Surgical InnovationPub Date : 2024-12-01Epub Date: 2024-08-16DOI: 10.1177/15533506241273449
Chen Chai, Shu-Zhen Peng, Rui Zhang, Cheng-Wei Li, Yan Zhao
{"title":"Advancing Emergency Department Triage Prediction With Machine Learning to Optimize Triage for Abdominal Pain Surgery Patients.","authors":"Chen Chai, Shu-Zhen Peng, Rui Zhang, Cheng-Wei Li, Yan Zhao","doi":"10.1177/15533506241273449","DOIUrl":"10.1177/15533506241273449","url":null,"abstract":"<p><strong>Background: </strong>The development of emergency department (ED) triage systems remains challenging in accurately differentiating patients with acute abdominal pain (AAP) who are critical and urgent for surgery due to subjectivity and limitations. We use machine learning models to predict emergency surgical abdominal pain patients in triage, and then compare their performance with conventional Logistic regression models.</p><p><strong>Methods: </strong>Using 38 214 patients presenting with acute abdominal pain at Zhongnan Hospital of Wuhan University between March 1, 2014, and March 1, 2022, we identified all adult patients (aged ≥18 years). We utilized routinely available triage data in electronic medical records as predictors, including structured data (eg, triage vital signs, gender, and age) and unstructured data (chief complaints and physical examinations in free-text format). The primary outcome measure was whether emergency surgery was performed. The dataset was randomly sampled, with 80% assigned to the training set and 20% to the test set. We developed 5 machine learning models: Light Gradient Boosting Machine (Light GBM), eXtreme Gradient Boosting (XGBoost), Deep Neural Network (DNN), and Random Forest (RF). Logistic regression (LR) served as the reference model. Model performance was calculated for each model, including the area under the receiver-work characteristic curve (AUC) and net benefit (decision curve), as well as the confusion matrix.</p><p><strong>Results: </strong>Of all the 38 214 acute abdominal pain patients, 4208 underwent emergency abdominal surgery while 34 006 received non-surgical treatment. In the surgery outcome prediction, all 4 machine learning models outperformed the reference model (eg, AUC, 0.899 [95%CI 0.891-0.903] in the Light GBM vs. 0.885 [95%CI 0.876-0.891] in the reference model), Similarly, most machine learning models exhibited significant improvements in net reclassification compared to the reference model (eg, NRIs of 0.0812[95%CI, 0.055-0.1105] in the XGBoost), with the exception of the RF model. Decision curve analysis shows that across the entire range of thresholds, the net benefits of the XGBoost and the Light GBM models were higher than the reference model. In particular, the Light GBM model performed well in predicting the need for emergency abdominal surgery with higher sensitivity, specificity, and accuracy.</p><p><strong>Conclusions: </strong>Machine learning models have demonstrated superior performance in predicting emergency abdominal pain surgery compared to traditional models. Modern machine learning improves clinical triage decisions and ensures that critically needy patients receive priority for emergency resources and timely, effective treatment.</p>","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141988970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Role of Qualitative and Quantitative Indocyanine Green Angiography to Assess Mastectomy Skin Flaps Perfusion: A Prospective Monocentric Experience.","authors":"Manuela Mastronardi, Stefano Fracon, Serena Scomersi, Margherita Fezzi, Zaira Pellin, Marina Bortul","doi":"10.1177/15533506241273383","DOIUrl":"10.1177/15533506241273383","url":null,"abstract":"<p><strong>Introduction: </strong>Mastectomy skin flap (MSF) necrosis remains a significant complication in breast reconstruction. This study aims to identify a correlation between the qualitative and quantitative analysis of the MSF perfusion grade and the skin necrosis rate 1 month after surgery using indocyanine green angiography (ICGA), focusing on lag time and perfusion metrics.</p><p><strong>Methods: </strong>Consecutive women scheduled for nipple/skin-sparing/skin-reducing mastectomy between May 2020 and October 2022 were prospectively enrolled. Patients were divided into Group 1 in the absence of superficial and full-thickness necrosis (SN; FTN) and Group 2 in the presence of both. Demographic data, lag time T1 (time between ICG injection and the initial perfusion of the least perfused MSF area), ICG-Q1, and ICG-Q% (absolute and relative perfusion values of the least vascularized area) were collected.