Blood Eosinophil Percentage and Improved Sinus CT Score as Diagnostic Tools for ECRS.
OTO Open
; 8(1): e106, 2024.
Article
em En
| MEDLINE
| ID: mdl-38223492
ABSTRACT
Objective:
Differentiating 2 types of chronic rhinosinusitis with nasal polyps (CRSwNP) is important for the treatment. The current diagnostic methods using single indicators, including peripheral blood eosinophils and traditional sinus computed tomography (CT) scores, are not accurate. In this study, we aimed to investigate the diagnostic value of combining peripheral blood eosinophils and improved sinus CT scores for eosinophic chronic rhinosinusitis (ECRS). StudyDesign:
Retrospective cohort.Setting:
Tertiary medical center.Methods:
We conducted a study involving 81 patients with CRSwNP. Peripheral blood samples were collected from the non-ECRS and ECRS groups. Improved three-dimensional volume image analysis and Lund-Mackay scoring system were performed to quantify the thickening of sinus mucosa. Multivariate binary logistic regression analysis was carried out to detect the predictive value of the scoring indicators. For significant indexes, receiver operating characteristic (ROC) curve analysis was applied.Results:
The ECRS group had higher levels of blood eosinophil percentage and count, ethmoid sinus score, total sinus score, the ratio of ethmoid sinus score and maxillary sinus score, and the difference between ethmoid and maxillary score, compared to the non-ECRS group (P < 0.05). Binary logistic regression analysis demonstrated that both blood eosinophil percentage and the improved E - M score (subtraction of ethmoid and maxillary sinus scores) were significant predictors of ECRS diagnosis (P < .01). ROC curve analysis indicated that the combination of improved E - M score and blood eosinophil percentage had a higher diagnostic value compared to either factor alone (area under the curve = 0.874).Conclusion:
Our study suggested the combination of improved total ethmoid sinus-maxillary score and blood eosinophil percentage is more accurate in predicting the diagnosis of ECRS.
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Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article