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Record W4323310479 · doi:10.5195/ijms.2022.1832

Hearing Loss After COVID-19 Vaccines: A Systematic Review and Meta-Analysis

2023· review· en· W4323310479 on OpenAlexaboutno aff
Khaled Albakri, Yasmeen Jamal Alabdallat, Omar Ahmed Abdelwahab, Mohamed Diaa Gabra, Mohamed H. Nafady, Ebraheem Albazee

Bibliographic record

VenueInternational Journal of Medical Students · 2023
Typereview
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHearing lossObservational studyVertigoMeta-analysisMEDLINESystematic reviewAudiologyCoronavirus disease 2019 (COVID-19)TinnitusPediatricsSurgeryInternal medicineDisease

Abstract

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ABSTRACT. Background: Hearing loss is generally classified as conductive hearing loss (CHL) and sensory-neural hearing loss (SNHL). It has been reported that COVID-19 infection may affect the vestibular-hearing system causing dizziness, tinnitus, vertigo, and hearing impairment. However, other studies reported that COVID-19 did not lead to significant hearing impairment. Many studies in the literature have reported hearing loss as a complication of COVID-19 vaccines. However, no systematic review or meta-analysis summarizes the literature on this topic. Method: We performed a comprehensive search for the following databases: PubMed, Cochrane (Medline), Web of Science, and Scopus. All studies published in English till October 2022 were included. These include case reports, case series, prospective and retrospective observational studies, and clinical trials reporting hearing loss following COVID-19 vaccines. Newcastle Ottawa scale (NOS) was used to assess the risk of bias for observational studies. NIH tools were used for non-controlled before and after clinical trials and case reports and case series. A third author solved any disagreements. We analyzed the data using SPSS Software version 26. Results: A total of 630 patients were identified, with a mean age of 57.3 that ranged from 15 to 93 years old. The majority of the patients were females, 339 (53.8%). In addition, 328 out of 609 vaccinated patients took the Pfizer-BioNTech BNT162b2 vaccine, while 242 (40%) took the Moderna COVID-19 vaccine. The mean time from vaccination to hearing impairment was 6.2, ranging from a few hours to one month after the last dose. Most patients reported unilateral sensorineural hearing loss post-vaccination 593 (94.1%). In order to report the fate of cases, a follow-up was initiated with a mean of 15.6 and a range of 2 to 63 days after the initiation of the treatment. A total of 20 patients were fully recovered, and 11 reported no response. Three out of 328 patients who took the Pfizer-BioNTech BNT162b2 vaccine fully recovered, while five reported partial recovery. According to the chi-squared test, there is a statistically significant difference between patients in terms of fate and the type of COVID-19 vaccination (P-value = 0.001) while reporting no significant difference in dose number prior to the onset of the symptoms (P-value = 0.65) and gender (P-value = 0.4). The ANOVA test was conducted to compare vaccine types and the number of doses in terms of mean time from vaccination to hearing impairment onset. The results found a significant difference between vaccine types (P-value < 0.000) while showing no significance in terms of the number of doses prior to the onset (P-value = 0.6). Conclusion: There is a statistically significant difference between patients in terms of fate and the type of COVID-19 vaccination while reporting no significant difference in dose number prior to the onset of the symptoms and gender. Further, we concluded that there is a significant difference between vaccine types while showing no significance in terms of the number of doses prior to the onset.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.670
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0040.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.165
GPT teacher head0.480
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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