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A novel risk score for disease control prediction of Chronic rhinosinusitis
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  • Lijie Jiang,
  • Kanghua Wang,
  • Tengjiao Lin,
  • Yifeng Jiang,
  • Wenxiang Gao,
  • Cong Li,
  • Zhaoqi Huang,
  • Zhiyin Nie,
  • Chuxin Chen,
  • Rui Zheng,
  • Yueqi Sun,
  • Jianbo Shi,
  • Yinyan Lai
Lijie Jiang
Sun Yat-sen University First Affiliated Hospital

Corresponding Author:[email protected]

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Kanghua Wang
The Seventh Affiliated Hospital Sun Yat-sen University
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Tengjiao Lin
Guangzhou University of Traditional Chinese Medicine First Affiliated Hospital
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Yifeng Jiang
Sun Yat-sen University First Affiliated Hospital
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Wenxiang Gao
Sun Yat-sen University First Affiliated Hospital
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Cong Li
Sun Yat-sen University First Affiliated Hospital
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Zhaoqi Huang
Sun Yat-sen University First Affiliated Hospital
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Zhiyin Nie
The Seventh Affiliated Hospital Sun Yat-sen University
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Chuxin Chen
The Seventh Affiliated Hospital Sun Yat-sen University
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Rui Zheng
Third Affiliated Hospital of Sun Yat-Sen University
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Yueqi Sun
The Seventh Affiliated Hospital Sun Yat-sen University
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Jianbo Shi
Sun Yat-sen University First Affiliated Hospital
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Yinyan Lai
Sun Yat-sen University First Affiliated Hospital
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Abstract

Abstract Objectives: To assess the impact of risk factors on the disease control among CRS patients, following 1 year of functional endoscopic sinus surgery (FESS), and combining the risk factors to formulate a convenient, visualized prediction model. Design: A retrospective and nonconcurrent cohort study Setting and Participants: A total of 325 patients with Chronic rhinosinusitis (CRS) from June 2018 to July 2020 at the First Affiliated Hospital, the Third Affiliated Hospital, and the Seventh Affiliated Hospital of Sun Yat-sen University. Main Outcomes Measures: Outcomes were time to event measures: the disease control of CRS after surgery 1 year. The presence of nasal polyps, smoking habits, allergic rhinitis (AR), the ratio of tissue eosinophil (TER), and peripheral blood eosinophil count (PBEC)and asthma was assessed. The logistic regression models were used to conduct multivariate and univariate analyses. Asthma, TER, AR, PBEC were also included in the nomogram. The calibration curve and AUC (Area Under Curve) were used to evaluate the forecast performance of the model. Results: In univariate analyses, most of the covariates had significant associations with the endpoints, except for age, gender, and smoking. The nomogram showed the highest accuracy with an AUC of 0.760 (95% CI, 0.688-0.830) in the training cohort. Conclusions: In this cohort study that included the asthma, AR, TER, PBEC had significantly affected the disease control of CRS after surgery. The model provided relatively accurate prediction in the disease control of CRS after FESS and served as a visualized reference for daily diagnosis and treatment.
03 Jan 2022Submitted to Clinical Otolaryngology
08 Jan 2022Submission Checks Completed
08 Jan 2022Assigned to Editor
09 Jan 2022Reviewer(s) Assigned
13 Feb 2022Review(s) Completed, Editorial Evaluation Pending
14 Feb 2022Editorial Decision: Revise Major
09 Mar 20221st Revision Received
18 Mar 2022Assigned to Editor
18 Mar 2022Submission Checks Completed
20 Mar 2022Reviewer(s) Assigned
23 Mar 2022Review(s) Completed, Editorial Evaluation Pending
27 Mar 2022Editorial Decision: Revise Major
30 Mar 20222nd Revision Received
05 Apr 2022Submission Checks Completed
05 Apr 2022Assigned to Editor
02 May 2022Reviewer(s) Assigned
17 May 2022Review(s) Completed, Editorial Evaluation Pending
22 May 2022Editorial Decision: Accept
Sep 2022Published in Clinical Otolaryngology volume 47 issue 5 on pages 568-576. 10.1111/coa.13949