoV-2 virus may not at some point mutate in a way that allows it to escape the antibody response created by those vaccines; but even if that were to be the case, as we now know through research on this virus, our cellular immune system also has long-term memory that can be effective in preventing infection and especially in keeping the severity of any infection limited.
Within such a context a recently published model of COVID-19 concluded that the virus naturally induces two kinds of immunity: a shorter-term immunity that prevents infection and a much longer-term immunity which efficiently combats severity of COVID-19.1 Analyzing publicly available COVID-19 data, CHR’s Medical Director and Chief Scientist, Norbert Gleicher, MD, who started his academic research career in immunology, independently, came to the same conclusion, furthermore demonstrating in a just submitted paper that different strains of the virus apparently have different abilities in inducing these two kinds of protective community immunity.2
Because of quicker waning disease-preventing immunity it should not surprise that the CEO of Pfizer recently was quoted as saying that “there likely will be a need for a third dose of the vaccine as a “refresher-dosage” within (approximately) one year from initial immunization.3 But even without such a booster shot, those who will be infected will have only relatively milder disease.
Other people receiving a COVID vaccine cannot disrupt your menstrual cycle as an unvaccinated person, as rumors on the Internet have suggested. Under rare circumstances getting vaccinated may, however, affect a woman’s menstrual cycle, and that should not surprise. Just think how easily menstrual cycles are affected by travel or by getting the flu. A still unpublished study from Israel’s famous Hadassah Hospital in Jerusalem also showed no supportive evidence for another broadly distributed false rumor on social media, that COVID adversely affects female fertility.
Getting vaccinated can, however, affect your mammogram. Vaccinations in the upper arm can on rare occasions lead to enlargement of axillary lymph nodes on the side of injection and these lymph nodes can be erroneously read as suspicious by radiologists. Apparently second vaccinations more often than first vaccination can also lead to side effects and some data suggest that this may happen more often to women than men. The most common side effects kick in roughly 24 hours after receiving shots, with feeling fatigued and “achy” feverish, like when having the flu. But the fever usually breaks quickly and, once that happens, people feel “great,” even better than usual. These kinds of responses are a good sign and suggest that the immune system has learned from the first vaccination how to respond to the virus.
You, however, must be careful if you have a weakened immune system, either due to disease or due to prolonged and powerful immune system suppression by medications. In such individuals the immune system response to vaccines can be low to insufficient and other remedies are being investigated how to strengthen the immune response, with monoclonal antibody treatments being the most promising. For cancer patients on chemotherapy, organ transplant recipients on anti-rejection drugs and individuals on immunosuppressive medications because of autoimmune and/or inflammatory diseases it, therefore, is important to check their immunity after COVID vaccinations and not to automatically assume to be protected.
But even in fully immuno-competent people, vaccination does not always work. Nothing in medicine, indeed, works in 100% of cases but practical life-experience with good COVID vaccines now has demonstrated that a full course protects roughly 95% of people from infection. The CDC identified only ca. 5800 breakthrough cases among 66 million vaccinated individuals, representing a rate of only ca. 0.008% who experienced positive COVID-19 tests after being full vaccinated. On a statistical probability level, this is approaching the chance of winning the lottery! Interestingly, as recently reported in JAMA, women are more easily infected than men, but men are more frequently dying,4 raising the question why?
One could hypothesize that women, having immune systems with enormous potential capacity for tolerance (the fetus is a very rapidly growing solid semi-allograft that must be tolerated for 9 months) may be at greater risk to be infected for that reason. That tolerance, however, also provides their immune system with greater capabilities to control overreactions of their immune systems, which, as we now have learned, is frequently the cause of deaths in severe COVID-19 cases. And here is one more reason why getting COVID-19 as a man is not such a great thing: The risk of erectile dysfunction in young men who develop COVID is ca. elevated sixfold.5
When it comes to the most basic question how the SARS-CoV-2 virus affects pregnancy, the picture is increasingly confusing. Early reports at the beginning of the pandemic were reassuring, alleging a surprisingly benign course of disease for pregnant women. Those reports were, indeed, quite surprising because they suggested that COVID-19 was more benign than the classical flu, which for decades has been known to be “more dangerous” in pregnancy than in the non-pregnant state.