</p><p><strong>Results: </strong>76 breasts were considered. FTN was reported in 8 breasts (10.5%) and SN in 4 (5.2%). The 2 groups statistically differ in T1 (Group2 > Group1), ICG-Q1, and ICG-Q% (Group1 > Group2) (<i>P</i> < 0.05). T1 longer than 170 seconds, body mass index, previous chemo/radiotherapy, arterial hypertension, breast weight, type of surgery, and ICG quantitative values can help in predicting MSF necrosis.</p><p><strong>Conclusions: </strong>MSF qualitative and quantitative perfusion evaluation can be helpful to prevent MSF necrosis. However, it should be considered together with the patient's characteristics, the type of surgery, and T1. In this way, it is possible to predict the risk of MSF necrosis and plan the best reconstructive strategy.</p>","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141898297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Surgical InnovationPub Date : 2024-12-01Epub Date: 2024-08-16DOI: 10.1177/15533506241275288
James Williams, Daniel T Lammers, Andrew D Francis, Beau J Prey, Luke I Pumiglia, Matthew J Eckert, Yang Liu, Jason R Bingham, John M McClellan
{"title":"Who Says You can't go FAST at Night? Use of a Novel Ultrasound-Capable Night Vision Device for Prehospital Medical Personnel to Identify Noncompressible Truncal Hemorrhage.","authors":"James Williams, Daniel T Lammers, Andrew D Francis, Beau J Prey, Luke I Pumiglia, Matthew J Eckert, Yang Liu, Jason R Bingham, John M McClellan","doi":"10.1177/15533506241275288","DOIUrl":"10.1177/15533506241275288","url":null,"abstract":"<p><strong>Background: </strong>Early detection of abdominal hemorrhage via ultrasound has life-saving implications for military and civilian trauma. However, strict adherence to light discipline may prohibit the use of ultrasound devices in the deployed setting. Additionally, current night vision devices remain noncompatible with ultrasound technology. This study sought to assess an innovative night vision device with ultrasound capable picture-in-picture display via a intraabdominal hemorrhage model to identify noncompressible truncal hemorrhage in blackout conditions.</p><p><strong>Methods: </strong>8 post mortem fetal porcine specimens were used and divided into 2 groups: intrabdominal hemorrhage (n = 4) vs no hemorrhage (n = 4). Intrabdominal hemorrhage was modeled via direct injection of 200 mL of normal saline into the peritoneal cavity. Under blackout conditions, 5 participants performed a focused assessment with sonography for trauma (FAST) exam on each model using the prototype ultrasound-capable night vision device.</p><p><strong>Results: </strong>Of the 40 FAST exams performed, 95% (N = 38) resulted in the correct identification of intraabdominal hemorrhage. Of the incorrectly identified exams, both were false positives resulting in a 100% sensitivity, 90% specificity, 91% positive predictive value, and a 100% negative predictive value. All participants noted the novel device was easy to use and provided superior visualization for performing FAST exams under blackout conditions.</p><p><strong>Conclusion: </strong>The ultrasound-enabled night vision prototype demonstrated promising results in identifying noncompressible truncal hemorrhage while maintaining strict light discipline in blackout conditions. Further research efforts should be directed at assessing the ability of providers to perform procedures in blackout conditions using the ultrasound-enabled prototype night vision device.</p>","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141996539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Three-Dimensional Holographic-Guided Robotic Lung Segmentectomy for Deep Pulmonary Nodules: Technique and Initial Results.","authors":"Patrick Bagan, Kaouther Aissa, Rime Essid, Wissam Azbabay, Rym Zaimi, Bassel Dakhil","doi":"10.1177/15533506241290069","DOIUrl":"10.1177/15533506241290069","url":null,"abstract":"<p><p><b>Background:</b> Diagnosis and treatment of <i>small and isolated lung</i> nodules remain challenging issues. <b>Purpose:</b> The aim of this article is to report the technique of real-time navigation using holographic reconstruction technology combined with a robot assisted thoracic surgery (RATS) platform for lung resection in patients with <i>small deep nodules</i>.