Journal of Otolaryngology and Ophthalmology of Shandong University ›› 2026, Vol. 40 ›› Issue (5): 103-108.doi: 10.6040/j.issn.1673-3770.0.2025.219

• Original Article • Previous Articles    

A risk prediction model for extubation failure after tracheotomy was constructed based on the decision tree method

WEI Qianqian, WU Juan   

  1. Department of Emergency, The First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, Jiangsu, China
  • Published:2026-09-07

PDF (PC)

11

Abstract: Objective To identify the risk factors for extubation failure in patients after tracheotomy and to construct a risk prediction model based on a decision tree algorithm. Methods A total of 215 patients with tracheotomy who were hospitalized in the First Affiliated Hospital of Nanjing Medical University from February 2022 to April 2024 were retrospectively selected as the research subjects. They were divided into the successful extubation group(176 cases)and the failed extubation group(39 cases)according to whether the tracheotomy cannulas were successfully removed after the operation. Logistic regression was used to analyze and screen the related factors of postoperative extubation failure in patients with tracheotomy, and the decision tree model was constructed using R language software. Results The extubation failure rate was 18.14%; Logistic regression analysis showed that age ≥60 years, Glasgow Coma Scale(GCS)score ≤8, cough effectiveness grade 0~2, absent swallowing reflex, swallowing dysfunction, and abnormal hemoglobin levels were all independent risk factors for extubation failure after tracheotomy(P<0.05); Decision tree modeling identified swallowing reflex as the most influential factor for extubation failure in tracheotomy patients, with an information gain of 0.32; Both the logistic regression model and the decision tree model demonstrated good predictive performance for postoperative extubation failure risk, with areas under the receiver operating characteristic(ROC)curve of 0.848 and 0.823, respectively. Conclusion The construction of a risk prediction model, based on decision trees, has proven effective in the prediction ofextubation failure subsequent to tracheotomy.

Key words: Tracheotomy, Pull the tube, Risk factors, Prediction model

CLC Number: 

