A Nomogram for Predicting the Need of Postoperative Tracheostomy in Patients With Aneurysmal Subarachnoid Hemorrhage

Frontiers in Neurology

卷:12

Deng-Liang Wang¹  Yue Chen¹  Wen-Hua Fang¹  Xiao-Yong Chen¹  Jin-Yuan Chen²  Chen-Yu Ding³  De-Zhi Kang⁴  Ni Lin⁵ 

[1] Department of Neurosurgery, Neurosurgical Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China;

[2] Department of Ophthalmology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China;

[3] Fujian Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China;

[4] Key Laboratory of Fujian Higher Education Institutions, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China;

[5] The School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China;

关键词: nomogram;    predict;    tracheostomy;    aneurysmal subarachnoid hemorrhage;    need;   

DOI  :  10.3389/fneur.2021.711468

来源: DOAJ

【 摘 要 】

Objective: Early identification for the need of tracheostomy (TT) in aneurysmal subarachnoid hemorrhage (aSAH) patients remains one of the main challenges in clinical practice. Our study aimed to establish and validate a nomogram model for predicting postoperative TT in aSAH patients.Methods: Patients with aSAH receiving active treatment (interventional embolization or clipping) in our institution between June 2012 and December 2018 were retrospectively included. The effects of patients' baseline information, aneurysm features, and surgical factors on the occurrence of postoperative TT were investigated for establishing a nomogram in the training cohort with 393 patients. External validation for the nomogram was performed in the validation cohort with 242 patients.Results: After multivariate analysis, higher age, high neutrophil-to-lymphocyte ratio (NLR), high World Federation of Neurological Surgeons Scale (WFNS), and high Barrow Neurological Institute (BNI) grade were left in the final logistic regression model. The predictive power of the model was excellent in both training cohort and validation cohort [area under the curve (AUC): 0.924, 95% confidence interval [CI]: 0.893–0.948; AUC: 0.881, 95% CI: 0.833–0.919]. A nomogram consisting of these factors had a C-index of 0.924 (95% CI: 0.869–0.979) in the training cohort and was validated in the validation cohort (C-index: 0.881, 95% CI: 0.812–0.950). The calibration curves suggested good match between prediction and observation in both training and validation cohorts.Conclusion: Our study established and validated a nomogram model for predicting postoperative TT in aSAH patients.

【 授权许可】

Unknown