Predictive value of computed tomography in the recurrence of chronic rhinosinusitis with nasal polyps

Background Chronic rhinosinusitis with nasal polyps (CRSwNP) is a nasal disease with a high tendency for recurrence. The aim of this study was to compare the use of computed tomography (CT) scan with other clinical parameters in predicting the recurrence of CRSwNP. Methods A total of 272 consecutive CRSwNP patients undergoing endoscopic functional sinus surgery were recruited. The demographic characteristics and clinical parameters, including CT scores, level of exhaled nitric oxide, and peripheral eosinophilia, were recorded. The degree of infiltration of inflammatory cells in the sinus mucosa was evaluated. Results Two hundred thirty of the 272 patients completed the study (118 patients with recurrence and 112 patients with no recurrence). The average follow‐up time was 24 months after the first surgery. The 2 groups were not significantly different with respect to age, gender distribution, comorbid allergy, exhaled oral fractional exhaled nitric oxide levels, nasal obstruction/runny nose/headache/facial pain scores, Lund‐Mackay score, peripheral eosinophil percentage, and peripheral eosinophil absolute count. The onset of surgical history and asthma, visual analog scores of CRS, anosmia score, ratio of total ethmoid sinus scores for both sides and maxillary sinus score for both sides (E/M ratio), Lund‐Kennedy score, tissue eosinophil percentage, and tissue eosinophil absolute count were significantly higher in the recurrence group. The E/M ratio showed high accuracy as a predictor for CRSwNP recurrence. The cut‐off point of 2.55 for E/M ratio indicated the highest predictive value of CRSwNP recurrence. Conclusion The E/M ratio is a useful predictor for the recurrence of CRSwNP in the Chinese population..

Medienart:

E-Artikel

Erscheinungsjahr:

2019

Erschienen:

2019

Enthalten in:

Zur Gesamtaufnahme - volume:9

Enthalten in:

International Forum of Allergy & Rhinology - 9(2019), 11, Seite 1236-1243

Beteiligte Personen:

Meng, Yifan [VerfasserIn]
Zhang, Luo [VerfasserIn]
Lou, Hongfei [VerfasserIn]
Wang, Chengshuo [VerfasserIn]

Anmerkungen:

© 2019 ARS‐AAOA, LLC

Umfang:

8

doi:

10.1002/alr.22355

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

WLY001251236