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Background: Digital technologies (such as smartphone applications, activity trackers, and e-learning platforms) have supported patients with long-term conditions to change their lifestyle health behaviours. The aim of this study was to examine the effectiveness of digital technologies in supporting patients undergoing elective surgery to change their health behaviours. Methods: A systematic review was conducted of articles reporting a digital intervention supporting behaviour change in adult patients who underwent elective bariatric, oncological or orthopaedic surgery. MEDLINE, Embase, CINAHL, PsycINFO, Web of Science, and Scopus were searched from inception to March 2019 for quantitative intervention studies with a specific focus on physical activity, dietary intake, and weight loss in patients before and after surgery (PROSPERO: CRD42019127972). The Joanna Briggs Institute critical appraisal checklist was used to assess study quality. Results: Of 3021 citations screened, 17 studies were included comprising 4923 surgical patients; these included experimental (pre-post design, feasibility studies, and RCTs) and observational studies. Three factors were identified as effective for supporting health behaviour change in elective surgical populations: digital technology delivery, implementation, and theoretical underpinning. Six of eight studies that referred to behaviour change theories observed significant improvements in health behaviour relating to reduced weight regain, and improved lifestyle choices for physical activity and diet. Meta-analysis was not possible because of heterogeneous outcome measures. Conclusion: Digital technologies may effectively support behavioural change in patients undergoing elective surgery. [ABSTRACT FROM AUTHOR]

Background: Surgical incidents can have significant effects on both patients and health professionals, including emotional distress and depression. The aim of this study was to explore the personal and professional impacts of surgical incidents on operating theatre staff. Methods: Face-to-face semistructured interviews were conducted with a range of different healthcare professionals working in operating theatres, including surgeons and anaesthetists, operating department practitioners, and theatre nurses, and across different surgical specialties at five different hospitals. All interviews were audio recorded, transcribed verbatim, and analysed using an inductive thematic approach, which involved reading and re-reading the transcripts, assigning preliminary codes, and searching for patterns and themes within the codes, with the aid of NVivo 12 software. These emerging themes were discussed with the wider research team to gain their input. Results: Some 45 interviews were conducted, generally lasting between 30 and 75 min. Three overarching themes emerged: personal and professional impact; impact of the investigation process; and positive consequences or impact. Participants recalled experiencing negative emotions following surgical incidents that depended on the severity of the incident, patient outcomes, and the support that staff received. A culture of blame, inadequate support, and lack of a clear and transparent investigative process appeared to worsen impact. Conclusion: The study indicated that more support is needed for operating theatre staff involved in surgical incidents. Greater transparency and better information during the investigation of such incidents for staff are still needed. [ABSTRACT FROM AUTHOR]

Objective: A high-reliability organization (HRO) is an organization that has sustained almost error-free performance, despite operating in hazardous conditions where the consequences of errors could be catastrophic. A number of tools and initiatives have been used within HROs to learn from safety incidents, some of which have the potential to be adapted and used in healthcare. We conducted a systematic review to identify any learning tools deemed to be effective that could be adapted and used by multidisciplinary teams in healthcare following a patient safety incident.Methods: This review followed the Preferred Reporting Items for Systematic Reviews and MetaAnalyses for Protocols reporting guidelines and was registered with the PROSPERO (CRD42017071528). A search of databases was carried out in January 2021, from the date of their commencement. We conducted a search on electronic databases such as Web of Science, Science Direct, MEDLINE in Process Jan 1950-present, EMBASE Jan 1974-present, CINAHL 1982-present, PsycINFO 1967-present, Scopus and Google Scholar. We also searched the grey literature including reports from government agencies, relevant doctoral dissertations and conference proceedings. A customized data extraction form was used to capture pertinent information from included studies and Critical Appraisal Skills Programme tool to appraise on their quality.Results: A total of 5921 articles were identified, with 964 duplicate articles removed and 4932 excluded at the title (4055), abstract (510) and full-text (367) stages. Twenty-five articles were included in the review. Learning tools identified included debriefing, simulation, crew resource management and reporting systems to disseminate safety messages. Debriefing involved deconstructing incidents using reflective questions, whilst simulation training involved asking staff to relive the event again by performing the task(s) in a role-play scenario. Crew resource management is a set of training procedures that focus on communication, leadership and decision-making. Sophisticated incident-reporting systems provide valuable information on hazards and were widely recommended as a way of disseminating key safety messages following safety incidents. These learning tools were found to have a positive impact on learning if conducted soon after the incident with efficient facilitation.Conclusion: Healthcare organizations should find ways to adapt to the learning tools or initiatives used in HROs following safety incidents. It is challenging to recommend any specific one as all learning tools have shown considerable promise. However, the way these tools or initiatives are implemented is critical, and so further work is needed to explore how to successfully embed them into healthcare organizations so that everyone at every level of the organization embraces them. [ABSTRACT FROM AUTHOR]

