Evidence map›Paper›PMID 32943014›Full record

ArticleBMC anesthesiology2020

Radiological indicators to predict the application of assistant intubation techniques for patients undergoing cervical surgery.

Bingchuan Liu, Yanan Song, Kaixi Liu, Fang Zhou, Hongquan Ji, Yun Tian, Yong Zheng Han

Abstract read
In one paragraph

Article in BMC anesthesiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Trends in Preoperative Airway Assessment.Diagnostics (Basel, Switzerland) · 2024
    Review
  2. Article
  3. Article
  4. Article
  5. Risk factors affecting the difficulty of fiberoptic nasotracheal intubation.Journal of dental anesthesia and pain medicine · 2020
    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

7 authors.

Bingchuan LiuDepartment of Orthopaedics, Peking University Third Hospital, Beijing, China.
Yanan SongDepartment of Anesthesiology, Peking University Third Hospital, 49 North Garden Rd, Haidian District, Beijing, 100191, China.
Kaixi LiuDepartment of Anesthesiology, Peking University Third Hospital, 49 North Garden Rd, Haidian District, Beijing, 100191, China.
Fang ZhouDepartment of Orthopaedics, Peking University Third Hospital, Beijing, China.
Hongquan JiDepartment of Orthopaedics, Peking University Third Hospital, Beijing, China.
Yun TianDepartment of Orthopaedics, Peking University Third Hospital, Beijing, China. tiany@bjmu.edu.cn.
Yong Zheng HanDepartment of Anesthesiology, Peking University Third Hospital, 49 North Garden Rd, Haidian District, Beijing, 100191, China. hanyongzheng@163.com.

Funding

Hospital Medical Research Foundation of Peking University Third Hospital Y86471-01Key Clinical Projects of Peking University Third Hospital BYSY2017014Young Scholar Research Grant of Chinese Anesthesiologist Association 21900007
6 · The paper itself

Abstract

backgroundWe aimed to distinguish the preoperative radiological indicators to predict the application of assistant techniques during intubation for patients undergoing selective cervical surgery.

methodsA total of 104 patients were enrolled in this study. According to whether intubation was successfully accomplished by simple Macintosh laryngoscopy, patients were divided into Macintosh laryngoscopy group (n = 78) and Assistant technique group (n = 26). We measured patients' radiographical data via their preoperative X-ray and MRI images, and compared the differences between two groups. Binary logistic regression model was applied to distinguish the meaningful predictors. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to describe the discrimination ability of indicators. The highest Youden's index corresponded to an optimal cut-off value.

resultsTen variables exhibited significant statistical differences between two groups (P <  0.05). Based on logistic regression model, four further showed correlation with the application of assistant techniques, namely, perpendicular distance from hard palate to tip of upper incisor (X2), atlanto-occipital gap (X9), angle between a line passing through posterior-superior point of hard palate and the lowest point of the occipital bone and a line passing through the anterior-inferior point and the posterior-inferior point of the second cervical vertebral body (Angle E), and distance from skin to hyoid bone (MRI 7). Angle E owned the largest AUC (0.929), and its optimal cut-off value was 19.9° (sensitivity = 88.5%, specificity = 91.0%). the optimal cut-off value, sensitivity and specificity of other three variables were X2 (30.1 mm, 76.9, 76.9%), MRI7 (16.3 mm, 69.2, 87.2%), and X9 (7.3 mm, 73.1, 56.4%).

conclusionsFour radiological variables possessed potential ability to predict the application of assistant intubation techniques. Anaesthesiologists are recommended to apply assistant techniques more positively once encountering the mentioned cut-off values.

Indexed as

Cervical VertebraeFemaleHumansIntubation, IntratrachealMagnetic Resonance ImagingMaleMiddle AgedPreoperative CareRadiographyRespiratory SystemSensitivity and SpecificityAssistant intubation techniqueClinical studyDifficult laryngoscopeRadiological indicator

Identifiers

PMID32943014
PMCPMC7499909

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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.