In Acta oto-laryngologica
BACKGROUND : The use of non-invasive clinical markers for predicting CRS recurrence is still not well investigated.
OBJECTIVE : The aim of this study was to investigate the comprehensive effects of non-invasive clinical markers on the recurrence of CRS with nasal polyps (CRSwNP).
MATERIALS AND METHODS : A total of 346 consecutive CRSwNP patients undergoing endoscopic functional sinus surgery were recruited. The demographic characteristics and clinical parameters were recorded. Machine learning algorithm were used for evaluating the predictive value of asthma history and blood eosinophils percentage.
RESULTS : Finally, 313/346 patients completed the study. The average follow-up time was 24 months after the first surgery. For the CRSwNP with asthma patients, the blood eosinophils percentage cut-off value was 3.7%. However, for the CRSwNP without asthma patients, the blood eosinophils percentage cut-off value was high, at 6.9%.
CONCLUSION : Combined asthma history and blood eosinophils percentage can predict CRSwNP recurrence, while asthma history can reduce the threshold of blood eosinophils percentage to predict CRSwNP recurrence.
SIGNIFICANCE : For the CRS patients, combined asthma history and blood eosinophils percentage can predict recurrence, while asthma history can reduce the threshold of blood eosinophils percentage to predict recurrence.
Wang Xiaoyan, Meng Yifan, Lou Hongfei, Wang Kuiji, Wang Chengshuo, Zhang Luo
Asthma, blood eosinophils percentage, chronic rhinosinusitis with nasal polyps, endoscopic sinus surgery, machine learning algorithm, prediction, recurrence