Identification of technical errors and hazard zones in sleeve gastrectomy using OCHRA : "OCHRA for sleeve gastrectomy"

Glucagon-Like Peptide 1 Receptor (Glp1r) Deficiency Does Not Appreciably Alter Airway Inflammation or Gut-Lung Microbiome Axis in a Mouse Model of Obese Allergic Airways Disease and Bariatric Surgery

Purpose

High body mass index (≥30 kg/m2) is associated with asthma severity, and nearly 40% of asthma patients exhibit obesity. Furthermore, over 40% of patients with obesity and asthma that receive bariatric surgery no longer require asthma medication. Increased levels of glucagon-like peptide 1 (GLP-1) occur after bariatric surgery, and recent studies suggest that GLP-1 receptor (GLP-1R) signaling may regulate the gut microbiome and have anti-inflammatory properties in the lung. Thus, we hypothesized that increased GLP-1R signaling following metabolic surgery in obese and allergen-challenged mice leads to gut/lung microbiome alterations, which together contribute to improved features of allergic airways disease.

Methods

Male and female Glp1r-deficient (Glp1r-/- ) and replete (Glp1r+/+) mice were administered high fat diet (HFD) to induce obesity with simultaneous intranasal challenge with house dust mite (HDM) allergen to model allergic airway disease with appropriate controls. Mice on HFD received either no surgery, sham surgery, or vertical sleeve gastrectomy (VSG) on week 10 and were sacrificed on week 13. Data were collected with regard to fecal and lung tissue microbiome, lung histology, metabolic markers, and respiratory inflammation.

Results

HFD led to metabolic imbalance characterized by lower GLP-1 and higher leptin levels, increased glucose intolerance, and alterations in gut microbiome composition. Prevalence of bacteria associated with short chain fatty acid (SCFA) production, namely Bifidobacterium, Lachnospiraceae UCG-001, and Parasutterella, was reduced in mice fed HFD and positively associated with serum GLP-1 levels. Intranasal HDM exposure induced airway inflammation. While Glp1r-/- genotype affected fecal microbiome beta diversity metrics, its effect was limited.

Conclusion

Herein, GLP-1R deficiency had surprisingly little effect on host gut and lung microbiomes and health, despite recent studies suggesting that GLP-1 receptor agonists are protective against lung inflammation.

Surgical step recognition in laparoscopic distal gastrectomy using artificial intelligence: a proof-of-concept study

PURPOSE

Laparoscopic distal gastrectomy (LDG) is a difficult procedure for early career surgeons. Artificial intelligence (AI)-based surgical step recognition is crucial for establishing context-aware computer-aided surgery systems. In this study, we aimed to develop an automatic recognition model for LDG using AI and evaluate its performance.

METHODS

Patients who underwent LDG at our institution in 2019 were included in this study. Surgical video data were classified into the following nine steps: (1) Port insertion; (2) Lymphadenectomy on the left side of the greater curvature; (3) Lymphadenectomy on the right side of the greater curvature; (4) Division of the duodenum; (5) Lymphadenectomy of the suprapancreatic area; (6) Lymphadenectomy on the lesser curvature; (7) Division of the stomach; (8) Reconstruction; and (9) From reconstruction to completion of surgery. Two gastric surgeons manually assigned all annotation labels. Convolutional neural network (CNN)-based image classification was further employed to identify surgical steps.

RESULTS

The dataset comprised 40 LDG videos. Over 1,000,000 frames with annotated labels of the LDG steps were used to train the deep-learning model, with 30 and 10 surgical videos for training and validation, respectively. The classification accuracies of the developed models were precision, 0.88; recall, 0.87; F1 score, 0.88; and overall accuracy, 0.89. The inference speed of the proposed model was 32 ps.

CONCLUSION

The developed CNN model automatically recognized the LDG surgical process with relatively high accuracy. Adding more data to this model could provide a fundamental technology that could be used in the development of future surgical instruments.

Real-time detection of active bleeding in laparoscopic colectomy using artificial intelligence

BACKGROUND

Most intraoperative adverse events (iAEs) result from surgeons' errors, and bleeding is the majority of iAEs. Recognizing active bleeding timely is important to ensure safe surgery, and artificial intelligence (AI) has great potential for detecting active bleeding and providing real-time surgical support. This study aimed to develop a real-time AI model to detect active intraoperative bleeding.

