Browse the corpus
Walk the evidence base by book and chapter — the raw source passages that ground Ask, Differential, and the rest.
1 passage
BACKGROUND: Concha bullosa (CB) varies widely in reported prevalence, laterality, and subtype distribution, underscoring the need for a meta-analysis. This meta-analysis aimed to derive pooled estimates of CB prevalence, sex distribution, laterality, morphological variants, and the concha bullosa pneumatization index (CBPI). MATERIALS AND METHODS: We conducted a meta-analysis in accordance with PRISMA guidelines. Independent raters screened relevant studies and extracted data. Eligible studies included human research using high-resolution imaging or cadaveric dissection that reported effect sizes together with measures of variance. Risk of bias was evaluated using the AQUA tool. Meta-analyses were performed in R (v4.5.1); heterogeneity was assessed using I2 and Cochran's Q, and publication bias was evaluated with funnel plots and Egger's test. RESULTS: Thirty-seven studies (n = 16,753) met the inclusion criteria, yielding a sample approximately 25% larger than that of the meta-analysis by Valenzuela- Fuenzalida et al. (2023). The pooled prevalence of CB was 36% (95% CI: 30-43%). Regional estimates were 31% in Asia, 42% in the Americas, 47% in Europe, and 44% in Africa. Sex-stratified analysis (16 studies, n = 9,392) showed similar prevalence in males (33%) and females (38%), although regional analyses indicated relatively higher prevalence among females in Asia and the Middle East. Laterality analysis (n = 24,532) demonstrated comparable prevalence of unilateral (21%) and bilateral (17%) forms. Morphological subtype analysis (n = 5,265) showed that the lamellar (19%) and extensive (16%) variants were significantly more common than the bulbous type (8%). Pneumatized conchae contralateral to septal deviation showed a significantly higher CBPI (mean difference 2.07, 95% CI: 1.19-2.96). CONCLUSIONS: This meta-analysis derived pooled estimates of CB prevalence, sex distribution, laterality, subtype distribution, and the CBPI. These findings support standardized and personalized management protocols.