Introduction: Antimicrobial resistance was listed among the top ten global health issues by the World Health Organization in 2019.1 By 2050, it is projected to have caused 10 million deaths, surpassing cancer, diabetes, and road traffic accidents.2 The rise in resistant bacterial strains and reduced availability of novel antibiotics makes tackling antimicrobial resistance even more challenging. Preventing infections is the most effective approach, and Artificial Intelligence (AI) has the potential to help predict the likelihood of a patient experiencing a post-operative infection.3 This can help clinicians identify those who might be at higher risk and implement clinical interventions to potentially reduce this risk, during the pre-operative stage. Aim: To develop and internally validate an AI-predictive model for predicting the likelihood of post-operative infection in surgical patients. Methods: A secondary care dataset from the Pioneer Research Hub was used to develop the predictive model, which included a range of data such as demographic information, vital signs, microbiological culture results, lab investigations, comorbidities, surgical details, and infection diagnoses. Machine learning techniques and clinician input were used to select predictors, both modifiable (e.g. blood glucose) and non-modifiable (e.g. age). Recursive feature elimination with cross-validation was performed, and the dataset was split into training (80%) and internal validation (20%) sets. Missing data was managed through complete case analysis and multiple imputation. Various supervised machine learning classifier algorithms were trained, and an ensemble model was created. Ethical approval was obtained (20/EM/0183, IRAS 280077). Results: Data on 2,716 patients who underwent elective abdominal surgery were included in the model training and validation. The infection incidence in this cohort was 38%. Out of 74 initial predictors, 19 were selected. These predictors included demographic data (gender), comorbidities (diabetes, COPD, cardiac conditions, obesity, anaemia), microbiology data (positive cultures within 90 days before surgery, multi-drug resistance), and laboratory investigations within 90 days before surgery: WBCs, lymphocytes, blood glucose, platelets, haematocrit, mean cell haemoglobin, haemoglobin, total bilirubin, aspartate aminotransferase, alanine transaminase, and C-reactive protein. The gradient boosting classifier performed the best among the supervised machine learning algorithms. The ensemble model showed high performance in training (sensitivity: 85.3%, specificity: 74.6%, AUROC: 88.6%) and internal validation (sensitivity: 96.9%, specificity: 74.1%, AUROC: 85.5%). The PROBAST checklist was used to address bias before predictor selection. Discussion/Conclusion: The developed AI-predictive model has the potential to predict the likelihood of an elective abdominal surgery patient experiencing a post-operative infection. Identifying patients at high risk of post-surgical infections can guide clinical decision making and help implement interventions during the pre-operative stage, (i.e. as part of nutritional prehabilitation screening), to reduce infection risk. However, it is important to acknowledge the limitations of this model. One limitation is the presence of missing data in the training dataset, which may introduce biases and affect the accuracy of the model. Additionally, potential inaccuracies in data entry could impact the reliability of the model's predictions. Furthermore, it is crucial to consider any historical biases that might have influenced data collection, as these biases could have adverse effects on the developed model. References: 1. Antimicrobial resistance fact sheets. https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance [Accessed on 20th May 2023] 2. Kumar M, Silori R, Mazumder P, Shrivastava V, Loge F, Barceló D, Mahlknecht J. Wars and Pandemics: AMR Accelerators of the 21st Century?. Environ. Sci. Technol. Lett. 2023 Mar 26;10(4):289-91. 3. Hassan N, Slight R, Weiand D, Vellinga A, Morgan G, Aboushareb F, Slight SP. Preventing sepsis; how can artificial intelligence inform the clinical decision-making process? A systematic review. IJMI. 2021 Apr 10:104457. [ABSTRACT FROM AUTHOR]

The World Health Organisation advocates Digital Health Technologies (DHTs) for advancing population health, yet concerns about inequitable outcomes persist. Differences in access and use of DHTs across different demographic groups can contribute to inequities. Academics and policy makers have acknowledged this issue and called for inclusive digital health strategies. This systematic review synthesizes literature on these strategies and assesses facilitators and barriers to their implementation. We searched four large databases for qualitative studies using terms relevant to digital technology, health inequities, and socio-demographic factors associated with digital exclusion summarised by the CLEARS framework (Culture, Limiting conditions, Education, Age, Residence, Socioeconomic status). Following the PRISMA guidelines, 10,401 articles were screened independently by two reviewers, with ten articles meeting our inclusion criteria. Strategies were grouped into either outreach programmes or co-design approaches. Narrative synthesis of these strategies highlighted three key themes: firstly, using user-friendly designs, which included software and website interfaces that were easy to navigate and compatible with existing devices, culturally appropriate content, and engaging features. Secondly, providing supportive infrastructure to users, which included devices, free connectivity, and non-digital options to help access healthcare. Thirdly, providing educational support from family, friends, or professionals to help individuals develop their digital literacy skills to support the use of DHTs. Recommendations for advancing digital health equity include adopting a collaborative working approach to meet users' needs, and using effective advertising to raise awareness of the available support. Further research is needed to assess the feasibility and impact of these recommendations in practice., (© 2024. The Author(s).)

