Bibliographic record
Abstract
OBJECTIVE: To provide a clinical summary of the Canadian clinical practice guidelines for chronic rhinosinusitis (CRS) that includes recommendations relevant for family physicians. QUALITY OF EVIDENCE: Guideline authors performed a systematic literature search and drafted recommendations. Recommendations received both strength of evidence and strength of recommendation ratings. Input from external content experts was sought, as was endorsement from Canadian medical societies (Association of Medical Microbiology and Infectious Disease Canada, Canadian Society of Allergy and Clinical Immunology, Canadian Society of Otolaryngology-Head and Neck Surgery, Canadian Association of Emergency Physicians, and Family Physicians Airways Group of Canada). MAIN MESSAGE: Diagnosis of CRS is based on type and duration of symptoms and an objective finding of inflammation of the nasal mucosa or paranasal sinuses. Chronic rhinosinusitis is categorized based on presence or absence of nasal polyps, and this distinction leads to differences in treatment. Chronic rhinosinusitis with nasal polyps is treated with intranasal corticosteroids. Antibiotics are recommended when symptoms indicate infection (pain or purulence). For CRS without nasal polyps, intranasal corticosteroids and second-line antibiotics (ie, amoxicillin- clavulanic acid combinations or fluoroquinolones with enhanced Gram-positive activity) are recommended. Saline irrigation, oral steroids, and allergy testing might be appropriate. Failure of response should prompt consideration of alternative diagnoses and referral to an otolaryngologist. Patients undergoing endoscopic sinus surgery require postoperative treatment and follow-up. CONCLUSION: The Canadian guidelines provide diagnosis and treatment approaches based on the current understanding of the disease and available evidence. Additionally, the guidelines provide the expert opinion of a diverse group of practice and academic experts to help guide clinicians where evidence is sparse.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.025 | 0.012 |
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".