Medical and surgical treatment outcomes in patients with chronic rhinosinusitis and immunodeficiency: a systematic review
Bibliographic record
Abstract
BACKGROUND: Immunodeficiency is a risk factor for recalcitrant chronic rhinosinusitis (CRS). Currently, there is no consensus on effective treatment modalities for immunodeficient CRS patients. This review aims to evaluate the existing evidence on the treatment outcomes and its limitations in patients with CRS and immunodeficiency. METHODS: MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched from inception to April 2019 for studies reporting measurable medical or surgical treatment outcomes for adult patients with CRS and underlying primary or secondary immunodeficiency. RESULTS: Of the 2459 articles screened, 13 studies met the inclusion criteria: 2 prospective double-blind placebo-controlled trials, 2 prospective case-control studies, 2 prospective cohort studies, and 7 case series. The high degree of study heterogeneity precluded a meta-analysis. Antibiotic monotherapy was not linked with significant improvement in clinical, radiographic, or endoscopic outcomes. Immunoglobulin replacement therapy may potentially reduce the frequency of acute or chronic sinusitis in patients with primary immunodeficiency (PID) but may not improve their sinonasal symptoms. Outcomes from endoscopic sinus surgery (ESS) were reported in 8 studies, which found that surgery was linked with improvement in symptoms, disease-specific quality of life, endoscopy scores, and radiographic scores. The average reported ESS revision rate was 14%. CONCLUSION: Patients with CRS and immunodeficiency likely benefit from ESS based on the available evidence. Data supporting medical therapy in this targeted population is limited overall, but there may be a potential role for immunoglobulin therapy in patients with PID 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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".