Background: Predictive models have been used in clinical care for decades. They can determine the risk of a patient developing a particular condition or complication and inform the shared decision-making process. Developing artificial intelligence (AI) predictive models for use in clinical practice is challenging; even if they have good predictive performance, this does not guarantee that they will be used or enhance decision-making. We describe nine stages of developing and evaluating a predictive AI model, recognising the challenges that clinicians might face at each stage and providing practical tips to help manage them., Findings: The nine stages included clarifying the clinical question or outcome(s) of interest (output), identifying appropriate predictors (features selection), choosing relevant datasets, developing the AI predictive model, validating and testing the developed model, presenting and interpreting the model prediction(s), licensing and maintaining the AI predictive model and evaluating the impact of the AI predictive model. The introduction of an AI prediction model into clinical practice usually consists of multiple interacting components, including the accuracy of the model predictions, physician and patient understanding and use of these probabilities, expected effectiveness of subsequent actions or interventions and adherence to these. Much of the difference in whether benefits are realised relates to whether the predictions are given to clinicians in a timely way that enables them to take an appropriate action., Conclusion: The downstream effects on processes and outcomes of AI prediction models vary widely, and it is essential to evaluate the use in clinical practice using an appropriate study design., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: A patient's capability, motivation, and opportunity to change their lifestyle are determinants of successful outcomes following bariatric surgery. Lifestyle changes before and after surgery, including improved dietary intake and physical activity levels, have been associated with greater postsurgical weight loss and improved long-term health. Integrating patient-centered digital technologies within the bariatric surgical pathway could form part of an innovative strategy to promote and sustain healthier behaviors, and provide holistic patient support, to improve surgical success. Previous research focused on implementing digital technologies and measuring effectiveness in surgical cohorts. However, there is limited work concerning the desires, suggestions, and reflections of patients undergoing bariatric surgery. This qualitative investigation explores patients' perspectives on technology features that would support behavior changes during the pre- and postoperative periods, to potentially maintain long-term healthy lifestyles following surgery., Objective: This study aims to understand how digital technologies can be used to support patient care during the perioperative journey to improve weight loss outcomes and surgical success, focusing on what patients want from digital technologies, how they want to use them, and when they would be of most benefit during their surgical journey., Methods: Patients attending bariatric surgery clinics in one hospital in the North of England were invited to participate. Semistructured interviews were conducted with purposively sampled pre- and postoperative patients to discuss lifestyle changes and the use of digital technologies to complement their care. The interviews were audio recorded and transcribed verbatim. Reflexive thematic analysis enabled the development of themes from the data. Ethical approval was obtained from the National Health Service Health Research Authority., Results: A total of 20 patients were interviewed (preoperative phase: 40% (8/20); postoperative phase: 60% (12/20). A total of 4 overarching themes were developed and related to the optimization of technology functionality. These centered on providing tailored content and support; facilitating self-monitoring and goal setting; delivering information in an accessible, trusted, and usable manner; and meeting patient information-seeking and engagement needs during the surgical pathway. Functionalities that delivered personalized feedback and postoperative follow-up were considered beneficial. Individualized goal setting functionality could support a generation of digitally engaged patients with bariatric conditions as working toward achievable targets was deemed an effective strategy for motivating behavior change. The creation of digital package of care checklists between patients and clinicians was a novel finding from this study., Conclusions: Perceptions of patients undergoing bariatric surgery validated the integration of digital technologies within the surgical pathway, offering enhanced connectedness and support. Recommendations are made relating to the design, content, and functionality of digital interventions to best address the needs of this cohort. These findings have the potential to influence the co-design and integration of person-centered, perioperative technologies., (©Anna Robinson, Andrew Husband, Robert Slight, Sarah P Slight. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 04.03.2022.)