<b>Research Design:</b> The pre-surgery 3D planning was based on the chest CT scan. The reconstruction was uploaded to a head-mounted display for real-time navigation during mini invasive robot assisted surgery performed with an open console platform. We evaluated this technique with the success rate of diagnosis, the operative time and the post-operative course.<b>Study Sample:</b> This technique was performed in 6 patients (4 female, mean age 65 years) to date.<b>Results:</b> The precision of the head-mounted display based localization system was effective in all cases without the need of open conversion. The mean diameter of the nodules was 8 mm (6-9). The diagnosis was a lung cancer (n = 5) and tuberculoma (n = 1). The mean operative time was 125 min (100-145). The mean hospital stay was 2.5 days (1-3).<b>Conclusions:</b> In conclusion, the intraoperative navigation using the 3D holographic assistance was an helpful tool for mini invasive RATS lung segmentectomy without the need of preoperative localization.</p>","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142372915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Surgical InnovationPub Date : 2024-12-01Epub Date: 2024-09-24DOI: 10.1177/15533506241285233
Filip W N Haenen
{"title":"Letter re: Knotless Closure of the Cardiac Arterial Canulation Site Using Barbed Suture.","authors":"Filip W N Haenen","doi":"10.1177/15533506241285233","DOIUrl":"10.1177/15533506241285233","url":null,"abstract":"","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142354231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Surgical InnovationPub Date : 2024-12-01Epub Date: 2024-10-03DOI: 10.1177/15533506241290071
Mohammad Alomari, Ishaq Wadiwala, Steven Bowers, Enrique F Elli, Mathew Thomas
{"title":"Oxygen Saturation Endoscopic Imaging as a Novel Alternative to Assess Tissue Perfusion During Esophagectomy.","authors":"Mohammad Alomari, Ishaq Wadiwala, Steven Bowers, Enrique F Elli, Mathew Thomas","doi":"10.1177/15533506241290071","DOIUrl":"10.1177/15533506241290071","url":null,"abstract":"<p><strong>Background: </strong>Assessment of gastric conduit perfusion during esophagectomy is crucial to determine its viability and identify the optimal site for anastomosis. Indocyanine green (ICG) fluorescence imaging is commonly used for this purpose, but it is contraindicated in patients with hypersensitivity to ICG, iodine, or shellfish. Oxygen saturation endoscopic imaging (OXEI) is a newer, non-pharmacologic technique for assessing perfusion. We report our experience with OXEI in 3 esophagectomy patients who had contraindications to ICG.</p><p><strong>Methods: </strong>All 3 patients underwent robot-assisted esophagectomies. None of the conduits had ischemic areas identified by white light. Using a 5 mm laparoscopic specialized camera (ELUXEO Vision, FUJIFILM Healthcare Americas Corp., USA), OXEI was deployed for intracorporeal assessment of gastric conduit perfusion after pull-up into the chest. Postoperative outcomes including anastomotic leaks and complications were recorded.</p><p><strong>Results: </strong>In two patients, OXEI revealed ischemic zones, which were resected to ensure optimal conduit viability. In the remaining patient, OXEI indicated robust vascularity throughout the conduit. All three patients experienced uneventful postoperative courses and were discharged within 10 days. There were no instances of anastomotic leaks or other major complications.</p><p><strong>Conclusion: </strong>In our experience, OXEI is a viable method for intraoperative assessment of gastric conduit perfusion in patients with contraindications to ICG. Prospective studies are needed to validate its efficacy in preventing anastomotic complications and to compare it with other methods of perfusion assessment including gross visual and ICG dye in a larger patient population.</p>","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142366602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Role of Indocyanine Green With Near-Infrared Imaging for the Intraoperative Detection and Enhancement of Endometriosis Lesions: A Narrative Review.","authors":"Minoli Rajasinghe, Tarana Lucky, Shamitha Kathurusinghe","doi":"10.1177/15533506241290079","DOIUrl":"10.1177/15533506241290079","url":null,"abstract":"<p><p><b>Background:</b> There is a clinical need for improved intraoperative detection of endometriosis, and the use of Indocyanine Green with Near-Infrared Imaging (NIR-ICG) is a novel technique for this purpose. The aim of this review is to determine whether NIR-ICG is an effective tool for endometriosis detection and establish an evidence-based methodology for its use.