A Graph Attention Network Framework for Surgical Site Infection Prediction Integrating Intraoperative Variables, Surgeon Experience, and Comorbidity Graphs

cirpublications.com-6OCe-1790880684-m957332645 1790880684 Clinical Intelligence Research Press info@cirpublications.com Clinical Intelligence Research Press Journal of Artificial Intelligence for Healthcare Systems J. Artif. Intell. Healthc. Syst. 3149-8981 2025 4 1 A Graph Attention Network Framework for Surgical Site Infection Prediction Integrating Intraoperative Variables, Surgeon Experience, and Comorbidity Graphs Elena Petrova Ivan Georgiev Nikolay Stoyanov Petar Kolev 2025 10.68159/m957332645 https://cirpublications.com/pub/journal/1/article/m957332645 Gillespie BM, Harbeck E, Rattray M, Liang R, Walker R, Latimer S, et al. Worldwide incidence of surgical site infections in general surgical patients: a systematic review and meta-analysis of 488,594 patients. Int J Surg. 2021;95:106136. 10.1016/j.ijsu.2021.106136 Xu Z, Qu H, Gong Z, Kanani G, Zhang F, Ren Y, et al. Risk factors for surgical site infection in patients undergoing colorectal surgery: A meta-analysis of observational studies. PLoS One. 2021;16(10):e0259107. 10.1371/journal.pone.0259107 Fernandez-Moure JS, Wes A, Kaplan LJ, Fischer JP. Actionable risk model for the development of surgical site infection after emergency surgery. Surg Infect (Larchmt). 2021;22(2):168-73. 10.1089/sur.2020.171 Al Mamlook RE, Wells LJ, Sawyer R. Machine-learning models for predicting surgical site infections using patient pre-operative risk and surgical procedure factors. Am J Infect Control. 2023;51(5):544-50. 10.1016/j.ajic.2022.09.020 van Boekel AM, van der Meijden SL, Arbous SM, Nelissen RG, Veldkamp KE, Nieswaag EB, et al. Systematic evaluation of machine learning models for postoperative surgical site infection prediction. PLoS One. 2024;19(12):e0312968. 10.1371/journal.pone.0312968 Zhao D, Liang GH, Pan JK, Zeng LF, Luo MH, Huang HT, et al. Risk factors for postoperative surgical site infections after anterior cruciate ligament reconstruction: a systematic review and meta-analysis. Br J Sports Med. 2023;57(2):118-28. 10.1136/bjsports-2021-105132 Chen T, Liu C, Zhang Z, Liang T, Zhu J, Zhou C, et al. Using machine learning to predict surgical site infection after lumbar spine surgery. Infect Drug Resist. 2023;16:5197-207. 10.2147/IDR.S421171 Akmaz B, van Kuijk SM, Nia PS. Association between individual surgeon volume and outcome in mitral valve surgery: a systematic review. J Thorac Dis. 2021;13(7):4500-12. 10.21037/jtd-20-3310 Van den Broeck T, Oprea-Lager D, Moris L, Kailavasan M, Briers E, Cornford P, et al. A systematic review of the impact of surgeon and hospital caseload volume on oncological and nononcological outcomes after radical prostatectomy for nonmetastatic prostate cancer. Eur Urol. 2021;80(5):531-45. 10.1016/j.eururo.2021.06.032 Bruins HM, Veskimäe E, Hernandez V, Neuzillet Y, Cathomas R, Comperat EM, et al. The importance of hospital and surgeon volume as major determinants of morbidity and mortality after radical cystectomy for bladder cancer: a systematic review and recommendations by the European Association of Urology Muscle-invasive and Metastatic Bladder Cancer Guideline Panel. Eur Urol Oncol. 2020;3(2):131-44. 10.1016/j.euo.2019.11.005 Kuo PJ, Wu SC, Chien PC, Chang SS, Rau CS, Tai HL, et al. Artificial neural network approach to predict surgical site infection after free-flap reconstruction in patients receiving surgery for head and neck cancer. Oncotarget. 2018;9(17):13768-82. 