Evidence map›Paper›PMID 38177983›Full record

ArticleBMC medical research methodology2024

Identification of difficult laryngoscopy using an optimized hybrid architecture.

XiaoXiao Liu, Colin Flanagan, Gang Li, Yiming Lei, Liaoyuan Zeng, Jingchao Fang, Xiangyang Guo, Sean McGrath, Yongzheng Han

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical research methodology, 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
0.6field-weighted citation impact, top 37% of its field
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 citations in OpenAlex.

  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

9 authors at 3 institutions in 3 countries.

XiaoXiao Liu *College of Mathematics and Information Science, Hebei University, Baoding, China.ORCID 0000-0003-2244-3550
Colin Flanagan *Electronic and Computer Engineering, University of Limerick, Limerick, Ireland.
Gang Li *Department of General Surgery (GL), Peking University Third Hospital, Beijing, China.
Yiming LeiMinistry of Education Engineering Research Centre on Mobile Digital Hospital Systems, School of Electronics, Peking University, Beijing, China. leiym@pku.edu.cn.
Liaoyuan ZengSchool of Communications, University of Electronic Science and Technology of China, Chengdu, China.
Jingchao FangDepartment of Radiology (JCF), Peking University Third Hospital, Beijing, China.
Xiangyang GuoDepartment of Anaesthesiology, Peking University Third Hospital, Beijing, China.
Sean McGrathElectronic and Computer Engineering, University of Limerick, Limerick, Ireland. sean.mcgrath@ul.ie.
Yongzheng HanDepartment of Anaesthesiology, Peking University Third Hospital, Beijing, China. hanyongzheng@bjmu.edu.cn.
Peking University · CNUniversity of Limerick · IEUniversity of Electronic Science and Technology of China · CN

Funding

Peking University PKU2022LCXQ031Peking University Third Hospital BYSYZHKC2022103
6 · The paper itself

Abstract

backgroundIdentification of difficult laryngoscopy is a frequent demand in cervical spondylosis clinical surgery. This work aims to develop a hybrid architecture for identifying difficult laryngoscopy based on new indexes.

methodsInitially, two new indexes for identifying difficult laryngoscopy are proposed, and their efficacy for predicting difficult laryngoscopy is compared to that of two conventional indexes. Second, a hybrid adaptive architecture with convolutional layers, spatial extraction, and a vision transformer is proposed for predicting difficult laryngoscopy. The proposed adaptive hybrid architecture is then optimized by determining the optimal location for extracting spatial information.

resultsThe test accuracy of four indexes using simple model is 0.8320. The test accuracy of optimized hybrid architecture using four indexes is 0.8482.

conclusionThe newly proposed two indexes, the angle between the lower margins of the second and sixth cervical spines and the vertical direction, are validated to be effective for recognizing difficult laryngoscopy. In addition, the optimized hybrid architecture employing four indexes demonstrates improved efficacy in detecting difficult laryngoscopy.

trial registrationEthics permission for this research was obtained from the Medical Scientific Research Ethics Committee of Peking University Third Hospital (IRB00006761-2015021) on 30 March 2015. A well-informed agreement has been received from all participants. Patients were enrolled in this research at the Chinese Clinical Trial Registry ( http://www.chictr.org.cn , identifier: ChiCTR-ROC-16008598) on 6 June 2016.

Indexed as

LaryngoscopySpondylosisCervical VertebraeHospitals, UniversityHumansAtlantooccipital gapCervical spondylosisDifficult laryngoscopyHybrid architectureRadiological variables

Identifiers

PMID38177983
PMCPMC10765670
OpenAlexW4390587316

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.