Evidence map›Paper›PMID 39623345›Full record

ArticleBMC anesthesiology2024

Radiological indicators and a novel combined predictive model for anticipating difficult laryngoscopy in cervical spondylosis patients: a prospective cohort study.

Jiao Li, Yang Tian, Mingya Wang, Jingchao Fang, Hua Zhang, Feng Yue, Mao Xu, Jun Wang, Min Li, Xiangyang Guo and 1 more

Abstract read
In one paragraph

Article in BMC anesthesiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Jiao Li *Department of Anesthesiology, Peking University Third Hospital, No. 49, North Garden Street, Haidian District, Beijing, 100191, China.
Yang Tian *Department of Anesthesiology, Peking University Third Hospital, No. 49, North Garden Street, Haidian District, Beijing, 100191, China.
Mingya Wang *Department of Anesthesiology, Peking University Third Hospital, No. 49, North Garden Street, Haidian District, Beijing, 100191, China.
Jingchao FangDepartment of Radiology, Peking University Third Hospital, Beijing, 100191, China.
Hua ZhangResearch Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, 100191, China.
Feng YueDepartment of Anesthesiology, Peking University Third Hospital, No. 49, North Garden Street, Haidian District, Beijing, 100191, China.
Mao XuDepartment of Anesthesiology, Peking University Third Hospital, No. 49, North Garden Street, Haidian District, Beijing, 100191, China.
Jun WangDepartment of Anesthesiology, Peking University Third Hospital, No. 49, North Garden Street, Haidian District, Beijing, 100191, China.
Min LiDepartment of Anesthesiology, Peking University Third Hospital, No. 49, North Garden Street, Haidian District, Beijing, 100191, China.
Xiangyang GuoDepartment of Anesthesiology, Peking University Third Hospital, No. 49, North Garden Street, Haidian District, Beijing, 100191, China.
Yongzheng HanDepartment of Anesthesiology, Peking University Third Hospital, No. 49, North Garden Street, Haidian District, Beijing, 100191, China. hanyongzheng@bjmu.edu.cn.

Funding

Capital's Funds for Health Improvement and Research Capital's Funds for Health Improvement and ResearchInnovation and Transformation Project, Peking University Third Hospital Innovation and Transformation Project, Peking University Third HospitalWu Jieping Medical Foundation 320.6750.2023-08-5
6 · The paper itself

Abstract

backgroundsAnticipating 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.

methodsA 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).

resultsA 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.

conclusionLMHT and the novel combined predictive model incorporating LMAT are potentially valuable predictors for difficult laryngoscopy in patients with cervical spondylosis.

trial registrationThe study was registered at the Chinese Clinical Trial Registry (ChiCTR2200058361) on April 7, 2022.

Indexed as

LaryngoscopySpondylosisAdultAgedCervical VertebraeCohort StudiesFemaleHumansMaleMiddle AgedPredictive Value of TestsProspective StudiesAirway assessmentCervical spondylosisDiagnostic imagingDifficult laryngoscopyPredictive modelPredictive testsRadiological indicatorX-ray

Identifiers

PMID39623345
PMCPMC11610216

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.