<b>Methods:</b> This review searches Ovid MEDLINE and Embase through July 2023 and considers primary literature published in English describing the use of NIR-ICG to detect endometriosis intraoperatively. Case studies, video demonstrations and articles describing NIR-ICG used for other surgical roles were not considered. Identified studies were screened independently by two authors, and data was extracted by a single author.<b>Results:</b> NIR-ICG was found to enhance the detection of endometriosis in six out of the nine included studies with additional lesion identification, and to have an unchanged or reduced efficacy compared to current standards in the remaining three. Across all studies there were lesions missed by NIR-ICG which were detected by conventional imaging. A greater duration of time between dye administration and visualisation of lesions was found to be more effective for detection. The ideal ICG protocol proposed from this review is a fixed amount of dye proportional to patient weight prior to surgery (0.25-0.3 mg/kg) followed by a longer waiting time before imaging (10-30 min).<b>Conclusion:</b> NIR-ICG has a possible role to enhance the identification of endometriosis intraoperatively as an adjunct to conventional white light imaging, particularly deeper infiltrating disease. However, substantial further research is required in this field.</p>","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11476485/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142375990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Surgical InnovationPub Date : 2024-12-01Epub Date: 2024-09-01DOI: 10.1177/15533506241281316
Graham J Spurzem, Ryan C Broderick, Patricia R Cota, Bryan J Sandler, Garth R Jacobsen, Santiago Horgan
{"title":"Early Experience With a Novel Super-Hydrophilic Laparoscopic Scope Cleaning Device and Narrative Review of Available Cleaning Strategies.","authors":"Graham J Spurzem, Ryan C Broderick, Patricia R Cota, Bryan J Sandler, Garth R Jacobsen, Santiago Horgan","doi":"10.1177/15533506241281316","DOIUrl":"10.1177/15533506241281316","url":null,"abstract":"<p><strong>Background: </strong>Impaired visibility is a challenge in laparoscopic surgery. Frequent scope removal increases operative time, reduces efficiency, and potentially compromises patient safety. We examine our initial experience with a novel cleaning device that applies cold plasma to the scope lens and review current available laparoscope cleaning methods.</p><p><strong>Methods: </strong>The novel device was used in a variety of laparoscopic general surgery cases from April to November 2023. Primary outcome was number of scope removals per case. Secondary outcomes were time spent cleaning and number of times the scope became smudged or dirty with blood/tissue debris (debris events). An existing device that utilizes heated anti-fogging solution was used for comparison.</p><p><strong>Results: </strong>97 cases were included (31 with novel device and 66 with existing device). Scope removal rate for the novel device was lower compared to the existing device (0.87 ± 1.02 vs 0.97 ± 1.20 removals/case, <i>P</i> = 0.69), but not statistically significant. Average number of debris events was also lower for the novel device, but not statistically significant (0.90 ± 0.94 vs 1.0 ± 1.18 debris events/case, <i>P</i> = 0.69). Average total time spent cleaning per case was similar between devices (16.9 ± 24.0 vs 15.9 ± 18.7 seconds, <i>P</i> = 0.82).</p><p><strong>Conclusion: </strong>This study demonstrates that a hydrophilic scope cleaning device has comparable performance to heated anti-fogging solution and may reduce scope removals and debris events. Direct comparisons between cleaning products are lacking. Surgeons are most likely to be successful with the cleaning strategy that best suits one's surgical practice.</p>","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11475763/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142112260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Surgical InnovationPub Date : 2024-12-01Epub Date: 2024-10-04DOI: 10.1177/15533506241289481
