Institute of Nursing Research, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Medicine, Wuhan University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Department of Cardiology, Wuhan Asia Heart Hospital affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Braz J Cardiovasc Surg. 2024 Sep 9;39(4):e20230424. doi: 10.21470/1678-9741-2023-0424.
The aim of this study was to identify perioperative risk factors of laryngeal symptoms and to develop an implementable risk prediction model for Chinese hospitalized patients undergoing coronary artery bypass grafting (CABG).
A total of 1476 Chinese CABG patients admitted to Wuhan Asian Heart Hospital from January 2020 to June 2022 were included and then divided into a modeling cohort and a verification cohort. Univariate analysis was used to identify laryngeal symptoms risk factors, and multivariate logistic regression was applied to construct a prediction model for laryngeal symptoms after CABG. Discrimination and calibration of this model were validated based on the area under the receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow (H-L) test, respectively.
The incidence of laryngeal symptoms in patients who underwent CABG was 6.48%. Four independent risk factors were included in the model, and the established aryngeal complications risk calculation formula was Logit (P) = -4.525 + 0.824 × female + 2.09 × body mass index < 18.5 Kg/m2 + 0.793 × transesophageal echocardiogram + 1.218 × intensive care unit intubation time. For laryngeal symptoms, the area under the ROC curve was 0.769 in the derivation cohort (95% confidence interval [CI]: 0.698-0.840) and 0.811 in the validation cohort (95% CI: 0.742-0.879). According to the H-L test, the P-values in the modeling group and the verification group were 0.659 and 0.838, respectively.
The prediction model developed in this study can be used to identify high-risk patients for laryngealsymptoms undergoing CABG, and help clinicians implement the follow-up treatment.
本研究旨在确定围手术期与喉症状相关的风险因素,并为中国行冠状动脉旁路移植术(CABG)的住院患者开发一个可实施的风险预测模型。
共纳入 2020 年 1 月至 2022 年 6 月期间武汉亚洲心脏病医院的 1476 例行 CABG 的中国患者,分为建模队列和验证队列。采用单因素分析识别与喉症状相关的风险因素,应用多因素 logistic 回归构建 CABG 术后喉症状预测模型。采用受试者工作特征(ROC)曲线下面积和 Hosmer-Lemeshow(H-L)检验分别验证模型的区分度和校准度。
CABG 患者喉症状发生率为 6.48%。模型纳入 4 个独立风险因素,建立的喉并发症风险计算公式为 Logit(P)=-4.525+0.824×女性+2.09×BMI<18.5kg/m2+0.793×经食管超声心动图+1.218×重症监护病房插管时间。在推导队列中,预测喉症状的 ROC 曲线下面积为 0.769(95%置信区间[CI]:0.698-0.840),在验证队列中为 0.811(95% CI:0.742-0.879)。根据 H-L 检验,建模组和验证组的 P 值分别为 0.659 和 0.838。
本研究建立的预测模型可用于识别行 CABG 的喉症状高危患者,帮助临床医生实施随访治疗。