METHODS

We extracted 27 surgical videos from a nationwide multi-institutional surgical video database in Japan and divided them at the patient level into three sets: training (n = 21), validation (n = 3), and testing (n = 3). We subsequently extracted the bleeding scenes and labeled distinctively active bleeding and blood pooling frame by frame. We used pre-trained YOLOv7_6w and developed a model to learn both active bleeding and blood pooling. The Average Precision at an Intersection over Union threshold of 0.5 (AP.50) for active bleeding and frames per second (FPS) were quantified. In addition, we conducted two 5-point Likert scales (5 = Excellent, 4 = Good, 3 = Fair, 2 = Poor, and 1 = Fail) questionnaires about sensitivity (the sensitivity score) and number of overdetection areas (the overdetection score) to investigate the surgeons' assessment.

RESULTS

We annotated 34,117 images of 254 bleeding events. The AP.50 for active bleeding in the developed model was 0.574 and the FPS was 48.5. Twenty surgeons answered two questionnaires, indicating a sensitivity score of 4.92 and an overdetection score of 4.62 for the model.

CONCLUSIONS

We developed an AI model to detect active bleeding, achieving real-time processing speed. Our AI model can be used to provide real-time surgical support.

The relationship between the esophageal endoscopic submucosal dissection technical difficulty and its intraoperative process

BACKGROUND

Estimating the esophageal endoscopic submucosal dissection (ESD) technical difficulty is important to reduce complications. Endoscopic duration is one of the related factors to a technical difficulty. The relationship between the esophageal ESD technical difficulty and its intraoperative process was analyzed as a first step toward automatic technical difficulty recognition using artificial intelligence.

METHODS

This study enrolled 75 patients with superficial esophageal cancer who underwent esophageal ESD. The technical difficulty score was established, which consisted of three factors, including total procedure duration, en bloc resection, and complications. Additionally, technical difficulty-related factors, which were perioperative factors that included the intraoperative process, were investigated.

RESULTS

Eight (11%) patients were allocated to high difficulty, whereas 67 patients (89%) were allocated to low difficulty. The intraoperative process, which was shown as the extension of each endoscopic phase, was significantly related to a technical difficulty. The area under the curve (AUC) values were higher at all the phase duration than at the clinical characteristics. Submucosal dissection phase (AUC 0.902; 95% confidence intervals (CI) 0.752-1.000), marking phase (AUC 0.827; 95% CI 0.703-0.951), and early phase which was defined as the duration from the start of marking to the end of submucosal injection (AUC 0.847; 95% CI 0.701-0.992) were significantly related to technical difficulty.

CONCLUSIONS

The intraoperative process, particularly early phase, was strongly associated with esophageal ESD technical difficulty. This study demonstrated the potential for automatic evaluation of esophageal ESD technical difficulty when combined with an AI-based automatic phase evaluation system.

Pituitary society expert Delphi consensus: operative workflow in endoscopic transsphenoidal pituitary adenoma resection

PURPOSE

Surgical workflow analysis seeks to systematically break down operations into hierarchal components. It facilitates education, training, and understanding of surgical variations. There are known educational demands and variations in surgical practice in endoscopic transsphenoidal approaches to pituitary adenomas. Through an iterative consensus process, we generated a surgical workflow reflective of contemporary surgical practice.

METHODS

A mixed-methods consensus process composed of a literature review and iterative Delphi surveys was carried out within the Pituitary Society. Each round of the survey was repeated until data saturation and > 90% consensus was reached.

RESULTS

There was a 100% response rate and no attrition across both Delphi rounds. Eighteen international expert panel members participated. An extensive workflow of 4 phases (nasal, sphenoid, sellar and closure) and 40 steps, with associated technical errors and adverse events, were agreed upon by 100% of panel members across rounds. Both core and case-specific or surgeon-specific variations in operative steps were captured.

CONCLUSIONS

Through an international expert panel consensus, a workflow for the performance of endoscopic transsphenoidal pituitary adenoma resection has been generated. This workflow captures a wide range of contemporary operative practice. The agreed "core" steps will serve as a foundation for education, training, assessment and technological development (e.g. models and simulators). The "optional" steps highlight areas of heterogeneity of practice that will benefit from further research (e.g. methods of skull base repair). Further adjustments could be made to increase applicability around the world.

Assurance of surgical quality within multicenter randomized controlled trials for bariatric and metabolic surgery: a systematic review

BACKGROUND

Surgical quality assurance methods aim to ensure standardization and high quality of surgical techniques within multicenter randomized controlled trials (RCTs), thereby diminishing the heterogeneity of surgery and reducing biases due to surgical variation. This study aimed to establish the measures undertaken to ensure surgical quality within multicenter RCTs investigating bariatric and metabolic surgery, and their influence upon clinical outcomes.