Background and Objectives: Sepsis is a life-threatening condition that is associated with increased mortality. Artificial intelligence tools can inform clinical decision making by flagging patients at risk of developing infection and subsequent sepsis. This systematic review aims to identify the optimal set of predictors used to train machine learning algorithms to predict the likelihood of an infection and subsequent sepsis., Methods: This systematic review was registered in PROSPERO database (CRD42020158685). We conducted a systematic literature review across 3 large databases: Medline, Cumulative Index of Nursing and Allied Health Literature, and Embase. Quantitative primary research studies that focused on sepsis prediction associated with bacterial infection in adults in all care settings were eligible for inclusion., Results: Seventeen articles met our inclusion criteria. We identified 194 predictors that were used to train machine learning algorithms, with 13 predictors used on average across all included studies. The most prevalent predictors included age, gender, smoking, alcohol intake, heart rate, blood pressure, lactate level, cardiovascular disease, endocrine disease, cancer, chronic kidney disease (eGFR<60 mL/min), white blood cell count, liver dysfunction, surgical approach (open or minimally invasive), and pre-operative haematocrit < 30 %. All included studies used artificial intelligence techniques, with average sensitivity 75.7 ± 17.88, and average specificity 63.08 ± 22.01., Conclusion: The type of predictors influenced the predictive power and predictive timeframe of the developed machine learning algorithm. Predicting the likelihood of sepsis through artificial intelligence can help concentrate finite resources to those patients who are most at risk. Future studies should focus on developing more sensitive and specific algorithms., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Digital technology has influenced many aspects of modern living, including health care. In the context of elective surgeries, there is a strong association between preoperative physical and psychological preparedness, and improved postoperative outcomes. Health behavior changes made in the pre- and postoperative periods can be fundamental in determining the outcomes and success of elective surgeries. Understanding the potential unmet needs of patients undergoing elective surgery is central to motivating health behavior change. Integrating digital and mobile health technologies within the elective surgical pathway could be a strategy to remotely deliver this support to patients., Objective: This meta-ethnographic systematic review explores digital interventions supporting patients undergoing elective surgery with health behavior changes, specifically physical activity, weight loss, dietary intake, and psychological support., Methods: A literature search was conducted in October 2019 across 6 electronic databases (International Prospective Register of Systematic Reviews [PROSPERO]: CRD42020157813). Qualitative studies were included if they evaluated the use of digital technologies supporting behavior change in adult patients undergoing elective surgery during the pre- or postoperative period. Study quality was assessed using the Critical Appraisal Skills Programme tool. A meta-ethnographic approach was used to synthesize existing qualitative data, using the 7 phases of meta-ethnography by Noblit and Hare. Using this approach, along with reciprocal translation, enabled the development of 4 themes from the data., Results: A total of 18 studies were included covering bariatric (n=2, 11%), cancer (n=13, 72%), and orthopedic (n=3, 17%) surgeries. The 4 overarching themes appear to be key in understanding and determining the effectiveness of digital and mobile interventions to support surgical patients. To successfully motivate health behavior change, technologies should provide motivation and support, enable patient engagement, facilitate peer networking, and meet individualized patient needs. Self-regulatory features such as goal setting heightened patient motivation. The personalization of difficulty levels in virtual reality-based rehabilitation was positively received. Internet-based cognitive behavioral therapy reduced depression and distress in patients undergoing cancer surgery. Peer networking provided emotional support beyond that of patient-provider relationships, improving quality of life and care satisfaction. Patients expressed the desire for digital interventions to be individually tailored according to their physical and psychological needs, before and after surgery., Conclusions: These findings have the potential to influence the future design of patient-centered digital and mobile health technologies and demonstrate a multipurpose role for digital technologies in the elective surgical pathway by motivating health behavior change and offering psychological support. Through the synthesis of patient suggestions, we highlight areas for digital technology optimization and emphasize the importance of content tailored to suit individual patients and surgical procedures. There is a significant rationale for involving patients in the cocreation of digital health technologies to enhance engagement, better support behavior change, and improve surgical outcomes., (©Anna Robinson, Umay Oksuz, Robert Slight, Sarah Slight, Andrew Husband. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 01.12.2020.)

