DOI 10.1186/s12871-024-02826-w
Radiological indicators and a novel combined predictive model for anticipating difficult laryngoscopy in cervical spondylosis patients: a prospective cohort study.
Аннотация
BACKGROUNDS: Anticipating difficult laryngoscopy is crucial for preoperative assessment, especially for patients with cervical spondylosis. Radiological assessment has become essential for improving airway management safety. This research introduces novel radiological indicators from lateral cervical X-ray in the extended head position proposed to enhance the accuracy of predicting difficult laryngoscopy.
METHODS
A prospective cohort study included 422 patients scheduled for elective cervical spine surgery. The Cormack-Lehane grades I and II were categorized as "easy laryngoscopy group", while grades III and IV were labeled "difficult laryngoscopy group". Demographic data, conventional bedside indicators including inter-incisor gap (IIG), neck circumference (NC), thyromental distance, the upper lip bite test (ULBT), and 4 radiological indicators including Mandibular Length, Laryngeal Height, the Larynx-Mandibular Angle Test (LMAT) and Larynx-Mandibular Height Test (LMHT) were analyzed comparatively. A binary logistic regression model was developed to identify independent predictive factors. The predictive value of the indicators was evaluated with the area under the curve (AUC).
RESULTS
A total of 402 patients were analyzed in the present study. A binary logistic regression model identified IIG, NC, ULBT, and LMAT as the independent indicators associated with difficult laryngoscopy. A novel combined predictive model equation was derived: Ɩ=-0.969 - 1.33×IIG + 0.408×ULBT + 0.201×NC - 0.042×LMAT. The AUC for this composite model was 0.776, exceeding the individual AUC of 0.677 for LMHT.
CONCLUSION
LMHT and the novel combined predictive model incorporating LMAT are potentially valuable predictors for difficult laryngoscopy in patients with cervical spondylosis.
TRIAL REGISTRATION: The study was registered at the Chinese Clinical Trial Registry (ChiCTR2200058361) on April 7, 2022.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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