METHODS

An electronic literature search was performed from the Embase, Medline, and Web of Science databases to identify multicenter RCTs investigating bariatric and metabolic surgery. Each RCT was evaluated against a checklist of surgical quality measures within 3 domain: (1) standardization of surgical techniques; (2) credentialing of surgical experience; and (3) monitoring of performance. Outcome measures were postoperative weight change and complications.

RESULTS

Nineteen multicenter RCTs were included in the analysis. Three studies undertook pretrial education of surgical standard. Fourteen studies described complete standardization of surgical techniques. Four studies credentialed surgeons by case volume prior to enrollment. Two studies used intraoperative or video evaluation of surgical technique prior to enrollment. Only two studies monitored performance during the study. Although there were limited quality assurance methods undertaken, utilization of these techniques was associated with reduced overall complications. Standardization of surgery was associated with reduced re-operation rates but did not influence postoperative weight loss.

CONCLUSION

The utilization of methods for surgical quality assurance are very limited within multicenter RCTs of bariatric and metabolic surgery. Future studies must implement surgical quality assurance methods to reduce variability of surgical performance and potential bias within RCTs.

Surgical workflow recognition with 3DCNN for Sleeve Gastrectomy

PURPOSE

Surgical workflow recognition is a crucial and challenging problem when building a computer-assisted surgery system. Current techniques focus on utilizing a convolutional neural network and a recurrent neural network (CNN-RNN) to solve the surgical workflow recognition problem. In this paper, we attempt to use a deep 3DCNN to solve this problem.

METHODS

In order to tackle the surgical workflow recognition problem and the imbalanced data problem, we implement a 3DCNN workflow referred to as I3D-FL-PKF. We utilize focal loss (FL) to train a 3DCNN architecture known as Inflated 3D ConvNet (I3D) for surgical workflow recognition. We use prior knowledge filtering (PKF) to filter the recognition results.

RESULTS

We evaluate our proposed workflow on a large sleeve gastrectomy surgical video dataset. We show that focal loss can help to address the imbalanced data problem. We show that our PKF can be used to generate smoothed prediction results and improve the overall accuracy. We show that the proposed workflow achieves 84.16% frame-level accuracy and reaches a weighted Jaccard score of 0.7327 which outperforms traditional CNN-RNN design.

CONCLUSION

The proposed workflow can obtain consistent and smooth predictions not only within the surgical phases but also for phase transitions. By utilizing focal loss and prior knowledge filtering, our implementation of deep 3DCNN has great potential to solve surgical workflow recognition problems for clinical practice.

Deep learning-based automatic surgical step recognition in intraoperative videos for transanal total mesorectal excision

BACKGROUND

Dividing a surgical procedure into a sequence of identifiable and meaningful steps facilitates intraoperative video data acquisition and storage. These efforts are especially valuable for technically challenging procedures that require intraoperative video analysis, such as transanal total mesorectal excision (TaTME); however, manual video indexing is time-consuming. Thus, in this study, we constructed an annotated video dataset for TaTME with surgical step information and evaluated the performance of a deep learning model in recognizing the surgical steps in TaTME.

METHODS

This was a single-institutional retrospective feasibility study. All TaTME intraoperative videos were divided into frames. Each frame was manually annotated as one of the following major steps: (1) purse-string closure; (2) full thickness transection of the rectal wall; (3) down-to-up dissection; (4) dissection after rendezvous; and (5) purse-string suture for stapled anastomosis. Steps 3 and 4 were each further classified into four sub-steps, specifically, for dissection of the anterior, posterior, right, and left planes. A convolutional neural network-based deep learning model, Xception, was utilized for the surgical step classification task.

RESULTS

Our dataset containing 50 TaTME videos was randomly divided into two subsets for training and testing with 40 and 10 videos, respectively. The overall accuracy obtained for all classification steps was 93.2%. By contrast, when sub-step classification was included in the performance analysis, a mean accuracy (± standard deviation) of 78% (± 5%), with a maximum accuracy of 85%, was obtained.

CONCLUSIONS

To the best of our knowledge, this is the first study based on automatic surgical step classification for TaTME. Our deep learning model self-learned and recognized the classification steps in TaTME videos with high accuracy after training. Thus, our model can be applied to a system for intraoperative guidance or for postoperative video indexing and analysis in TaTME procedures.