Objectives: A systematic review was undertaken to understand the nature of the relationship between the UK National Health Service (NHS) labour force and satisfaction, retention and wages., Design: Narrative systematic review., Data Sources: The literature was searched using seven databases in January 2020: MEDLINE (1996-present), the Cumulative Index to Nursing and Allied Health Literature (CINAHL via EBSCO) (1984-present), Embase (1996-present), PsycINFO (1987-present), ProQuest (1996-present), Scopus (all years) and Cochrane library (all years). We used medical subject headings and key words relating to 'retention', 'satisfaction' and 'wages'., Eligibility Criteria for Selecting Studies: Primary research studies or reviews that focused on the following relationships within the NHS workforce: wages and job satisfaction, job satisfaction and retention or wages and retention., Data Extraction and Synthesis: Two independent reviewers screened all titles, abstracts and full texts, with arbitration by a third reviewer., Results: 27 803 articles were identified and after removing duplicates (n=17 156), articles were removed at the title (n=10 421), abstract (n=150) and full-text (n=45) stages. A total of 31 full-text articles were included. They identified three broad themes, low job satisfaction impacting negatively on job retention, poor pay impacting negatively on staff satisfaction and the limitations of increasing pay as a means of improving staff retention. Several factors affected these relationships, including the environment, discrimination, flexibility, autonomy, training and staffing levels., Conclusions: This review highlighted how multiple factors influence NHS labour force retention. Pay was found to influence satisfaction, which in turn affected retention. An increase in wages alone is unlikely to be sufficient to ameliorate the concerns of NHS workers. More research is needed to identify the role of autonomy on retention. A system leadership approach underpinned by data is required to implement bespoke job satisfaction improvement strategies to improve retention and achieve the goals of the NHS Long Term Plan., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Evidence strongly supports improved outcomes following surgery when patients are more physically active, have better dietary intake, or are generally fitter prior to surgery. Having an operation is a major life event for patients, and many are not educated around what they can do as individuals to aid a speedier and more successful recovery following their operation. What if there was a time point before surgery where clinicians could inspire patients to adjust their lifestyles for the better, in order to see fewer complications after surgery? This is where the concept of teachable moments comes into play. This commentary explores the concept of teachable moments and their value in surgical patient care and discusses the potentially under-utilized opportunities on hand to the surgical multidisciplinary team to remotely support patients using digital health technologies., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s). 2020.)

Purpose: To study the relationship between primary open-angle glaucoma (POAG) in a cohort of patients of African descent (AD) and serum vitamin D levels., Methods: A subset of the AD and glaucoma evaluation study III (ADAGES III) cohort, consisting of 357 patients with a diagnosis of POAG and 178 normal controls of self-reported AD, were included in this analysis. Demographic information, family history, and blood samples were collected from all the participants. All the subjects underwent clinical evaluation, including visual field (VF) mean deviation (MD), central cornea thickness (CCT), intraocular pressure (IOP), and height and weight measurements. POAG patients were classified into early and advanced phenotypes based on the severity of their visual field damage, and they were matched for age, gender, and history of hypertension and diabetes. Serum 25-Hydroxy (25-OH) vitamin D levels were measured by enzyme-linked immunosorbent assay (ELISA). The association of serum vitamin D levels with the development and severity of POAG was tested by analysis of variance (ANOVA) and the paired t -test., Results: The 178 early POAG subjects had a visual field MD of better than -4.0 dB, and the 179 advanced glaucoma subjects had a visual field MD of worse than -10 dB. The mean (95% confidence interval [CI]) levels of vitamin D of the subjects in the control (8.02 ± 6.19 pg/ml) and early phenotype (7.56 ± 5.74 pg/ml) groups were significantly or marginally significantly different from the levels observed in subjects with the advanced phenotype (6.35 ± 4.76 pg/ml; p = 0.0117 and 0.0543, respectively). In contrast, the mean serum vitamin D level in controls was not significantly different from that of the subjects with the early glaucoma phenotype (p = 0.8508)., Conclusions: In this AD cohort, patients with advanced glaucoma had lower serum levels of vitamin D compared with early glaucoma and normal subjects.

