Chronic Otitis Media in Patients with Chronic Rhinosinusitis: A Systematic Review
Bibliographic record
Abstract
Introduction: Chronic otitis media (COM) and chronic rhinosinusitis (CRS) are two of the most common otolaryngological disorders. CRS and COM share pathophysiological mechanisms such as bacterial infection, biofilm, and the persistence of the obstruction state of ventilation routes. The purpose of this systematic review was to evaluate all available information on the association between COM and CRS. Methods: The protocol of this investigation was registered on PROSPERO in November 2022. Pubmed, Scopus, Web of Science, and Cochrane databases were systematically searched according to the PRISMA statement. Results: After the application of inclusion-exclusion criteria, four manuscripts with adequate relevance to this topic were included in the review. The study population consisted of 20,867 patients with a diagnosis of CRS, of whom 991 were also diagnosed with COM (4.75%). Conclusions: The included studies have shown that CRS has become significantly associated with COMas: a global inflammatory process that involves the epithelium in both the middle ear and upper airway. The identification of a relationship between CRS and COM may contribute to preventing chronic inflammatory conditions through the early management of the associated disease. Further, carefully designed studies are necessary to demonstrate the relationship between COM and CRS.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".