Accuracy and usefulness in assessing proficiency of the observational clinical human reliability assessment checklist of the open inguinal hernia repair procedure: A cross-sectional study

BACKGROUND

The Observational Clinical Human Reliability Assessment (OCHRA) can be used to score errors during surgical procedures. To construct an OCHRA-checklist, steps, substeps, and hazards of a surgical procedure need to be defined. A step-by-step framework was developed to segment surgical procedures into steps, substeps, and hazards. The first aim of this study was to investigate if the step-by-step framework could be used to construct an accurate Lichtenstein open inguinal hernia repair (LOIHR) stepwise description. The second aim was to investigate if the OCHRA-checklist based on this stepwise description was accurate and useful for surgical training and assessment.

MATERIALS AND METHODS

Ten expert surgeons rated statements regarding the accuracy of the LOIHR stepwise description, the accuracy, and the usefulness of the LOIHR OCHRA-checklist (eight, seven, and six statements, respectively) using a 5-point Likert scale. One-sample Wilcoxon signed-rank test was used to compare the outcomes to the neutral value of 3.

RESULTS

The accuracy of the stepwise description and the accuracy and usefulness of the OCHRA-checklist were rated statistically significantly higher than the neutral value of 3 (median 4.75 [5.00-4.00] with p = .009, median 5.00 [5.00-4.00] with p = .012, median 4.00 [5.00-4.00] with p = .047, respectively). The experts rated the OCHRA-checklist to be useful for the training (5.00 [5.00-4.00], p = .009), and assessment (4.50 [5.00-4.00], p = .010) of surgical residents.

CONCLUSION

This preliminary study showed that the stepwise LOIHR description constructed using the step-by-step framework was found to be accurate. The LOIHR OCHRA-checklist developed using the stepwise description was also accurate, and particularly useful for the training and assessment of proficiency of surgical residents.

Evaluation of Online Videos of Laparoscopic Sleeve Gastrectomy Using the LAP-VEGaS Guidelines

BACKGROUND

Laparoscopic sleeve gastrectomy (LSG) is the most common bariatric surgical procedure worldwide. Educational videos of LSGs are available from online sources with YouTube® being the most popular online video repository. However, due to the unrestricted and uncontrolled nature of YouTube®, anyone can upload videos without peer review or standardization. The LAP-VEGaS guidelines were formed to guide the production of high-quality surgical videos. The aim of this study is to use the LAP-VEGaS guidelines to determine if videos of LSGs available on Youtube® are of an acceptable standard for surgical educational purposes.

METHODS

A YouTube® search was performed using the term laparoscopic sleeve gastrectomy. Appropriate videos were analysed by two individuals using the sixteen LAP-VEGaS guidelines.

RESULTS

A total of 575 videos were found, of which 202 videos were included and analysed using the LAP-VEGaS guidelines. The median video guideline score was 6/16 with 89% of videos meeting less than half of all guidelines. There was no correlation between the LAP-VEGaS score and view count.

CONCLUSIONS

There is an abundance of laparoscopic sleeve gastrectomy educational videos available on YouTube®; however, when analysed using the LAP-VEGaS guidelines, the majority do not meet acceptable educational standards for surgical training purposes.

Objective assessment of surgical operative performance by observational clinical human reliability analysis (OCHRA): a systematic review

BACKGROUND

Both morbidity and mortality data (MMD) and learning curves (LCs) do not provide information on the nature of intraoperative errors and their mechanisms when these adversely impact on patient outcome. OCHRA was developed specifically to address the unmet surgical need for an objective assessment technique of the quality of technical execution of operations at individual operator level. The aim of this systematic review was to review of OCHRA as a method of objective assessment of surgical operative performance.

METHODS

Systematic review based on searching 4 databases for articles published from January 1998 to January 2019. The review complies with Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and includes original publications on surgical task performance based on technical errors during operations across several surgical specialties.

RESULTS

Only 26 published studies met the search criteria, indicating that the uptake of OCHRA during the study period has been low. In 31% of reported studies, the operations were performed by fully qualified consultant/attending surgeons and by surgical trainees in 69% in approved training programs. OCHRA identified 7869 consequential errors (CE) during the conduct of 719 clinical operations (mean = 11 CEs). It also identified 'hazard zones' of operations and proficiency-gain curves (P-GCs) that confirm attainment of persistent competent execution of specific operations by individual trainee surgeons. P-GCs are both surgeon and operation specific.

