JCNRJournal of Clinical and Nursing Research2208-36852208-3693Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jcnr.v10i5.14531ArticleA Scoping Review of Risk Prediction Models for Oral Mucosal Pressure Injury in ICU Patients with Oral Tracheal Intubationhttps://artdesignp.com/journal/JCNR/10/5/10.26689/jcnr.v10i5.14531ShenXuan,YuanYingzi,GuanQianqian,ZhangYing20261052026-05-31Objective: To conduct a comprehensive review of risk prediction models for oral mucosal pressure injury in ICU patients with oral tracheal intubation, aiming to provide a reference for the development and clinical application selection of risk prediction models in the future. Methods: Using the scope review methodology framework, this study searched PubMed, Web of Science, Embase, Cochrane Library, China Biomedical Literature Database, CNKI and Wanfang from database construction until December 31. Two researchers independently screened and extracted data for aggregated analysis. Results: Seven studies were finally included. The subjects were mainly ICU patients with oral tracheal intubation. Logistic regression model was used as the model construction method, and nomogram was used as the model presentation. The three most frequently occurring predictors were tracheal intubation indwelling time, APACHEⅡ score, and dental pad usage. Conclusion: The included models had good overall predictive power. However, to establish models with a low risk of bias, good predictive performance, and strong operability, a high overall risk of bias needed to be addressed to provide some guidance for clinical practice.

Feng Y, Shi D, Huang J, 2012, Research Progress on Different Fixation Methods in Transoral Tracheal Intubation. China Practical Nursing Journal, 28(z2): 143.

Amrani G, Gefen A, 2020, Which Endotracheal Tube Location Minimises the Device-Related Pressure Ulcer Risk: The Centre or a Corner of the Mouth? International Wound Journal, 17(2): 268–276.

Kim S, Nah H, Kim J, et al., 2021, Relationships Between Oral-Mucosal Pressure Ulcers, Mechanical Conditions, and Individual Susceptibility in Intubated Patients Under Intensive Care: A PCR-Based Observational Study. Biological Research for Nursing, 23(4): 557–567.

Choi B, Kim M, Kim S, 2020, Risk Prediction Models for the Development of Oral-Mucosal Pressure Injuries in Intubated Patients in Intensive Care Units: A Prospective Observational Study. J Tissue Viability, 29(4): 252–257.

Wang B, Jiang X, Shi G, et al., 2024, Analysis of Characteristics and Influencing Factors of Oral Mucosal Pressure Injury in Elderly ICU Patients with Tracheal Intubation. Chinese Journal of Geriatric Stomatology, 22(04): 200–204 + 229.

Coyer F, Stotts N, Blackman V, 2014, A Prospective Window into Medical Device-Related Pressure Ulcers in Intensive Care. International Wound Journal, 11(6): 656–664.

Barakat-Johnson M, Barnett C, Wand T, et al., 2017, Medical Device-Related Pressure Injuries: An Exploratory Descriptive Study in an Acute Tertiary Hospital in Australia. J Tissue Viability, 26(4): 246–253.

Nan R, Pei J, Zhang Y, et al., 2020, Research Progress on Nursing Care for Mucosal Pressure Injuries. Journal of PLA Nursing, 37(12): 62–64.

Gu T, Huang G, Zhang P, et al., 2024, Construction and Validation of a Risk Prediction Model for Oral Mucosal Pressure Injury in Patients with Orotracheal Intubation. Journal of Nursing, 39(20): 64–68.

Moons K, de Groot J, Bouwmeester W, et al., 2014, Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies: The CHARMS Checklist. PLoS Medicine, 11(10): e1001744.

Chen X, Zhang Y, Zhuang Y, et al., 2020, PROBAST: Assessment of Bias Risk in Diagnostic or Prognostic Multivariate Predictive Model Studies. China Journal of Evidence-Based Medicine, 20(06): 737–744.

Jia L, Deng Y, Xu Y, et al., 2024, Development and Validation of a Nomogram for Oral Mucosal Membrane Pressure Injuries in ICU Patients: A Prospective Cohort Study. Journal of Clinical Nursing, 33(10): 4112–4123.

Zhang S, Jiang H, Hou J, et al., 2024, Construction of a Risk Prediction Model for Oral Mucosal Pressure Injury in Elderly Patients Undergoing Endotracheal Intubation via the Mouth in the ICU. Nursing Research, 38(20): 3592–3597.

Li M, Tang L, Yao Q, et al., 2024, Construction and Validation of a Predictive Model for Oral Mucosal Pressure Injury Risk in Patients Undergoing Endotracheal Intubation via the Mouth. Nursing and Rehabilitation, 23(06): 1–8.

Zhang Y, Pan Y, Huang Y, et al., 2025, Risk Factor Analysis and Risk Prediction Model Construction for Oral Mucosal Pressure Injury in Patients Undergoing Endotracheal Intubation via the Mouth in the Emergency Intensive Care Unit. Journal of Practical Clinical Medicine, 29(3): 75–79 + 83.

Wang Z, He X, Tao Z, et al., 2024, Construction of a Line Graph Model for the Risk of Oral Mucosal Pressure Injury in ICU Patients with Tracheal Intubation. Chinese Journal of Modern Nursing, 30(13): 1764–1770.

Kim C, Kim M, Kang M, et al., 2019, Oral Mucosa Pressure Ulcers in Intensive Care Unit Patients: A Preliminary Observational Study of Incidence and Risk Factors. J Tissue Viability, 28(1): 27–34.

Hampson J, Green C, Stewart J, et al., 2018, Impact of the Introduction of an Endotracheal Tube Attachment Device on the Incidence and Severity of Oral Pressure Injuries in the Intensive Care Unit: A Retrospective Observational Study. BMC Nursing, 17: 4.

Zhang Q, Song C, Zou Q, et al., 2020, Observation on the Efficacy of Modified Transoral Tracheal Intubation Fixation Method for Instrument-Induced Pressure Injuries of the Oral and Facial Neck in ICU Patients. Chinese General Practice, 18(08): 1421–1424.

Ren X, Chen J, 2019, Prevention and Nursing Care of Tongue Pressure Ulcers in Patients Undergoing Transoral Endotracheal Intubation. General Nursing, 17(15): 1841–1843.

Serra R, Caroleo S, Buffone G, et al., 2014, Low Serum Albumin Level as an Independent Risk Factor for the Onset of Pressure Ulcers in Intensive Care Unit Patients. International Wound Journal, 11(5): 550–553.

Liu Y, Yang X, Li L, 2021, Advances in the Application of Machine Learning for Disease Prediction. Journal of Nursing Science, 28(07): 30–34.