Risk Factor Analysis and Risk Model Construction of Postoperative Infection in Patients with Maxillofacial Fractures

doi:10.13701/j.cnki.kqyxyj.2024.10.008

Abstract

Abstract: Objective: To analyze the risk factors for postoperative infection in patients with maxillofacial fractures and construct a risk prediction model. Methods: From January 2022 to January 2024, 81 patients with oral and maxillofacial fractures who developed infection after surgical treatment at Xuzhou Medical University Affiliated Hospital were selected as the research subjects. Meanwhile, 70 patients with oral and maxillofacial fractures who did not develop infection after surgery at the same hospital during the same period were selected as the control group. Clinical data of patients were retrospectively collected and multiple logistic regression analysis was performed to screen for independent risk factors. A risk prediction model was constructed and its predictive value was evaluated. Results: The study found that operation duration ≥3 h, diabetes, and the number of titanium nails ≥20 were independent risk factors for postoperative infection of maxillofacial fractures (P<0.05). According to the selected independent risk factors, a prediction model for postoperative infection risk of patients with maxillofacial fractures was constructed: Logit (P) =-0.747+operation duration×1.730+diabetes×1.789+number of titanium nails×1.078. Hosmer-Lemeshow good of fit test showed that the fitting accuracy of the model was good (χ²=2.015, P=0.365). The calibration curve showed that the prediction probability was close to the actual probability, indicating that the model had a good calibration degree. The receiver operating characteristic (ROC) curve indicated that the area under the curve (AUC) of the predictive model was 0.728, suggesting that the model possessed moderate discriminative capacity. Decision curve analysis (DCA) revealed that within the horizontal axis range of 0.3-0.8 the predictive model's curve lay above the two extreme curves, suggesting that the model's clinical utility was acceptable. Conclusion: Postoperative infection in patients with maxillofacial fractures is related to the operation duration, diabetes, and the number of titanium nails. The risk prediction model based on it has certain diagnostic value.

Key words: maxillofacial fractures, postoperative infection, risk factors, prediction model, diagnostic value

LU Xinyue, PAN Yuetong, SUN Xinyi, LV Zhongjin. Risk Factor Analysis and Risk Model Construction of Postoperative Infection in Patients with Maxillofacial Fractures[J]. Journal of Oral Science Research, 2024, 40(10): 890-894.

References

[1] 刘宁,宋正坤,米洪燕,等. 632例颌面部骨折患者临床资料的回顾性研究[J].河南医学研究,2022,31(4):606-609.
[2] 许桂坤,黄艳玲,龙洁.口腔颌面部间隙感染的相关研究及治疗进展[J].西部医学,2022,34(4):615-619.
[3] 郑德攀,吴兴源,周才盛,等.踝关节骨折术后手术部位感染的危险因素分析及预测模型构建[J].创伤外科杂志,2022,24(12):895-901.
[4] 王洋,田壮,刘伟,等.老年髋部骨折患者术后泌尿系感染的危险因素及风险预测模型构建[J].中国老年学杂志,2022,42(8):1863-1866.
[5] Li W, Wang Y, Zhang Z, et al. A risk prediction model for postoperative recovery of closed calcaneal fracture: a retrospective study[J]. J Orthop Surg Res, 2023, 18(1):612.
[6] Khan TU, Rahat S, Khan ZA, et al. Etiology and pattern of maxillofacial trauma[J]. PLoS One, 2022, 17(9):e0275515.
[7] 钱浩亮. 下颌骨骨折临床特征及相关解剖学因素分析[D].南京医科大学,2018.
[8] Jain P, Rathee M. Mandible body fracture[M]. StatPearls Publishing, 2023.
[9] 刘志敏,鲁敏佳,朱晨,等.口腔颌面部骨折病人心理痛苦现状及其影响因素[J].循证护理,2024,10(1):184-186.
[10] Metsemakers WJ, Onsea J, Neutjens E, et al. Prevention of fracture-related infection: a multidisciplinary care package[J]. Int Orthop, 2017, 41(12):2457-2469.
[11] Depypere M, Morgenstern M, Kuehl R, et al. Pathogenesis and management of fracture-related infection[J]. Clin Microbiol Infect, 2020, 26(5):572-578.
[12] Xu H, Yu L, Li Y, et al. Prolonged surgical duration, higher body mass index and current smoking increases risk of surgical site infection after intra-articular fracture of distal femur[J]. ANZ J Surg, 2019, 89(6):723-728.
[13] Zhao D, Liang GH, Pan JK, et al. Risk factors for postoperative surgical site infections after anterior cruciate ligament reconstruction: a systematic review and meta-analysis[J]. Br J Sports Med, 2023, 57(2):118-128.
[14] 刘敏,朱凤.骨盆骨折急诊术后感染的危险因素、病原菌特点及诊断指标分析[J].重庆医学,2024,53(7):1009-1015.
[15] 刘坚,刘佳,凌越,等.老年患者股骨颈骨折术后感染危险因素及 NLR、TLR2、SDF-1的预测价值[J].中华医院感染学杂志,2024,34(2):226-230.
[16] 吴彬,张雄军,李国湘.胫骨开放性骨折术后感染的危险因素及NLRP3信号通路变化[J].中华医院感染学杂志,2023,33(18):2810-2814.
[17] 王宇婷,赵媛,杨勇昆.踝关节骨折切开复位内固定术后感染发生情况及影响因素分析[J].中国医药导报,2024,21(6):94-97.
[18] Hodgson K, Morris J, Bridson T, et al. Immunological mechanisms contributing to the double burden of diabetes and intracellular bacterial infections[J]. Immunology, 2015, 144(2):171-185.
[19] 刘月华,田宇.糖尿病与根尖周炎相关关系研究进展[J].口腔医学研究,2024,40(4):283-286.
[20] Edmonston DL, Foulkes GD. Infection rate and risk factor analysis in an orthopaedic ambulatory surgical center[J]. J Surg Orthop Adv, 2010, 19(3):174-176.
[21] 王燕,韩佳慧,徐策,等.开放性骨折患者低白蛋白血症与手术部位感染的相关性[J].中国病原生物学杂志,2022,17(1):110-113.
[22] Metsemakers WJ, Morgenstern M, Senneville E, et al. General treatment principles for fracture-related infection: recommendations from an international expert group[J]. Arch Orthop Trauma Surg, 2020, 140(8):1013-1027.
[23] 王伟,刘晓玲.骨折合并糖尿病老年手术患者血糖控制和并发症的观察[J].糖尿病新世界,2021,24(3):27-29.
[24] Liu XJ, Han J, Su X. Influence of continuous nursing on surgical site wound infection and postoperative complication for colorectal cancer patients with stoma: A meta-analysis[J]. Int Wound J, 2024, 21(4):e14480.
[25] Alverdy JC, Hyman N, Gilbert J. Re-examining causes of surgical site infections following elective surgery in the era of asepsis[J]. Lancet Infect Dis, 2020, 20(3):e38-e43.