收稿日期: 2021-10-10
网络出版日期: 2022-02-21
基金资助
国家自然科学基金(82002878);北京大学口腔医院青年基金(YS020219)
Analysis of etiological characteristics and establishment of prediction model of postoperative infections in patients undergoing oral squamous cell carcinoma surgery with free flap reconstruction
Received date: 2021-10-10
Online published: 2022-02-21
Supported by
Nation Natural Science Foundation of China(82002878);Peking University Hospital of Stomatology Young Foundation(YS020219)
目的: 旨在发现行根治性肿瘤切除、颈淋巴结清扫并游离皮瓣修复重建术的原发性口腔鳞状细胞癌患者术后感染的病原学特征,并构建感染风险预测模型。方法: 选取2018年1月至2020年12月在北京大学口腔医院行根治性肿瘤切除并游离皮瓣修复重建术的口腔鳞状细胞癌患者1 596例为研究对象,按照患者术后感染发生情况分为感染组(n=154)和未感染组(n=1 442), 分析感染组患者的病原菌特征。以患者是否发生术后感染作为结果变量,采用单因素和多因素Logistic回归分析来确定术后感染的相关因素,并用于构建感染风险预测模型,采用受试者工作特征(receiver operating characteristic,ROC)曲线评估模型的预测效能。结果: 1 596例口腔鳞状细胞癌患者行修复重建术后发生感染154例,感染率为9.65%,感染部位以手术切口和呼吸道为主;共培养分离病原菌268株,其中革兰阴性菌240株,占89.55%,以铜绿假单胞菌(Pseudomonas aeruginosa)和肺炎克雷伯菌(Klebsiella pneumoniae)为主;革兰阳性菌23株,占8.58%,以粪肠球菌(Enterococcus faecalis)和金黄色葡萄球菌(Staphylococcus aureus)为主;真菌5株,占1.87%。分离出的铜绿假单胞菌对亚胺培南和美罗培南的耐药率较高,对环丙沙星等比较敏感;分离出的金黄色葡萄球菌对红霉素和克林霉素耐药率较高,对万古霉素敏感。N分期≥1、美国麻醉医师协会(American Society of Anesthesiologists,ASA)分级≥Ⅱ级、气管切开、住院天数>13 d是患者术后感染的独立危险因素(P<0.05), 据此构建感染风险预测模型的表达式为:预测概率值P=1/(1+e-a),a=-0.803+0.674×(N分期≥1)+0.518×(ASA分级≥Ⅱ级)+0.918×(气管切开)+1.581×(住院天数>13 d),Hosmer-Lemeshow χ2=10.647,P=0.223,提示模型的拟合度较好。模型预测患者术后感染的ROC曲线下面积为0.818,95%CI为0.789~0.846。结论: 口腔鳞状细胞癌修复重建术后感染发生率较高,主要致病菌为革兰阴性菌。多因素Logistic回归分析构建的感染预测模型可以有效预测口腔鳞状细胞癌修复重建术后感染的发生,使临床能够有针对性地采取监测和干预措施,合理使用抗菌药物,有利于预防和减少术后感染。
苏俊琪 , 宋扬 , 谢尚 . 口腔鳞状细胞癌患者修复重建术后感染的病原学特征及感染风险预测模型的构建[J]. 北京大学学报(医学版), 2022 , 54(1) : 68 -76 . DOI: 10.19723/j.issn.1671-167X.2022.01.011
Objective: To investigate the characteristics of pathogen infection and to establish a prediction model of infections in oral squamous cell carcinoma patients undergoing surgery with free flap reconstruction. Methods: The retrospective cohort study consisted of 1 596 patients undergoing tumor resection and free flap reconstruction for oral squamous cell carcinoma from January 2018 to December 2020. According to the postoperative infection, the patients were divided into the infected group (n=154) and non-infected group (n=1 442). The characteristics of pathogens were analyzed in the infected patients. The primary outcome variable was postoperative infection, and Logistic regression was used to determine risk factors of the infection. The prediction model was established and the discriminatory accuracy of the model was evaluated using receiver operating characteristic (ROC) curve. Results: Totally 154 cases were infected in the 1 596 cases undergoing surgery with free flap reconstruction, and the infection rate was 9.65%. The most frequent sites of infection were the surgical wound and respiratory tract. A total of 268 pathogens were isolated and cultured, including 240 strains of Gram-negative bacteria, accounting for 89.55%, mainly Pseudomonas aeruginosa and Klebsiella pneumoniae; 23 strains of Gram-positive bacteria, accounting for 8.58%, mainly Enterococcus