Current trends in laparoscopic hernioplasty TAPP

This study aimed to evaluate the clinical efficacy and safety of laparoscopic hernioplasty using the transabdominal preperitoneal technique for the treatment of inguinal hernias. A retrospective analysis of medical data from patients who underwent treatment for inguinal hernias between 2018 and 2023 was conducted. The sample included 120 patients, categorised into groups based on the type of hernia: primary, recurrent, and bilateral. Key indicators examined to assess the effectiveness of laparoscopic hernioplasty using the transabdominal preperitoneal technique included postoperative complications, recovery time, chronic pain, and recurrence rate. The clinical efficacy of this method in comparison with traditional surgical approaches was determined. All data were collected from medical records and analysed using statistical methods to identify significant differences between the groups. Postoperative complications were lower in patients with recurrent and bilateral hernias (5%) compared to traditional treatment (15%). Recovery time was 7 days after laparoscopy versus 14 days in the conventional treatment group. Chronic pain after 6 months was significantly lower (10 vs. 25%), and the recurrence rate was only 2%. The findings confirm that laparoscopic hernioplasty using the method of transabdominal preperitoneal technique is a safe and promising approach to the surgical treatment of inguinal hernias, reducing complications, shortening rehabilitation, and lowering chronic pain. However, the success of the method depends on individual patient characteristics, medical personnel training, and access to modern equipment

minimally invasive hernia repair; Lichtenstein technique; outpatient surgical treatment; open hernia repair techniques; inguinal canal diseases

https://doi.org/10.61751/ijmmr/2.2024.49

[1] Patterson TJ, Beck J, Currie PJ, Spence RAJ, Spence G. Meta-analysis of patient-reported outcomes after laparoscopic versus open inguinal hernia repair. British J Surg. 2019;106(7):824–36. DOI: 10.1002/bjs.11139

[2] Hernia Surge Group. International guidelines for groin hernia management. Hernia. 2018;22: 1–165. DOI: 10.1007/s10029-017-1668-x

[3] Chen LS, Chen WC, Kang YN, Wu CC, Tsai LW, Liu MZ. Effects of transabdominal pre-peritoneal and totally extraperitoneal inguinal hernia repair: An update systematic review and meta-analysis of randomized controlled trials. Surg Endosc. 2019;33(2):418–28. DOI: 10.1007/s00464-018-6314-x

[4] Gavriilidis P, Davies RJ, Wheeler J, De’Angelis N, Di Saverio S. Total extraperitoneal endoscopic hernioplasty (TEP) versus Lichtenstein hernioplasty: A systematic review by updated traditional and cumulative meta-analysis of randomised-controlled trials. Hernia. 2019;23(6):1093–103. DOI: 10.1007/s10029-019-02049-w

[5] Ielpo B, Ferri N, Silva J, Quijano Y, Vicente E, Diago MV, et al. Laparoscopic transabdominal pre-peritoneal (TAPP) inguinal hernia repair using fibrin glue for fixation of the mesh and peritoneum closure. Surg Laparosc Endosc Percutan Tech. 2020;30(4):e24–7. DOI: 10.1097/SLE.0000000000000797

[6] Zheng Z, Tan C, Mao S, Duan J. Novel use of laparoscopic-assisted transinguinal technique for preperitoneal inguinal hernia repair: First case. Asian J Surg. 2020;43(7):773–4. DOI: 10.1016/j.asjsur.2020.02.009

[7] Gülaydin N, Ersöz F, Kalayci M, Kara E. Endoscopic hernia repair: A novel technique for the repair of inguinal hernia in a cadaver model. Surg Laparosc Endosc Percutan Tech. 2021;31(4):404–7. DOI: 10.1097/SLE.0000000000000935

[8] Lyu Y, Cheng Y, Wang B, Du W, Xu Y. Comparison of endoscopic surgery and Lichtenstein repair for treatment of inguinal hernias: A network meta-analysis. Med. 2020;99(6):e19134. DOI: 10.1097/MD.0000000000019134

[9] Jeroukhimov I, Dykman D, Hershkovitz Y, Poluksht N, Nesterenko V, Yehuda AB, et al. Chronic pain following totally extra-peritoneal inguinal hernia repair: A randomized clinical trial comparing glue and absorbable tackers. Langenbecks Arch Surg. 2023;408(1):190. DOI: 10.1007/s00423-023-02932-2

