Airway Sequelae After Mechanical Ventilation for COVID-19: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: The epidemiology, morbidity, and burden of disease related to airway sequelae associated with invasive mechanical ventilation in the context of the COVID-19 pandemic remain unclear. OBJECTIVE: This scoping review aims to summarize the current knowledge regarding airway sequelae after severe SARS-CoV-2 infection. This knowledge will help guide research endeavors and decision-making in clinical practice. METHODS: This scoping review will include participants of all genders, and no particular age group who developed post-COVID-19 airway-related complication will be excluded. No exclusion criteria will be applied from country, language, or document type. The information source will include analytical observational studies. Unpublished data will not be completely covered as gray literature will be covered. A total of 2 independent reviewers will participate in the process of screening, selection, and data extraction, and the whole process will be performed blindly. Conflict between the reviewers will be solved through discussion and an additional reviewer. The results will be reported by using descriptive statistics, and information will be displayed on RedCap (Research Electronic Data Capture). RESULTS: The literature search was conducted in May 2022 in the following databases: PubMed, Embase, SCOPUS, Cochrane Library, as well as LILACS and gray literature to identify observational studies; a total of 738 results were retrieved. The scoping review will be finished by March 2023. CONCLUSIONS: This scoping review will describe current knowledge on the most frequently encountered laryngeal or tracheal sequelae in patients exposed to mechanical ventilation due to SARS-CoV-2 infection. This scoping review will find the incidence of airway sequelae post COVID-19 and the most common sequelae such as airway granuloma, vocal fold paralysis, and airway stenoses. Future studies should evaluate the incidence of these disorders. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/41811.
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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 | 0.080 | 0.069 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.015 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.068 | 0.013 |
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".