Evidence map›Paper›PMID 41332408›Full record

ArticleHua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology2025

[Early warning model of postoperative infection of internal fixation device in maxillofacial fracture based on the synthetic minority over-sampling technique algorithm].

Jinfeng Jiang, Haiyan Wang, Yanfeng Shi, Ke Xu

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Article in Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology, 2025. 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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4 authors.

Jinfeng JiangDept. of Oral and Maxillofacial Surgery, Affiliated Hospital of Nantong University, Nantong 226000, China.
Haiyan WangDept. of Oral and Maxillofacial Surgery, Affiliated Hospital of Nantong University, Nantong 226000, China.
Yanfeng ShiDept. of Oral and Maxillofacial Surgery, Affiliated Hospital of Nantong University, Nantong 226000, China.
Ke XuDept. of Oral and Maxillofacial Surgery, Affiliated Hospital of Nantong University, Nantong 226000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study investigates independent risk factors for postoperative internal fixation device infection in patients with maxillofacial fractures and proposes an early warning model based on the synthetic minority over-sampling technique (SMOTE) algorithm.

methodsA total of 1 104 patients who underwent surgical treatment for maxillofacial fractures at Oral and Maxillofacial Surgery Department, Affiliated Hospital of Nantong University from January 2021 to December 2024 were retrospectively analyzed. The patients were divided into two groups based on the presence of postoperative internal fixation device infection: the infection group (27 cases) and non-infection group (1 077 cases). Clinical data from both groups were collected and subjected to statistical analysis. Univariate and binary Logistic regression analysis were used to identify risk factors for postoperative internal fixation device infection in maxillofacial fractures. Subsequently, a Logistic regression model was established, and the dataset was improved based on the SMOTE algorithm to construct an early warning model with the improved dataset. The prediction performance of the models was compared and validated.

resultsAmong the 1 104 patients who underwent surgical treatment for maxillofacial fractures, 27 cases of postoperative internal fixation device infections were identified, corresponding to an infection rate of 2.45% (27/1 104). Age, diabetes history, fracture severity, and oral hygiene status were all identified as risk factors for postoperative internal fixation device infections in maxillofacial fractures (all

conclusionsAge, diabetes history, postoperative fracture severity, and oral hygiene status are all risk factors for infections associated with internal fixation devices after maxillofacial fracture surgery. The proposed early warning model demonstrated good predictive performance. Medical professionals can utilize this model to effectively intervene and anticipate infections related to internal fixation devices after maxillofacial fracture surgery.

Indexed as

AlgorithmsFracture Fixation, InternalInternal FixatorsMaxillofacial InjuriesSurgical Wound InfectionAdolescentAdultAgedFemaleHumansLogistic ModelsMaleMiddle AgedRetrospective StudiesRisk Factorsearly warning modelinternal fixation device infectionmaxillofacial fracturepostoperativesynthetic minority over-sampling technique

Identifiers

PMID41332408
PMCPMC12680117

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