  • R473
[1] Jia ZY, Yi Y, Liu JH, et al. Epidemiology of hepatitis E virus in China: results from the third national viral hepatitis prevalence survey, 2005-2006[J]. PLoS One, 2014, 9(10): e110837. DOI:10.1371/journal.pone.0110837
[2] Toker A, Hayanga JA, Dhamija A, et al. Tracheotomy, closure of long-term tracheostomy and standard tracheal segmental resections[J]. J Thorac Dis, 2020, 12(10): 6185-6197. DOI:10.21037/jtd.2020.02.41
[3] Ustrell S, Simmons JK, Henkle G, et al. Revision tracheotomy complicated by history of follicular B-cell lymphoma[J]. Ear Nose Throat J, 2023, 102(9_suppl): 16S-19S. DOI:10.1177/01455613231189229
[4] 陈萍, 王芳, 张文静. 影响气管切开重症患者拔管的风险因素及预防护理策略[J]. 齐鲁护理杂志, 2024, 30(2): 99-102. DOI:10.3969/j.issn.1006-7256.2024.02.032
[5] 丁克元, 李贤英, 王捷, 等. GCS评分、咳嗽效力评级与颅脑疾病气管切开术后拔管成功的关系[J]. 临床误诊误治, 2023, 36(7): 97-100.
[6] 董旭, 冯涛, 刘庆, 等. 重症康复科颈脊髓损伤合并膈肌功能障碍患者并发肺部感染高危因素的回顾性研究[J]. 宁夏医学杂志, 2023, 45(6): 514-516. DOI:10.13621/j.1001-5949.2023.06.0514
[7] 高敏, 韩小彤, 张兴文, 等. 探讨中重型颅脑损伤机械通气患者拔管的预测因素[J]. 中国呼吸与危重监护杂志, 2023, 22(4): 274-280. DOI:10.7507/1671-6205.202209066
[8] 高胜浩, 李琳璨, 张晓菊, 等. 有创-无创机械通气降级治疗策略在气管切开呼吸机依赖患者中的应用效果研究[J]. 中国全科医学, 2021, 24(5): 571-576. DOI:10.12114/j.issn.1007-9572.2020.00.511
[9] 韩奇, 刘倩, 林明泉, 等. 气管切开患者拔管评估研究进展[J]. 吉林医药学院学报, 2024, 45(4): 291-295
[10] 胡银, 青晨, 袁梅, 等. 神经外科病人气管切开拔管影响因素及拔管指征的研究进展[J]. 护理研究, 2025, 39(3): 488-494. DOI:10.12102/j.issn.1009-6493.2025.03.022
[11] 李勍, 姜宏英, 周婷, 等. 气管切开术后拔管困难患者成功拔除气切套管的相关因素分析[J]. 中国康复医学杂志, 2023, 38(9): 1227-1232. DOI:10.3969/j.issn.1001-1242.2023.09.008
[12] 李秋怡. 气管切开患者拔管的临床预测模型构建与验证[D]. 昆明医科大学, 2023: 56
[13] 戚婷, 刘冬, 王崇. 气管切开神经重症患者早期成功拔管的相关因素分析[J]. 临床医学研究与实践, 2025, 10(1): 63-66
[14] 唐志明, 温红梅, 许自阳, 等. 喉镜吞咽功能评估指导气管切开合并吞咽障碍患者拔管的应用分析[J]. 中华物理医学与康复杂志, 2020, 42(10): 886-889. DOI:10.3760/cma.j.issn.0254-1424.2020.10.005
[15] 王华, 张丰珍, 龙婷, 等. 后颅窝肿瘤术后儿童气管切开原因及预后转归分析[J]. 山东大学耳鼻喉眼学报, 2025, 39(4): 168-173. DOI:10.6040/j.issn.1673-3770.0.2025.028
[16] 王佳, 丁磊, 陈佳俊. 危重症气管插管病人非计划性拔管风险预测模型的构建与检验[J]. 全科护理, 2025, 23(21): 4114-4118. DOI: 10.12104/j.issn.1674-4748.2025.21.024
[1] ZHAO Huiming, LIU Bin, CHEN Kun, LI Yafei, CHEN Zi. Influencing factors and clinical predictive value for disease severity in pediatric obstructive sleep apnea-hypopnea syndrome [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2026, 40(5): 57-64.
[2] CHEN Xi, YAO Yisong, FANG Yuhui, LI Dongxian, LI Yumei, SONG Xicheng. Machine learning models for predicting distant metastasis in patients with major salivary gland cancers based on SEER database [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2026, 40(4): 81-89.
[3] WANG Hua, ZHANG Fengzhen, LONG Ting, ZHAO Jing, LI Hongbin, WANG Shengcai, WANG Guixiang. Analysis of the reasons and prognostic outcomes for tracheostomy in pediatric patients following posterior fossa tumor resection [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2025, 39(4): 168-173.
[4] WANG Huanxia, WANG Shuya, WANG Ying, SUN Xuan, HUANG Jie, WANG Xingrong. Risk factors for epiretinal membrane formation following pars plana vitrectomy for rhegmatogenous retinal detachment [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2025, 39(4): 181-185.
[5] LYU Yong, FENG Yun. Prediction model of cardiovascular disease risk in people with dual sensory impairment: analysis based on CHARLS [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2025, 39(3): 122-128.
[6] SONG Panpan, ZHAO Yufeng, ZHANG Yaoyao, DING Detao, ZHANG Jiafu, ZHANG Hui, ZHANG Jin, WU Yungang. Two cases of odontogenic deep cervical multi-space and mediastinal abscess and literature review [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2024, 38(3): 93-96.
[7] ZHANG Jing, ZHU Guochen. Laryngeal abscess with destruction of thyroid cartilage caused by enterococcus faecalis:a case report and literature review [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2023, 37(5): 80-84.
[8] LI Lu, ZHAO Jie, ZHAO Bojun. Research progress on the pathogenesis and treatments of central serous chorioretinopathy [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2023, 37(3): 118-124.
[9] XIAO Fuliang, LIN Yun, PAN Xinliang. A clinical study on prophylactic central lymph node dissection in early cN0 papillary thyroid carcinoma [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2023, 37(1): 64-71.
[10] ZHANG Lijun, XU Ran, LUO Jifang, LIU Guoqi, HE Qian, LI Wei, JIANG Zhenhua. Factors affecting flap neurosis and other postoperative flap-related complications after free-flap reconstruction of head and neck tumors [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2022, 36(4): 86-90.
[11] LIU Shanshan, HAN Shujing, WANG Xiaoxu, LI Yanhong, NI Xin, ZHANG Jie. Hearing loss in children after bacterial meningitis: a systematic review and meta-analysis [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2022, 36(1): 48-54.
