Editorial: Exploring neurotological health concerns post-COVID-19 infection
Bibliographic record
Abstract
Determining causality as to the effects of SARS-CoV-2 infection is a challenge met in the study of any infectious disease agent. In the face of an inability to gather evidence from well-controlled interventional studies, multiple complimentary lines of evidence are necessary to attribute health effects directly to microbial infection. Causal inference frameworks are drawn upon; mechanistic evidence that harkens back to Koch's postulates is necessary; and large, well-controlled observational study designs provide a primacy of evidence. Each of these modes of evidence has contributed to our understanding of COVID-19's neurotologic manifestations to date. Even in a post-pandemic reality, achieving a comprehensive understanding of the virus' effects and the mechanisms by which these are exerted is crucial from a public health standpoint. Our population has unprecedented vulnerability to global pandemics.A cornerstone of understanding the effects of SARS-CoV-2 infection on human health is precise characterization of disease presentation. A wide body of research ranging across medical specialty disciplines endeavors to do just this. Researchers studying the effects of the virus in the short-and long-term post-infection have elucidated nuances of its presentation and provided insight on how these can be measured and followed. Concerning the virus' neurotologic sequelae, Peron and colleagues provide important insights into the audiometric profile of SSNHL related to SARS-CoV-2 infection. Their prospective cohort study assessed patients presenting with SSNHL for COVID infection via PCR testing and symptomatology, and found a higher incidence of bilateral simultaneous SSNHL among patients with COVID infection and severe symptoms. These findings have important implications for the work-up of patients presenting with bilateral SSNHL, given that a proportion of these may represent COVID-infected individuals. From a vestibular standpoint, Campelo Corrêa et al. demonstrate the feasibility of assessing long-term balance impairment following viral infection using smartphone-based apps. They used smartphone inertial sensors to evaluate balance in patients with long COVID-19, finding greater postural instability on static balance tasks in these patients compared to controls. Though this approach is not specific to the assessment of patients with a history of SARS-CoV-2 infection, the study provides insights into its applicability in this population. These types of studies play a pivotal role in achieving a comprehensive understanding of the virus' effects. With large segments of the global population suffering long-term effects of SARS-CoV-2 infection, this knowledge is ever important.Complimentary and equally necessary to clinical, observational research are mechanistic studies. SARS-CoV-2 has been shown to exert its multi-system effects through a combination of mechanisms. These include but are not limited to direct viral entry in cells of target tissues, vascular endothelial injury driving inflammation and thrombosis -which may drive multi-organ ischemic injury -and immune dysregulation. The latter two effects have been long-theorized as accounting for certain presentations of non-infectious related audiovestibular dysfunction (for example, autoimmune or steroid-responsive inner ear disease, and possibly some cases of idiopathic sudden sensorineural hearing loss). Recent research studying inner ear cells collected from the vestibular end organs at the time of surgical labyrinthectomy have demonstrated that these cells express the membrane receptors necessary for SARS-CoV-2 infection. Additional work has demonstrated other possible mechanistic pathways for the neurotologic effects of the virus; for example, SARS-CoV-2 particles have been demonstrated in middle ear effusions following viral infection.Xinxin Li and colleagues explore this phenomenon in their study included as part of this Topic.Another class of negative health outcomes that emerged during the pandemic are those with possible links to COVID-19 vaccination, rather than to infection itself. The most consistently recognized serious adverse effects of the vaccine are thrombosis and thrombocytopenia, both of which are rare events. Though many practicing otolaryngologists have anecdotal reports of patients experiencing sudden sensorineural hearing loss or vertigo following COVID vaccination, these of course are unsubstantiated and represent the lowest quality of evidence The study "Comparison of the rates of emergent otologic adverse events following mRNA COVID-19 versus influenza vaccination: a matched cohort analysis" by Munjal et al rigorously addresses this potential association, with surprising results. This matched cohort study included a total of 42,859 individuals receiving the COVID-19 vaccine or any pre-pandemic influenza vaccine, and found no difference between the two groups in the odds of any hearing loss, sudden hearing loss, tinnitus, and otalgia. While the odds of aural fullness were significantly higher among the COVID vaccinated cohort compared to the influenza vaccinated cohort, the odds of vertigo were significantly lower among COVID-vaccinated individuals.To summarize: the neurotologic manifestations of SARS-CoV-2 infection and vaccination represent a still-rapidly evolving field at the intersection of clinical otology/neurotology and infectious diseases. Lessons from this and previous pandemics make it increasingly clear that both observational and mechanistic research are essential to delineate the pathways by which COVID-19 and its prevention strategies may affect human health, including the auditory and vestibular systems. Rigorous clinical and laboratory-based studies are key to distinguishing viral mechanisms of injury from coincidental associations. The contributions assembled in this Research Topic collectively advance our understanding of these complex relationships -ranging from clinical characterizations and diagnostic insights to explorations of underlying mechanisms -and highlight the importance of continued systematic inquiry to inform patient care and future public health preparedness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.022 | 0.026 |
| Insufficient payload (model declined to judge) | 0.015 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".