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已发表论文
基于炎症标志物构建预测颌面颈部间隙感染气道管理风险评分模型
Authors Wang X, Shi H, Qian W, Zhou Q, Wang B, Zhang W, Li H, Zheng L
Received 15 June 2025
Accepted for publication 29 October 2025
Published 4 November 2025 Volume 2025:18 Pages 15379—15392
DOI https://doi.org/10.2147/JIR.S547214
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Tara Strutt
Xijun Wang,1– 5,* Huan Shi,1– 5,* Wentao Qian,1– 5 Qin Zhou,1– 5 Baoli Wang,1– 5 Wenhao Zhang,1– 5 Hui Li,1– 5 Lingyan Zheng1– 5
1Department of Oral Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, People’s Republic of China; 2College of Stomatology, Shanghai Jiao Tong University, Shanghai, People’s Republic of China; 3National Center for Stomatology, Shanghai, People’s Republic of China; 4National Clinical Research Center for Oral Diseases, Shanghai, People’s Republic of China; 5Shanghai Key Laboratory of Stomatology, Shanghai, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Lingyan Zheng, Department of Oral Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 ZhiZaoJu Road, Shanghai, 200011, People’s Republic of China, Email zhenglingyan73@163.com Hui Li, Department of Oral Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 ZhiZaoJu Road, Shanghai, 200011, People’s Republic of China, Email lihui9x@163.com
Purpose: Patients with oral and maxillofacial space infections (OMSI) often experience rapidly progressing disease that can result in acute hypoxia, leading to severe complications such as cerebral hypoxia and cardiac arrest. Effective airway management (intubation or tracheotomy) is crucial in these cases. However, no validated tools currently exist to predict which patients require airway intervention. This study aimed to develop and validate a risk scoring system to predict the need for airway management in patients with OMSI.
Patients and Methods: We conducted a retrospective study of OMSI patients treated between January 2020 and December 2022 and divided them into training and validation cohorts. A risk prediction model was developed using LASSO and logistic regression analyses in the training cohort, and its discrimination and calibration were verified in the validation cohort.
Results: A total of 215 patients (150 for training and 65 for validation) were analyzed. Six independent predictors were identified: dyspnea (OR 3.95, 95% CI 1.38– 11.35, p = 0.011), BMI (OR 1.14, 95% CI 1.04– 1.25, p = 0.006), body temperature (OR 2.92, 95% CI 1.34– 6.37, p = 0.007), sIL-2R level (OR 1.01, 95% CI 1.01– 1.01, p = 0.007), CRP level (OR 1.01, 95% CI 1.01– 1.01, p = 0.047), and retropharyngeal space involvement (OR 15.71, 95% CI 3.36– 73.40, p < 0.001). Internal validation revealed good discrimination (AUC 0.91) and calibration (HL test, p = 0.061), with similar performance in the validation cohort (AUC 0.86; HL test, p = 0.133). Decision curve analysis demonstrated clinical utility in both cohorts.
Conclusion: The proposed risk scoring system reliably predicts the need for airway management in OMSI patients, which enables clinicians to identify high-risk patients early and implement preventive strategies to improve outcomes.
Keywords: oral and maxillofacial space infections, risk scoring system, predictive modeling, clinical decision-making
1Department of Oral Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, People’s Republic of China; 2College of Stomatology, Shanghai Jiao Tong University, Shanghai, People’s Republic of China; 3National Center for Stomatology, Shanghai, People’s Republic of China; 4National Clinical Research Center for Oral Diseases, Shanghai, People’s Republic of China; 5Shanghai Key Laboratory of Stomatology, Shanghai, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Lingyan Zheng, Department of Oral Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 ZhiZaoJu Road, Shanghai, 200011, People’s Republic of China, Email zhenglingyan73@163.com Hui Li, Department of Oral Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 ZhiZaoJu Road, Shanghai, 200011, People’s Republic of China, Email lihui9x@163.com
Purpose: Patients with oral and maxillofacial space infections (OMSI) often experience rapidly progressing disease that can result in acute hypoxia, leading to severe complications such as cerebral hypoxia and cardiac arrest. Effective airway management (intubation or tracheotomy) is crucial in these cases. However, no validated tools currently exist to predict which patients require airway intervention. This study aimed to develop and validate a risk scoring system to predict the need for airway management in patients with OMSI.
Patients and Methods: We conducted a retrospective study of OMSI patients treated between January 2020 and December 2022 and divided them into training and validation cohorts. A risk prediction model was developed using LASSO and logistic regression analyses in the training cohort, and its discrimination and calibration were verified in the validation cohort.
Results: A total of 215 patients (150 for training and 65 for validation) were analyzed. Six independent predictors were identified: dyspnea (OR 3.95, 95% CI 1.38– 11.35, p = 0.011), BMI (OR 1.14, 95% CI 1.04– 1.25, p = 0.006), body temperature (OR 2.92, 95% CI 1.34– 6.37, p = 0.007), sIL-2R level (OR 1.01, 95% CI 1.01– 1.01, p = 0.007), CRP level (OR 1.01, 95% CI 1.01– 1.01, p = 0.047), and retropharyngeal space involvement (OR 15.71, 95% CI 3.36– 73.40, p < 0.001). Internal validation revealed good discrimination (AUC 0.91) and calibration (HL test, p = 0.061), with similar performance in the validation cohort (AUC 0.86; HL test, p = 0.133). Decision curve analysis demonstrated clinical utility in both cohorts.
Conclusion: The proposed risk scoring system reliably predicts the need for airway management in OMSI patients, which enables clinicians to identify high-risk patients early and implement preventive strategies to improve outcomes.
Keywords: oral and maxillofacial space infections, risk scoring system, predictive modeling, clinical decision-making