faecalis and Staphylococcus aureus; and 5 strains of fungi, accounting for 1.87%. The isolated Pseudomonas aeruginosa had high resistant rate to imipenem and meropenem, and was sensitive to antibiotics, such as ciprofloxacin. The isolated Staphylococcus aureus had high resistant rate to erythromycin and clindamycin, and was sensitive to vancomycin. According to the multivariate Logistic analysis, four independent variables were significantly associated with an increased risk of postoperative infection (P<0.05): clinical N category≥1, the American Society of Anesthesiologists (ASA) grade ≥2, tracheotomy and length of hospital stay >13 d. The prediction model was established based on these factors and the expression of the risk prediction model was as follows: predicted probability value P=1/(1+e-a), a=-0.803+0.674×(clinical N category ≥1)+0.518×(the ASA grade ≥2)+0.918×(tracheotomy)+1.581×(length of hospital stay >13 d), Hosmer-Lemeshow χ2=10.647, P=0.223, the degree of fitting of the model was good. The area under the ROC curve was 0.818 and 95%CI of the model for predicting infection was 0.789-0.846. Conclusion: Oral squamous cell carcinoma patients undergoing surgery with free flap reconstruction are prone to have a high incidence of postoperative infection and Gram-negative bacteria are the main pathogens causing an infection. The established prediction model is of good predictive effect. Rational antimicrobial use coupled with awareness of infection control measures is paramount to reduce the incidence of postoperative infection in the oral squamous cell carcinoma patients undergoing surgery with free flap reconstruction.
| [1] | Panarese I, Aquino G, Ronchi A, et al. Oral and oropharyngeal squamous cell carcinoma: Prognostic and predictive parameters in the etiopathogenetic route[J]. Expert Rev Anticancer ther, 2019, 19(2):105-119. |
| [2] | Cannon RB, Houlton JJ, Mendez E, et al. Methods to reduce postoperative surgical site infections after head and neck oncology surgery[J]. Lancet Oncol, 2017, 18(7):e405-e413. |
| [3] | McBain AJ, Sissons C, Ledder RG, et al. Development and cha-racterization of a simple perfused oral microcosm[J]. J Appl Microbiol, 2005, 98(3):624-634. |
| [4] | Jansisyanont P, Kasemsai W, Bamroong P. Factors related to the treatment outcome of maxillofacial fascia space infection[J]. J Oral Max Surg Med Pathol, 2015, 27(4):458-464. |
| [5] | 张建丽, 刘玉坤, 任起辉, 等. 行口腔颌面外科术患者术后感染病原学特征及相关因素分析[J]. 中华医院感染学杂志, 2018, 28(3):440-443. |
| [6] | 李月莉, 苏翠霞, 高凤蕊, 等. 口腔颌面外科患者气管切开术后肺部感染的病原学分析及干预对策[J]. 中华医院感染学杂志, 2014, 24(5):1239-1241. |
| [7] | Manchon A, Prados-Frutos JC, Rueda-Rodriguez C, et al. Anti-biotic release from calcium phosphate materials in oral and maxillofacial surgery: Molecular, cellular and pharmaceutical aspects[J]. Curr Pharm Biotechnol, 2017, 18(1):52-63. |
| [8] | 刘登峰, 孙仁义, 肖进, 等. 口腔颌面外科患者医院感染病原菌分布及耐药性分析[J]. 中华医院感染学杂志, 2014, 24(23):5928-5930. |
| [9] | 李新芳, 顾华芳, 顾永华, 等. 肠杆菌科细菌耐药性与抗菌药物使用强度的相关性分析[J]. 中华医院感染学杂志, 2016, 26(1):16-18. |