Purpose: To describe the study protocol and baseline characteristics of the African Descent and Glaucoma Evaluation Study (ADAGES) III., Design: Cross-sectional, case-control study., Participants: Three thousand two hundred sixty-six glaucoma patients and control participants without glaucoma of African or European descent were recruited from 5 study centers in different regions of the United States., Methods: Individuals of African descent (AD) and European descent (ED) with primary open-angle glaucoma (POAG) and control participants completed a detailed demographic and medical history interview. Standardized height, weight, and blood pressure measurements were obtained. Saliva and blood samples to provide serum, plasma, DNA, and RNA were collected for standardized processing. Visual fields, stereoscopic disc photographs, and details of the ophthalmic examination were obtained and transferred to the University of California, San Diego, Data Coordinating Center for standardized processing and quality review., Main Outcome Measures: Participant gender, age, race, body mass index, blood pressure, history of smoking and alcohol use in POAG patients and control participants were described. Ophthalmic measures included intraocular pressure, visual field mean deviation, central corneal thickness, glaucoma medication use, or past glaucoma surgery. Ocular conditions, including diabetic retinopathy, age-related macular degeneration, and past cataract surgery, were recorded., Results: The 3266 ADAGES III study participants in this report include 2146 AD POAG patients, 695 ED POAG patients, 198 AD control participants, and 227 ED control participants. The AD POAG patients and control participants were significantly younger (both, 67.4 years) than ED POAG patients and control participants (73.4 and 70.2 years, respectively). After adjusting for age, AD POAG patients had different phenotypic characteristics compared with ED POAG patients, including higher intraocular pressure, worse visual acuity and visual field mean deviation, and thinner corneas (all P < 0.001). Family history of glaucoma did not differ between AD and ED POAG patients., Conclusions: With its large sample size, extensive specimen collection, and deep phenotyping of AD and ED glaucoma patients and control participants from different regions in the United States, the ADAGES III genomics study will address gaps in our knowledge of the genetics of POAG in this high-risk population., (Copyright © 2017 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Background: Adverse surgical incidents affect both patients and health professionals. This study sought to explore the effect of surgical incidents on operating theatre staff and their subsequent behaviours., Methods: Eligible studies were primary research or reviews that focused on the effect of incidents on operating theatre staff in primary, secondary or tertiary care settings. MEDLINE, Embase, CINALH and PsycINFO were searched. A data extraction form was used to capture pertinent information from included studies and the Critical Appraisal Skills Programme (CASP) tool to appraise their quality. PRISMA-P reporting guidelines were followed and the review is registered with PROSPERO., Results: A total of 3918 articles were identified, with 667 duplicates removed and 3230 excluded at the title, abstract and full-text stages. Of 21 included articles, eight focused on the impact of surgical incidents on surgeons and anaesthetists. Only two involved theatre nurses and theatre technicians. Five key themes emerged: the emotional impact on health professionals, organization culture and support, individual coping strategies, learning from surgical complications and recommended changes to practice., Conclusion: Health professionals suffered emotional distress and often changed their behaviour following a surgical incident. Both organizations and individual clinicians can do a great deal to support staff in the aftermath of serious incidents.

Blunt traumatic aortic transection (TAT) is an uncommon injury in clinical practice that is associated with a high morbidity and mortality. The approach to patients with such an injury is controversial with specific regard to the most effective diagnostic tools, timing of surgical intervention and mechanisms of spinal cord protection. Chest X-ray with widening of the mediastinum is unreliable as a diagnostic tool. Contrast enhanced helical CT Scan has replaced the traditional angiography as the screening diagnostic tool of choice Emergency thoracotomy and repair should be reserved for the few patients with isolated TAT without any major concomitant injuries. Delayed management approach with aggressive blood pressure control and serial radiological monitoring is a safe and recommended option for those with severe concomitant injuries or other medical co-morbidity that puts surgery at high risk. Active augmentation of the distal perfusion pressure during cross clamp offers the best protection against development of paraplegia during open surgical repair. Endovascular stenting offers a minimally invasive method of treatment but the long-term durability of the endovascular stent is still unknown. We feel that the greater feasibility of the endovascular repair in the acute phase of the thoracic injury is an advantage over the open surgery and should be the treatment of choice in patients with severe concomitant injuries.