Table_4_Development and validation of a regression model with nomogram for difficult video laryngoscopy in Chinese population: a prospective, single-center, and nested case-control study.DOCX

BackgroundAirway management failure is associated with increased perioperative morbidity and mortality. Airway-related complications can be significantly reduced if difficult laryngoscopy is predicted with high accuracy. Currently, there are no large-sample studies on difficult airway assessments in Chinese populations. An airway assessment model based on the Chinese population is urgently needed to guide airway rescue strategy.
MethodsThis prospective nested case–control study took place in a tertiary hospital in Shanghai, China. Information on 10,549 patients was collected, and 8,375 patients were enrolled, including 7,676 patients who underwent successful laryngoscopy and 699 patients who underwent difficult laryngoscopy. The baseline characteristics, medical history, and bedside examinations were included as predictor variables. Laryngoscopy was defined as ‘successful laryngoscopy’ based on a Cormack–Lehane Grades of 1–2 and as ‘difficult laryngoscopy’ based on a Cormack–Lehane Grades of 3–4. A model was developed by incorporating risk factors and was presented in the form of a nomogram by univariate logistic regression, least absolute shrinkage and selection operator, and stepwise logistic regression. The main outcome measures were area under the curve (AUC), sensitivity, and specificity of the predictive model.
ResultThe AUC value of the prediction model was 0.807 (95% confidence interval [CI]: 0.787–0.828), with a sensitivity of 0.730 (95% CI, 0.690–0.769) and a specificity of 0.730 (95% CI, 0.718–0.742) in the training set. The AUC value of the prediction model was 0.829 (95% CI, 0.800–0.857), with a sensitivity of 0.784 (95% CI, 0.73–0.838) and a specificity of 0.722 (95% CI, 0.704–0.740) in the validation set.
ConclusionOur model had accurate predictive performance, good clinical utility, and good robustness for difficult laryngoscopy in the Chinese population.

【背景】气道管理失败与围手术期并发症发生率及死亡率升高密切相关。若能高精度预测困难喉镜检查，可显著降低气道相关并发症的发生风险。目前国内尚无针对中国人群困难气道评估的大样本研究，亟需构建基于中国人群的气道评估模型以指导气道抢救策略的制定。
【方法】本研究为一项在中国上海某三级甲等医院开展的前瞻性巢式病例对照研究。共收集10549例患者的相关资料，最终纳入8375例患者，其中喉镜检查成功7676例，困难喉镜检查699例。研究将基线特征、病史及床边查体结果作为预测变量。以Cormack-Lehane分级（Cormack–Lehane Grades）1~2级定义为“喉镜检查成功”，3~4级定义为“困难喉镜检查”。本研究通过单因素logistic回归、最小绝对收缩和选择算子（Least Absolute Shrinkage and Selection Operator，LASSO）回归及逐步logistic回归筛选危险因素，构建预测模型并以列线图形式呈现。主要结局指标为预测模型的受试者工作特征曲线下面积（AUC）、灵敏度及特异度。
【结果】在训练集中，本预测模型的AUC值为0.807（95%置信区间[CI]：0.787~0.828），灵敏度为0.730（95%CI：0.690~0.769），特异度为0.730（95%CI：0.718~0.742）。在验证集中，该预测模型的AUC值为0.829（95%CI：0.800~0.857），灵敏度为0.784（95%CI：0.73~0.838），特异度为0.722（95%CI：0.704~0.740）。
【结论】本研究所构建的模型针对中国人群的困难喉镜检查具有良好的预测效能、临床实用性及稳健性。