CONCLUSIONS

Increased OCHRA use has the potential to improve patient outcome after surgery, but this is a contingent progress towards automatic assessment of unedited videos of operations. The low uptake of OCHRA is attributed to its labor-intensive nature involving human factors (cognitive engineering) expertise. Aside from faster and more objective peer-based assessment, this development should accelerate increased clinical uptake and use of the technique in both routine surgical practice and surgical training.

Technical review: Vertical sleeve gastrectomy in adolescents

Sleeve gastrectomy is an effective tool for inducing sustainable weight loss in adolescents with obesity. It is a seemingly straight-forward procedure, and yet deceptive in technical nuances. This review highlights the technical preparation (equipment, patient positioning, pre-operative management), and conduct (anatomy, instruments, methodology, pitfalls) of the operation, and concludes with essentials for anticipating and managing complications of the operation. Throughout the discussion, we emphasize practical techniques to maintain patient safety while achieving maximum weight loss benefits.

Application of the Structure Function in the Evaluation of the Human Factor in Healthcare

A structure function is one of the possible mathematical models of systems in reliability engineering. A structure function maps sets of component states into system performance levels. Methods of system reliability evaluation based on structure function representation are well established. A structure function can be formed based on completely specified data about system behavior. Such data for most real-world systems are incomplete and uncertain. The typical example is analysis and evaluation of the human factor. Therefore, the structure function is not used in human reliability analysis (HRA) typically. In this paper, a method for structure function construction is proposed based on incomplete and uncertain data in HRA. The proposed method application is considered for healthcare to evaluate medical error. This method is developed using a fuzzy decision tree (FDT), which allows all possible component states to be classified into classes of system performance levels. The structure function is constructed based on the decision table, which is formed according to the FDT. A case study for this method is considered by evaluating the human factor in healthcare: complications in the familiarization and exploitation of a new device in a hospital department are analyzed and evaluated. This evaluation shows the decreasing of medical errors in diagnosis after one year of device exploitation and a slight decrease in quality of diagnosis after two months of device exploitation. Numerical values of probabilities of medical error are calculated based on the proposed approach.

3D laparoscopy does not reduce operative duration or errors in day-case laparoscopic cholecystectomy: a randomised controlled trial

Background

Contemporary 3D platforms have overcome past deficiencies. Available trainee and laboratory studies suggest stereoscopic imaging improves performance but there is little clinical data or studies assessing specialists. We aimed to determine whether stereoscopic (3D) laparoscopic systems reduce operative time and number of intraoperative errors during specialist-performed laparoscopic cholecystectomy (LC).

Methods

A parallel arm (1:1) randomised controlled trial comparing 2D and 3D passive-polarised laparoscopic systems in day-case LC using was performed. Eleven consultant surgeons that had each performed > 200 LC (including > 10 3D LC) participated. Cases were video recorded and a four-point difficulty grade applied. The primary outcome was overall operative time. Subtask time and the number of intraoperative consequential errors as identified by two blinded assessors using a hierarchical task analysis and the observational clinical human reliability analysis technique formed secondary endpoints.

Results

112 patients were randomised. There was no difference in operative time between 2D and 3D LC (23:14 min (± 10:52) vs. 20:17 (± 9:10), absolute difference − 14.6%, p = 0.148) although 3D surgery was significantly quicker in difficulty grade 3 and 4 cases (30:23 min (± 9:24), vs. 18:02 (± 7:56), p < 0.001). No differences in overall error count was seen (total 47, median 1, range 0–4 vs. 45, 1, 0–3, p = 0.62) although there were significantly fewer 3D gallbladder perforations (15 vs. 6, p = 0.034).

Conclusion

3D laparoscopy did not reduce overall operative time or error frequency in laparoscopic cholecystectomies performed by specialist surgeons. 3D reduced Calot’s dissection time and operative time in complex cases as well as the incidence of iatrogenic gallbladder perforation (NCT01930344).

Electronic supplementary material

The online version of this article (10.1007/s00464-019-06961-1) contains supplementary material, which is available to authorized users.

Comparison of laparoscopic sleeve gastrectomy leak rates in five staple-line reinforcement options: a systematic review

Background

Staple-line leaks following laparoscopic sleeve gastrectomy (LSG) remain a concerning complication. Staple-line buttressing is largely adopted as an acceptable reinforcement but data regarding leaks have been equivocal. This study compared staple-line leaks in five reinforcement options during LSG: no reinforcement (NO-SLR), oversewing (suture), nonabsorbable bovine pericardial strips (BPS), tissue sealant or fibrin glue (Seal), or absorbable polymer membrane (APM).