But then the rollercoaster began: Increasingly reports appeared coming to the exactly opposite conclusion, suggesting that COVID-19 in pregnancy was a significantly more severe a disease. For example, investigation of a large national data base reported by researchers from Boston, MA, demonstrated significantly higher maternal and neonatal complications in COVID patients. Among
406446 women hospitalized for childbirth, 6380 (1.6%) had a diagnosis of COVID, 212 (3.3%) required ICU care and 86 (1.3%) mechanical ventilation. Though their mortality was low, it still significantly exceeded the mortality of non-COVID patients (141 vs 5/100000 women). Also higher were myocardial infarctions, venous thromboembolism, preeclampsia, and preterm delivery, though stillbirth was not increased.6
An even more recent multinational cohort study came to very similar conclusion, in the paper summarized as, “COVID-19 in pregnancy was associated with consistent and substantial increases in severe maternal morbidity and mortality and neonatal complications when pregnant women with and without COVID-19 diagnosis were compared.”7 A commentary in Science was headlined, “Clear link emerges between COVID-19 and pregnancy complications.8
Things, therefore, appeared clear in reaching the conclusion that COVID-19 in pregnancy was a significantly more severe disease than in the non-pregnant state, – when investigators from Texas again reported completely contrarian data: In a retrospective cohort study, pregnant patients hospitalized with a diagnosis of COVID had a lower risk of mortality than non-pregnant COVID-19 patients (1% vs.3.5%). Moreover, median time between admission to the hospital and death was 18 days in pregnant and 12 days in non-pregnant women, also suggesting more virulent disease in non-pregnant COVID patients.9
Confused? You are not alone! Let’s therefore try to make some sense of these contradictory data. All studies reported and below referenced, are observational studies. They, therefore, are not controlled for potential co-variables. Here are examples why this is important: One example is the well-known association of obesity with poorer outcome in severe COVID-19 cases. If a cohort of patients, therefore, has overrepresentation of obese women, this cohort will have worse outcome than a group of women with less obesity. A well-controlled study, therefore, should adjust outcomes for weight. Many other medical conditions have also been associated with increased mortality and therefore also should be adjusted for, as do certain racial and ethnic backgrounds. Such adjustments are, however, often difficult to make and, when avoided, can lead to significant biases.
The authors of the last study, indeed, cite such biases as the motivation for heir own study.9 They compared 1062 pregnant to 9815 non-pregnant women hospitalized with COVID-19 viral pneumonia, and recognized that pregnant patients were younger and more likely had public insurance than non-pregnant controls (i.e., were likely of lower socio-economic means) and, therefore, should be at increased risk for COVID-19. They, however, also had fewer co-morbidities like hypertension, diabetes, pulmonary diseases, and obesity and based on these co-variables, should be expected to have lower COVID-19 rates and less severe disease. Though recognizing and at least pointing out these outcome differences, they, like in previously quoted studies, were not statistically adjusted and, therefore, must be interpreted with great caution.
The difference in outcomes was, however, remarkable: Deaths occurred in only 0.8% 0f pregnant but in 3.5% of non-pregnant hospitalized women and, maybe even more remarkably, median time to deaths was 18 and 12 days, respectively, reemphasizing how more serious COVID-19 was in non-pregnant women. This obvious difference in severity of disease between the two studied groups of patients is, however, another obvious potential cause of bias because what these numbers suggest is that pregnant women may have been admitted to the hospital earlier in the disease (which would not surprise, considering pregnancy is currently considered a high-risk situation in association with COVID-19).
The authors, therefore, may have, once more, compared apples with oranges, demonstrating very well why observational studies must be interpreted with caution. The truth, therefore, is that of this moment it is unclear whether pregnancy affects COVID-19 to the good, bad or neither way. The likely “truth” is that, overall, there may be no big difference but, based on specific patient characteristics, there, indeed, may be significant differences. In other words, for at least, a likely very small group of women, COVID-19 may be especially dangerous. Now we need to learn who these women are. Until this becomes known, it appears prudent to continue treating pregnant women as high-risk patients when affected by COVID-19. Moreover, women trying to conceive should continue to be encouraged to get vaccinated before conception.
Newly available data also offer new insights into benefits mothers and their offspring derive from anti-COVID vaccines. Because of speed of development, politization of this issue and frequent misrepresentations by media claiming highly exaggerated risks, the public, understandably, has remained somewhat skeptical and concerned about safety. Remarkably, especially the two mRNA vaccines have proven to be unexpectedly effective and safe,10 with more traditional vaccines not far behind.11 A second major concern that pregnant women may produce inadequate immune response to vaccines can also be laid to rest since recent publications demonstrated robust maternal immune responses and transplacental passive transfer of immunity and through lactation to offspring.12,13 The earlier the mother receives the vaccine the better the immunity will be in offspring and immunity after a second shot (in 2-shot vaccines) improves the likelihood of good antibody levels in newborns.13
Norbert Gleicher, MD, leads CHR’s clinical and research efforts as Medical Director and Chief Scientist. A world-renowned specialist in reproductive endocrinology, Dr. Gleicher has published hundreds of peer-reviewed papers and lectured globally while keeping an active clinical career focused on ovarian aging, immunological issues and other difficult cases of infertility.
DISCOVER YOUR TREATMENT OPTIONS
