The Impact of Sinus Surgery for Chronic Rhinosinusitis on Concomitant Depression and Anxiety Symptoms: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND: Both anxiety and depression are prevalent among patients with chronic rhinosinusitis (CRS) and associated with poorer outcomes following treatment for CRS. However, the impact of treatment on CRS on mental health remains uncertain. Therefore, this study seeks to evaluate if surgical intervention for CRS may alleviate comorbid depression and anxiety. METHODS: PubMed, Embase, and Scopus databases were searched for retrospective and prospective cohort studies, cross-sectional studies, and randomized controlled trials relating to CRS treatment using sinus surgery from inception to April 30, 2024, using the Population, Intervention, Comparison, and Outcomes (PICO) framework. Three blinded reviewers selected observational studies and randomized controlled trials investigating levels of depression and anxiety pre- and post-surgical treatment of CRS. Eleven studies comprising 3067 patients were included, of which five studies were quantitatively analyzed. After which, data were extracted from included articles into a structured proforma and the Newcastle-Ottawa Scale was used to evaluate study bias, following Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines and a PROSPERO-registered protocol (CRD42022351855). Meta-analyses of the ratio of means were conducted in a random-effects model. RESULTS: Overall, sinus surgery was associated with significant improvement in test scores of depression (ratio of means (ROM) = 1.47, 95% confidence interval [CI] = 1.03‒2.10), anxiety (ROM = 1.10, 95% CI = 0.81‒1.49), and quality of life markers, which are closely correlated to mental health outcomes. CONCLUSIONS: Sinus surgery for CRS may improve mental health outcomes (both depression and anxiety) for patients.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.042 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".