10.18632/oncotarget.24403 Chen KA, Joisa CU, Stem JM, Guillem JG, Gomez SM, Kapadia MR. Improved prediction of surgical-site infection after colorectal surgery using machine learning. Dis Colon Rectum. 2023;66(3):458-66. 10.1097/DCR.0000000000002564 Lu K, Tu Y, Su S, Ding J, Hou X, Dong C, et al. Machine learning application for prediction of surgical site infection after posterior cervical surgery. Int Wound J. 2024;21(4):e14607. 10.1111/iwj.14607 Hopkins BS, Mazmudar A, Driscoll C, Svet M, Goergen J, Kelsten M, et al. Using artificial intelligence (AI) to predict postoperative surgical site infection: a retrospective cohort of 4046 posterior spinal fusions. Clin Neurol Neurosurg. 2020;192:105718. 10.1016/j.clineuro.2020.105718 Veličković P, Cucurull G, Casanova A, Romero A, Lio P, Bengio Y. Graph attention networks. arXiv. 2017;arXiv:1710.10903. 10.48550/arXiv.1710.10903 Sun Z, Yin H, Chen H, Chen T, Cui L, Yang F. Disease prediction via graph neural networks. IEEE J Biomed Health Inform. 2021;25(3):818-26. 10.1109/JBHI.2020.3004844 Zhang XM, Liang L, Liu L, Tang MJ. Graph neural networks and their current applications in bioinformatics. Front Genet. 2021;12:690049. 10.3389/fgene.2021.690049 Johnson R, Li MM, Noori A, Queen O, Zitnik M. Graph artificial intelligence in medicine. Annu Rev Biomed Data Sci. 2024;7(1):345-68. 10.1146/annurev-biodatasci-092123-114708 Tariq A, Lancaster L, Elugunti P, Siebeneck E, Noe K, Borah B, et al. Graph convolutional network-based fusion model to predict risk of hospital acquired infections. J Am Med Inform Assoc. 2023;30(6):1056-67. Song K, Park H, Lee J, Kim A, Jung J. COVID-19 infection inference with graph neural networks. Sci Rep. 2023;13(1):11469. 10.1038/s41598-023-38323-5 Peng XQ, Sun CG, Fei ZG, Zhou QJ. Risk factors for surgical site infection after spinal surgery: a systematic review and meta-analysis based on twenty-seven studies. World Neurosurg. 2019;123:e318-e329. 10.1016/j.wneu.2018.11.158 Roberts DJ, Nagpal SK, Stelfox HT, Brandys T, Corrales-Medina V, Dubois L, et al. Risk factors for surgical site infection after lower limb revascularization surgery in adults with peripheral artery disease: protocol for a systematic review and meta-analysis. JMIR Res Protoc. 2021;10(9):e28759. 10.2196/28759 Chikwe J, Toyoda N, Anyanwu AC, Itagaki S, Egorova NN, Boateng P, et al. Relation of mitral valve surgery volume to repair rate, durability, and survival. J Am Coll Cardiol. 2017;69(19):2397-406. 10.1016/j.jacc.2017.02.026 Franchi E, Donadon M, Torzilli G. Effects of volume on outcome in hepatobiliary surgery: a review with guidelines proposal. Glob Health Med. 2020;2(5):292-7. 10.35772/ghm.2020.01063 Ju IE, Trieu D, Chang SB, Mungovan SF, Patel MI. Surgeon experience and erectile function after radical prostatectomy: a systematic review. Sex Med Rev. 2021;9(4):650-8. 10.1016/j.sxmr.2021.04.003 Trieu D, Ju IE, Chang SB, Mungovan SF, Patel MI. Surgeon case volume and continence recovery following radical prostatectomy: a systematic review. ANZ J Surg. 2021;91(4):521-9. 10.1111/ans.16503 Zitnik M, Agrawal M, Leskovec J. Modeling polypharmacy side effects with graph convolutional networks. Bioinformatics. 2018;34(13):i457-i466. Li X, Wang Y, Wang D, Yuan W, Peng D, Mei Q. Improving rare disease classification using imperfect knowledge graph. BMC Med Inform Decis Mak. 2019;19(Suppl 5):238. 10.1186/s12911-019-0955-6 Arvind V, Kim JS, Oermann EK, Kaji D, Cho SK. Predicting surgical complications in adult patients undergoing anterior cervical discectomy and fusion using machine learning. Neurospine. 2018;15(4):329-37. 10.14245/ns.1836194.097