Risk Model for Laryngeal Complications Prediction in Chinese PatientGBVs After Coronary Artery Bypass Grafting.

Braz J Cardiovasc Surg

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.

Published: September 2024


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Article Abstract

Introduction: 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).

Methods: 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.

Results: 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.

Conclusion: 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.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11379146PMC
http://dx.doi.org/10.21470/1678-9741-2023-0424DOI Listing

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