[12] To describe characteristics and risk factors associated with central serous chorioretinopathy(CSC)in a hospital-based outpatient sample population. MethodsIn this hospital-based cross-sectional study, CSC patients were recruited from the Beijing Friendship Hospital from 01/2019 to 12/2019. All participants underwent a standardized interview. Logistic regression models were used to assess the risk factors associated with CSC. ResultsA total of 23,878 outpatients were recorded during the period 01/2019-12/2019. Of these, 45 patients(0.19%)were diagnosed with CSC, divided in 37 male patients(82.22%)and 8 female patients(17.78%). The patients′ age ranged from 21 to 65(42.3±10.1)years. Three patients(6.67%)presented a bilateral involvement. Of all the patients, 39 were included in the present analysis. Control patients were matched for age and sex at a ratio of 1:1. The presence of CSC was associated with exposure to steroids(OR=5.04, 95% CI:1.11-22.89), sleep time(going to sleep after 12 pm)(OR=4.16, 95% CI:1.33-13.04)),and shift-work(OR=5.74, 95% CI:1.47-22.45).ConclusionsOur data showed that CSC prevalence in the analyzed outpatients was 0.19%. Exposure to steroids, sleep time, and shift-work were factors related with CSC in the observed population.. Prevalence and risk factors of central serous chorioretinopathy in a hospital-based population YANG Xiufen, YOU Ran, MA Xiumei, WANG Kang, WANG Yanling Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, ChinaAbstract:Objective〓 [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(4): 75-79.
[13] This study was conducted to explore the preoperative risk factors for postoperative adhesion in patients with chronic rhinosinusitis(CRS)undergoing functional endoscopic sinus surgery(FESS), and to construct a risk score model to evaluate their predictive effect. MethodsA retrospective study was conducted on 323 patients with CRS who underwent FESS at our hospital between January 2015 and June 2018. The risk factors for postoperative adhesion were screened using a multivariate logistic regression analysis. The risk score was assigned according to the odds ratio(OR)value, and a receiver operating characteristic(ROC)curve was drawn to evaluate the predictive effect. ResultsPostoperative adhesion occurred in 35 patients(10.8%). The logistic regression results showed that concha bullosa, primary FESS, operative experience less than 10 years, and a history of middle turbinate resection were independent risk factors for postoperative adhesion in FESS. The OR values were 1.12(95% CI: 1.06-1.18), 3.87(95% CI: 2.23-5.51), 3.19(95% CI: 2.07-4.31), and 2.24(95% CI:1.95-2.53), respectively. The risk score model assigned 1 point for vesicular middle turbinate, 4 points for first time FESS, 3 points for operative experience less than 10 years, and 2 points for middle turbinate resection. The ROC curve analysis showed that the area under the curve(AUC)was 0.784(95% CI: 0.672-0.896, P<0.05). When 4 points were selected as the cut-off point, the Jordan index was the largest, with a sensitivity of 75.1% and a specificity of 73.6%. ConclusionThe incidence of postoperative adhesion in 323 patients with CRS who underwent FESS was 10.8%. The risk score model has certain reference value for predicting high-risk postoperative adhesion.. Potential risk factors and evaluation of a predictive risk score model for postoperative adhesion in functional endoscopic sinus surgeryCHEN Dong1, YU Hong2, LI Yang1, HUANG Qiang1, FANG Min1 1. Department of Otolaryngology, Jiangyou Peoples Hospital, Jiangyou 621700, Sichuan, China; 2. Department of Pathology, Jiangyou Peoples Hospital, Jiangyou 621700, Sichuan, ChinaAbstract:Objective〓 [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(4): 87-91.
[14] CHEN Haibing, WEI Ya'nan, XU Xiaoquan, CHEN Xi. Prediction of cervical lymph node metastasis in papillary thyroid cancer based on XGBoost artificial intelligence and enhanced computed tomography [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(3): 40-45.
[15] HAO Wenpei, ZHAI Hualei, SUN Xiaotong, ZHANG Yani, ZHU Yanhui, KONG Qianqian, CHENG Jun, ZHANG Ting. Etiology of repeat keratoplasty and risk factors for failure of corneal grafts [J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2020, 34(3): 134-140.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Website Copyright: Editorial Office of Journal of Otolaryngology and Ophthalmology of Shandong University
Address: No.27 Shanda South Road, Jinan, Shandong, China. Post code: 250100 Tel: +86-0531-88366912 Email: ebhxb@sdu.edu.cn Supported by Beijing Magtech Co.Ltd