Evidence map›Paper›PMID 41669481›Full record

ArticleQuantitative imaging in medicine and surgery2026

Association between upper airway computed tomography measurement parameters and mask ventilation in patients undergoing oral and maxillofacial surgery.

Maosheng Yu, Jiayi Wang, Ren Zhou, Jia Yan, Hong Jiang

Abstract read
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Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Maosheng Yu *Department of Anesthesiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.ORCID https://orcid.org/0009-0003-8328-8512
Jiayi Wang *Department of Anesthesiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
Ren ZhouDepartment of Anesthesiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
Jia YanDepartment of Anesthesiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
Hong JiangDepartment of Anesthesiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Difficult mask ventilation (DMV) poses significant perioperative challenges, particularly in oral and maxillofacial surgery. Maxillofacial computed tomography (CT) imaging may offer improved airway assessment. This study aimed to identify those preoperative midsagittal CT parameters associated with DMV in this high-risk patient population. Methods: A retrospective cohort study was conducted that analyzed patients undergoing oral and maxillofacial surgery, with 21 anatomical parameters being measured on preoperative midsagittal CT scans. Multivariable logistic regression, adjusted for demographic characteristics, medical history, and traditional airway assessment parameters, was used to identify independent predictors of DMV. Subgroup analyses were performed for significant parameters. Results: Among 449 participants included in the study, the incidence of DMV was 17.3%. Three CT parameters independently predicted DMV: anteroposterior diameter of the neck (dAP) [odds ratio (OR): 1.08; 95% confidence interval (CI): 1.03-1.13; P=0.003), uvula length (LU) (OR: 1.10; 95% CI: 1.03-1.18; P=0.008), and distance between the posterior nasal spine and the nasopharynx (Snp_Nph) (OR 0.92; 95% CI: 0.85-0.99; P=0.027). LU showed a stronger association with DMV in snoring patients (P for interaction=0.039) and Mallampati class I-II cases (P for interaction =0.038), while Snp_Nph showed a stronger association with DMV in patients with a body mass index (BMI) >24 kg/m Conclusions: Neck morphology and uvular characteristics significantly influence DMV risk. Preoperative CT measurement of dAP, LU, and Snp_Nph may enhance DMV prediction, improving airway management in oral and maxillofacial surgery.

Indexed as

airway computed tomography (airway CT)difficult airwaydifficult mask ventilation (DMV)Oral and maxillofacial surgery

Identifiers

PMID41669481
PMCPMC12883588

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