Cryoablation for the treatment of chronic rhinitis: A systematic review
Bibliographic record
Abstract
BACKGROUND: ClariFix is a novel intranasal cryotherapy device developed for clinic-based cryosurgical ablation of the posterior nasal nerves region. As a relatively new technology, there is a paucity of studies within the literature assessing the efficacy and safety profile of ClariFix for chronic rhinitis. METHODS: A systematic review was completed in accordance with PRISMA guidelines. Databases searched included: Ovid Medline, Ovid EMBASE, Pubmed, Cochrane and Web of Science. Inclusion criteria consisted of studies investigating the use of ClariFix in chronic rhinitis (i.e., allergic and non-allergic rhinitis) in patients of all ages. RESULTS: The initial search identified 1110 studies. Final analysis consisted of 8 articles, evaluating a total of 472 patients. The data showed a significant reduction in scores post-treatment across all studies based on validated outcome measures. In all studies, at all time intervals, there was a significant improvement in outcome scores from baseline. Minor adverse effects included post-procedural pain and discomfort, headache and palate numbness. No major adverse events were identified. CONCLUSION: ClariFix is a novel intranasal cryotherapy device that was introduced in Canada in 2021. This is the first systematic review evaluating its efficacy and safety profile. Across all studies, there was a significant reduction in validated outcome scores at multiple time intervals. Further, the treatment is safe with only minor adverse effects reported by patients. Overall, the consensus from this study highlights an apparent benefit in using this intervention for chronic rhinitis that is refractory to medical management.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".