Minh-Hieu Le, Thu-Thao Le, Phung Phi Tran
{"title":"AI in Surgery: Navigating Trends and Managerial Implications Through Bibliometric and Text Mining Odyssey.","authors":"Minh-Hieu Le, Thu-Thao Le, Phung Phi Tran","doi":"10.1177/15533506241289481","DOIUrl":"10.1177/15533506241289481","url":null,"abstract":"<p><p><b>Background: </b>This research employs bibliometric and text-mining analysis to explore artificial intelligence (AI) advancements within surgical procedures. The growing significance of AI in healthcare underscores the need for healthcare managers to prioritize investments in this technology. <b>Purpose: </b>To assess the increasing impact of AI on surgical practices through a comprehensive analysis of scientific literature, providing insights that can guide managerial decision-making in adopting AI solutions.<b>Research Design:</b> The study analyzes over 6000 scientific articles published since 1990 to evaluate trends and contributions in the field, informing managers about the current landscape of AI in surgery.<b>Study Sample:</b> The research focuses on publications from various influential publishers across North America, Northern Asia, and Eastern & Western Europe, highlighting key markets for AI implementation in surgical settings.<b>Data Collection and Analysis: </b>A bibliometric approach was utilized to identify key contributors and influential journals. At the same time, text-mining techniques highlighted significant keywords related to AI in surgery, aiding managers in recognizing essential areas for further exploration and investment.<b>Results: </b>The year 2022 marked a significant upsurge in publications, indicating widespread AI integration in healthcare. The U.S. emerged as the foremost contributor, followed by China, the UK, Germany, Italy, the Netherlands, and India. Key journals, such as Annals of Surgery and Spine Journal, play a crucial role in disseminating research findings, serving as valuable resources for managers seeking to stay informed.<b>Conclusions:</b> The findings underscore AI's pivotal role in enhancing diagnostic precision, predicting treatment outcomes, and improving operational efficiency in surgical practices. This progress represents a significant milestone in modern medical science, paving the way for intelligent healthcare solutions and further advancements in the field. Healthcare managers should leverage these insights to foster innovation and improve patient care standards.</p>","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142375988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Surgical InnovationPub Date : 2024-12-01Epub Date: 2024-10-04DOI: 10.1177/15533506241289482
Vancanneyt N, Tollens T, Baekelandt J
{"title":"Epigastric Ventral Hernia Repair Through Vaginal Natural Orifice Transluminal Endoscopic Surgery.","authors":"Vancanneyt N, Tollens T, Baekelandt J","doi":"10.1177/15533506241289482","DOIUrl":"10.1177/15533506241289482","url":null,"abstract":"<p><strong>Objective: </strong>Ventral hernia repair is a commonly performed operation and can be executed by open or laparoscopic approach. The search for even less invasive techniques continues. Natural orifice transluminal endoscopic surgery (NOTES) is a known method of minimally invasive surgery.</p><p><strong>Methods: </strong>We performed an epigastric ventral hernia repair through vaginal NOTES during a concurrent hysterectomy and bilateral salpingectomy. We used the access to do a synchronous hernia repair with mesh augmentation. The technique of repair was identical to the laparoscopic intraperitoneal onlay mesh repair (Lap. IPOM).</p><p><strong>Results: </strong>We reported a sufficient hernia repair without intra-operative complications. Also, post-operatively, no problems were encountered. Follow-up after 4 weeks showed a good and strong hernia repair. The complaints of the patient were relieved. CT scan 10 months after operation showed no recurrence nor signs of mesh infection.</p><p><strong>Conclusions: </strong>Ventral hernia repair through vaginal NOTES can be considered a possible new and minimal invasive (scarless) technique for ventral hernia repair but further investigations on a larger scale are needed to confirm feasibility & safety.</p>","PeriodicalId":22095,"journal":{"name":"Surgical Innovation","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142375989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}