Explore the vast range of titles available.

ObjectivesIntraoperative fluorescence imaging is currently used in a variety of surgical fields for four main purposes: assessing tissue perfusion; identifying/localizing cancer; mapping lymphatic systems; and visualizing anatomy. To establish evidence-based guidance for research and practice, understanding the state of research on fluorescence imaging in different surgical fields is needed. We evaluated the evidence on fluorescence imaging for perfusion assessments using the Idea, Development,Exploration, Assessment, Long Term Study (IDEAL) framework, which was designed for describing the stages of innovation in surgery and other interventional procedures.DesignNarrative literature review with analysis of IDEAL stage of each field of study.SettingAll publications on intraoperative fluorescence imaging for perfusion assessments reported in PubMed through 2019 were identified for six surgical procedures: coronary artery bypass grafting (CABG), upper gastrointestinal (GI) surgery, colorectal surgery, solid organ transplantation, reconstructive surgery, and cerebral aneurysm surgery.Main outcome measuresThe IDEAL stage of research evidence was determined for each specialty field using a previously described approach.Results196 articles (15 003 cases) were selected for analysis. Current status of research evidence was determined to be IDEAL Stage 2a for upper GI and transplantation surgery, IDEAL 2b for CABG, colorectal and cerebral aneurysm surgery, and IDEAL Stage 3 for reconstructive surgery. Using the technique resulted in a high (up to 50%) rate of revisions among surgical procedures, but its efficacy improving postoperative outcomes has not yet been demonstrated by randomized controlled trials in any discipline. Only one possible adverse reaction to intravenous indocyanine green was reported.ConclusionsUsing fluorescence imaging intraoperatively to assess perfusion is feasible and appears useful for surgical decision making across a range of disciplines. Identifying the IDEAL stage of current research knowledge aids in planning further studies to establish the potential for patient benefit.

Simulation-based medicine and the development of complex computer models of biological structures is becoming ubiquitous for advancing biomedical engineering and clinical research. Finite element analysis (FEA) has been widely used in the last few decades to understand and predict biomechanical phenomena. Modeling and simulation approaches in biomechanics are highly interdisciplinary, involving novice and skilled developers in all areas of biomedical engineering and biology. While recent advances in model development and simulation platforms offer a wide range of tools to investigators, the decision making process during modeling and simulation has become more opaque. Hence, reliability of such models used for medical decision making and for driving multiscale analysis comes into question. Establishing guidelines for model development and dissemination is a daunting task, particularly with the complex and convoluted models used in FEA. Nonetheless, if better reporting can be established, researchers will have a better understanding of a model's value and the potential for reusability through sharing will be bolstered. Thus, the goal of this document is to identify resources and considerate reporting parameters for FEA studies in biomechanics. These entail various levels of reporting parameters for model identification, model structure, simulation structure, verification, validation, and availability. While we recognize that it may not be possible to provide and detail all of the reporting considerations presented, it is possible to establish a level of confidence with selective use of these parameters. More detailed reporting, however, can establish an explicit outline of the decision-making process in simulation-based analysis for enhanced reproducibility, reusability, and sharing.

This title examines current research in materials development and discusses their implications for the learning and teaching of languages.

BackgroundFor many abdominal surgical interventions, laparotomy has gradually been replaced by laparoscopy, with numerous benefits for the patient in terms of post-operative recovery. However, during laparoscopy, the endoscope only provides a single viewpoint to the surgeon, leaving numerous blind spots and opening the way to peri-operative adverse events. Alternative camera systems have been proposed, but many lack the requisite resolution/robustness for use during surgery or cannot provide real-time images. Here, we present the added value of the Enhanced Laparoscopic Vision System (ELViS) which overcomes these limitations and provides a broad view of the surgical field in addition to the usual high-resolution endoscope.MethodsExperienced laparoscopy surgeons performed several typical procedure steps on a live pig model. The time-to-completion for surgical exercises performed by conventional endoscopy and ELViS-assisted surgery was measured. A debriefing interview following each operating session was conducted by an ergonomist, and a System Usability Scale (SUS) score was determined.ResultsProof of concept of ELVIS was achieved in an animal model with seven expert surgeons without peroperative adverse events related to the surgical device. No differences were found in time-to-completion. Mean SUS score was 74.7, classifying the usability of the ELViS as “good”. During the debriefing interview, surgeons highlighted several situations where the ELViS provided a real advantage (such as during instrument insertion, exploration of the abdominal cavity or for orientation during close work) and also suggested avenues for improvement of the system.ConclusionsThis first test of the ELViS prototype on a live animal model demonstrated its usability and provided promising and useful feedback for further development.

Uveitis is a major cause of ocular morbidity, potentially leading to significant visual impairment. The recent adoption of alternative drug delivery options has led to the development of new sustained-delivery corticosteroid systems, able to manage successfully chronic noninfectious posterior uveitis. The treatment goal is to target the site of inflammation with low dose of corticosteroids, delivered over an extended period of time, to minimize the cumulative damage resulting from repeated recurrences, reducing both injections frequency and ocular side effects. This article will review the pharmacology and preliminary clinical data of the 0.18 mg fluocinolone acetonide intravitreal implant (YUTIQ™), to show its efficacy and safety in the treatment of noninfectious posterior uveitis.

ObjectivesUltrasound-guided regional anesthesia (UGRA) relies on acquiring and interpreting an appropriate view of sonoanatomy. Artificial intelligence (AI) has the potential to aid this by applying a color overlay to key sonoanatomical structures.The primary aim was to determine whether an AI-generated color overlay was associated with a difference in participants’ ability to identify an appropriate block view over a 2-month period after a standardized teaching session (as judged by a blinded assessor). Secondary outcomes included the ability to identify an appropriate block view (unblinded assessor), global rating score and participant confidence scores.DesignRandomized, partially blinded, prospective cross-over study.SettingSimulation scans on healthy volunteers. Initial assessments on 29 November 2022 and 30 November 2022, with follow-up on 25 January 2023 – 27 January 2023.Participants57 junior anesthetists undertook initial assessments and 51 (89.47%) returned at 2 months.InterventionParticipants performed ultrasound scans for six peripheral nerve blocks, with AI assistance randomized to half of the blocks. Cross-over assignment was employed for 2 months.Main outcome measuresBlinded experts assessed whether the block view acquired was acceptable (yes/no). Unblinded experts also assessed this parameter and provided a global performance rating (0–100). