[Artificial intelligence-assisted prediction of olfactory disorders in patients with chronic rhinosinusitis].
Lin Chuang Er Bi Yan Hou Tou Jing Wai Ke Za Zhi
; 37(11): 871-877;885, 2023 Nov.
Article
em Zh
| MEDLINE
| ID: mdl-38114440
ABSTRACT
Objective:
To analyze the influencing factors and perform the prediction of olfactory disorders in patients with chronic rhinosinusitisï¼CRSï¼ based on artificial intelligence.Methods:
The data of 75 patients with CRS who underwent nasal endoscopic surgery from October 2021 to February 2023 in the Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-sen University were analyzed retrospectively. There were 53 males and 22 females enrolled in the study, with a median age of 42.0 years old. The CRS intelligent microscope interpretation system was used to calculate the proportion of area glands and blood vessels occupy in the pathological sections of each patient, and the absolute value and proportion of eosinophils, lymphocytes, plasma cells and neutrophils. The patients were grouped according to the results of the Sniffin' Sticks smell test, and the clinical baseline data, differences in nasal mucosal histopathological characteristics, laboratory test indicators and sinus CT were compared between the groups. Determine the independent influencing factors of olfactory disorders and receiver operating characteristic curvesï¼ROCï¼ were used to evaluate the performance of the prediction model. Statistical analysis was performed using SPSS 25.0 software.Results:
Among the 75 CRS patients, 25 casesï¼33.3%ï¼ had normal olfaction and 50 casesï¼66.7%ï¼ had olfactory disorders. Multivariate Logistic regression analysis showed that tissue eosinophils percentageï¼OR=1.032, 95%CI 1.002-1.064, P=0.036ï¼, Questionnaire of olfactory disorders-Negative statementï¼QOD-NSï¼ï¼OR=1.079, 95%CI 1.004-1.160, P=0.040ï¼ and Anterior olfactory cleft scoreï¼AOCSï¼ï¼OR=2.672, 95%CI 1.480-4.827, P=0.001ï¼ were independent risk factors for olfactory disorders in CRS patients. Further research found that the area under the ROC curveï¼AUCï¼ of the combined prediction model established by the tissue eosinophil percentage, QOD-NS and AOCS was 0.836ï¼95%CI 0.748-0.924, P<0.001ï¼, which is better than the above single factor prediction model in predicting olfactory disorders in CRS.Conclusion:
Based on pathological artificial intelligence, tissue eosinophil percentage, QOD-NS and AOCS are independent risk factors for olfactory disorders in CRS patients, and the combination of the three factors has a good predictive effect on CRS olfactory disorders.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Sinusite
/
Rinite
/
Pólipos Nasais
/
Rinossinusite
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Transtornos do Olfato
Limite:
Adult
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Female
/
Humans
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Male
Idioma:
Zh
Revista:
Lin Chuang Er Bi Yan Hou Tou Jing Wai Ke Za Zhi
Ano de publicação:
2023
Tipo de documento:
Article