[10] Shah MY, Raut P, Wilkinson TRV, Agrawal V. Surgical outcomes of laparoscopic total extraperitoneal (TEP) inguinal hernia repair compared with Lichtenstein tension-free open mesh inguinal hernia repair: A prospective randomized study. Med. 2022;101(26):e29746. DOI: 10.1097/MD.0000000000029746

[11] Howard R, Gunaseelan V, Brummett C, Waljee J, Englesbe M, Telem D. New persistent opioid use after inguinal hernia repair. Ann Surg. 2022;276(5):e577–83. DOI: 10.1097/SLA.0000000000004560

[12] Bracale U, Merola G, Sciuto A, Cavallaro G, Andreuccetti J, Pignata G. Achieving the learning curve in laparoscopic inguinal hernia repair by TAPP: A quality improvement study. J Invest Surg. 2018;32(8):738–45. DOI: 10.1080/08941939.2018.1468944

[13] Ielpo B, Duran H, Diaz E, Fabra I, Caruso R, Malavé L, et al. A prospective randomized study comparing laparoscopic transabdominal preperitoneal (TAPP) versus Lichtenstein repair for bilateral inguinal hernias. Am J Surg. 2018;216(1):78–83. DOI: 10.1016/j.amjsurg.2017.07.016

[14] Furtado M, Claus CMP, Cavazzola LT, Malcher F, Bakonyi-Neto A, Saad-Hossne R. Systemization of laparoscopic inguinal hernia repair (TAPP) based on a new anatomical concept: Inverted y and five triangles. ABCD Braz Arch Digest Surg. 2019;32(1):e1426. DOI: 10.1590/0102-672020180001e1426

[15] Misawa M, Kudo S, Mori Y, Cho T, Kataoka S, Yamauchi A, et al. Artificial intelligence-assisted polyp detection for colonoscopy: Initial experience. Gastroenterology. 2018;154(8):2027–9.e3. DOI: 10.1053/j.gastro.2018.04.003

[16] Hirasawa T, Aoyama K, Tanimoto T, Ishihara S, Shichijo S, Ozawa T, et al. Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images. Gastric Cancer. 2018;21(4):653–60. DOI: 10.1007/s10120-018-0793-2

[17] Zhao W, Yang J, Sun Y, Li C, Wu W, Jin L, et al. 3D deep learning from CT scans predicts tumor invasiveness of subcentimeter pulmonary adenocarcinomas. Cancer Res. 2018;78(24):6881–9. DOI: 10.1158/0008-5472.CAN-18-0696

[18] Hashimoto DA, Rosman G, Witkowski ER, Stafford C, Navarette-Welton AJ, Rattner DW, et al. Computer vision analysis of intraoperative video: Automated recognition of operative steps in laparoscopic sleeve gastrectomy. Ann Surg. 2019;270(3):414–21. DOI: 10.1097/sla.0000000000003460

[19] Kitaguchi D, Takeshita N, Matsuzaki H, Oda T, Watanabe M, Mori K, et al. Automated laparoscopic colorectal surgery workflow recognition using artificial intelligence: Experimental research. Int J Surg. 2020;79:88–94. DOI: 10.1016/j.ijsu.2020.05.015

[20] Lundervold AS, Lundervold A. An overview of deep learning in medical imaging focusing on MRI. J Med Phys. 2019;29(2):102–27. DOI: 10.1016/j.zemedi.2018.11.002

[21] Kim M, Yun J, Cho Y, Shin K, Jang R, Bae HJ, et al. Deep learning in medical imaging. Neurospine. 2019;16(4):657–68. DOI: 10.14245%2Fns.1938396.198

[22] Jin Y, Dou Q, Chen H, Yu L, Qin J, Fu CW, et al. SV-RCNet: Workflow recognition from surgical videos using recurrent convolutional network. IEEE Trans Med Imaging. 2018;37(5):1114–26. DOI: 10.1109/TMI.2017.2787657

[23] Guédon ACP, Meij SEP, Osman KNMMH, Kloosterman HA, van Stralen KJ, Grimbergen MCM, et al. Deep learning for surgical phase recognition using endoscopic videos. Surg Endosc. 2021;35(11):6150–7. DOI: 10.1007/s00464-020-08110-5

[24] Fan X, Ding Y, Sun N, Chen Y. Ultra-micro instrument in laparoscopic transabdominal preperitoneal (TAPP) hernioplasty. Updates Surg. 2023;76(2):601–5. DOI: 10.1007/s13304-023-01715-0