Methods

This systematic review study of articles published between 2012 and 2016 regarding LSG leak rates aligned with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Variables of interest included leak rates, bleeding, and complications in addition to surgical and population parameters. An independent Fisher’s exact test was used to compare the number of patients with and without leaks for the different reinforcement options.

Results

Of the 1633 articles identified, 148 met inclusion criteria and represented 40,653 patients. Differences in age (older in APM; p = 0.001), starting body mass index (lower in Suture; p = 0.008), and distance from pylorus (closer in BPS; p = 0.04) were observed between groups, but mean bougie size was equivalent. The overall leak rate of 1.5% (607 leaks) ranged from 0.7% for APM (significantly lower than all groups; p ≤ 0.007 for next lowest leak rate) to 2.7% (BPS).

Conclusions

This systematic review of staple-line leaks following LSG demonstrated a significantly lower rate using APM staple-line reinforcement as compared to oversewing, use of sealants, BPS reinforcement, or no reinforcement. Variation in surgical technique may also contribute to leak rates.

Electronic supplementary material

The online version of this article (10.1007/s00464-019-06782-2) contains supplementary material, which is available to authorized users.

A Delphi Consensus of the Crucial Steps in Gastric Bypass and Sleeve Gastrectomy Procedures in the Netherlands

PURPOSE

Bariatric procedures are technically complex and skill demanding. In order to standardize the procedures for research and training, a Delphi analysis was performed to reach consensus on the practice of the laparoscopic gastric bypass and sleeve gastrectomy in the Netherlands.

METHODS

After a pre-round identifying all possible steps from literature and expert opinion within our study group, questionnaires were send to 68 registered Dutch bariatric surgeons, with 73 steps for bypass surgery and 51 steps for sleeve gastrectomy. Statistical analysis was performed to identify steps with and without consensus. This process was repeated to reach consensus of all necessary steps.

RESULTS

Thirty-eight participants (56%) responded in the first round and 32 participants (47%) in the second round. After the first Delphi round, 19 steps for gastric bypass (26%) and 14 for sleeve gastrectomy (27%) gained full consensus. After the second round, an additional amount of 10 and 12 sub-steps was confirmed as key steps, respectively. Thirteen steps in the gastric bypass and seven in the gastric sleeve were deemed advisable. Our expert panel showed a high level of consensus expressed in a Cronbach's alpha of 0.82 for the gastric bypass and 0.87 for the sleeve gastrectomy.

CONCLUSIONS

The Delphi consensus defined 29 steps for gastric bypass and 26 for sleeve gastrectomy as being crucial for correct performance of these procedures to the standards of our expert panel. These results offer a clear framework for the technical execution of these procedures.

EAES classification of intraoperative adverse events in laparoscopic surgery

BACKGROUND

Surgical outcomes are traditionally evaluated by post-operative data such as histopathology and morbidity. Although these outcomes are reported using accepted systems, their ability to influence operative performance is limited by their retrospective application. Interest in direct measurement of intraoperative events is growing but no available systems applicable to routine practice exist. We aimed to develop a structured, practical method to report intraoperative adverse events enacted during minimal access surgical procedures.

METHODS

A structured mixed methodology approach was adopted. Current intraoperative adverse event reporting practices and desirable system characteristics were sought through a survey of the EAES executive. The observational clinical human reliability analysis method was applied to a series of laparoscopic total mesorectal excision (TME) case videos to identify intraoperative adverse events. In keeping with survey results, observed events were further categorised into non-consequential and consequential, which were further subdivided into four levels based upon the principle of therapy required to correct the event. A second survey phase explored usability, acceptability, face and content validity of the novel classification.

RESULTS

217 h of TME surgery were analysed to develop and continually refine the five-point hierarchical structure. 34 EAES expert surgeons (69%) responded. The lack of an accepted system was the main barrier to routine reporting. Simplicity, reproducibility and clinical utility were identified as essential requirements. The observed distribution of intraoperative adverse events was 60.1% grade I (non-consequential), 37.1% grade II (minor corrective action), 2.4% grade III (major correction or change in post-operative care) and 0.1% grade IV (life threatening). 84% agreed with the proposed classification (Likert scale 4.04) and 92% felt it was applicable to their practice and incorporated all desirable characteristics.

CONCLUSION

A clinically applicable intraoperative adverse event classification, which is acceptable to expert surgeons, is reported and complements the objective assessment of minimal access surgical performance.