| [10] | Batard E, Ollivier F, Boutoille D, et al. Relationship between hospital antibiotic use and quinolone resistance in Escherichia coli[J]. Int J Infect Dis, 2013, 17(4):e254-e258. |
| [11] | 解泽强, 菅记涌, 孙盼盼, 等. 2010—2015年医院铜绿假单胞菌感染分布及耐药性分析[J]. 中华医院感染学杂志, 2017, 27(3):498-500. |
| [12] | 张艳, 魏华波, 王志强, 等. 医院感染铜绿假单胞菌的分布及耐药性研究[J]. 中华医院感染学杂志, 2014, 24(13):3139-3141. |
| [13] | 侯飞, 王玲, 崔伟锋, 等. 铜绿假单胞菌医院感染的危险因素及耐药性分析[J]. 中华医院感染学杂志, 2013, 23(16):4050-4052. |
| [14] | Zhao Y, Guo L, Li J, et al. Molecular epidemiology, antimicro-bial susceptibility, and pulsed-field gel electrophoresis genotyping of Pseudomonas aeruginosa isolates from mink[J]. Can J Vet Res, 2018, 82(4):256-263. |
| [15] | Shanthi J, Pazhanimurugan R, Gopikrishnan V, et al. Mechanism of drug resistance, characterization of plasmid-borne determinants and transformation study in P. aeruginosa from burn and ICU units-its susceptibility pattern[J]. Burns, 2013, 39(4):643-649. |
| [16] | 郑百慧, 龚春梅, 黎敏, 等. 呼吸与危重症医学病房分离的碳青霉烯耐药铜绿假单胞菌的分子流行病学[J]. 中华医院感染学杂志, 2020, 30(17):2610-2614. |
| [17] | Oliveira MC, Oliveira CR, Gonçalves KV, et al. Enterobacte-riaceae resistant to third generation cephalosporins upon hospital admission: Risk factors and clinical outcomes[J]. Braz J Infect Dis, 2015, 19(3):239-245. |
| [18] | Guo Z, Zhang J, Gong Z, et al. Correlation of factors associated with postoperative infection in patients with malignant oral and maxillofacial tumours: A Logistic regression analysis[J]. Br J Oral Maxillofac Surg, 2019, 57(5):460-465. |
| [19] | Anehosur VS, Karadiguddi P, Joshi VK, et al. Elective tracheostomy in head and neck surgery: Our experience[J]. J Clin Diagn Res, 2017, 11(5): ZC36-ZC39. |
| [20] | Goetz C, Burian NM, Weitz J, et al. Temporary tracheotomy in microvascular reconstruction in maxillofacial surgery: Benefit or threat?[J]. J Craniomaxillofac Surg, 2019, 47(4):642-646. |
| [21] | Li L, Yuan W, Zhang S, et al. Analysis of risk factors for pneumonia in 482 patients undergoing oral cancer surgery with tracheo-tomy[J]. J Oral Maxillofac Surg, 2016, 74(2):415-419. |
| [22] | Xu J, Hu J, Yu P, et al. Perioperative risk factors for postoperative pneumonia after major oral cancer surgery: A retrospective analysis of 331 cases[J]. PLoS One, 2017, 12(11):e0188167. |
| [23] | Algar FJ, Alvarez A, Salvatierra A, et al. Predicting pulmonary complications after pneumonectomy for lung cancer[J]. Eur J Cardiothorac Surg, 2003, 23(2):201-208. |
| [24] | Maeng SH, Yoo HS, Choi SH, et al. Impact of parainfluenza virus infection in pediatric cancer patients[J]. Pediatr Blood Cancer, 2012, 59(4):708-710. |
| [25] | Liu P, Li X, Luo M, et al. Risk factors for carbapenem-resistant Klebsiella pneumoniae infection: A meta-analysis[J]. Microb Drug Resist, 2018, 24(2):190-198. |
| [26] | Zhu WM, Yuan Z, Zhou HY. Risk factors for carbapenem-resis-tant Klebsiella pneumoniae infection relative to two types of control patients: A systematic review and meta-analysis[J]. Antimicrob Resist Infect Control, 2020, 9(1):23. |
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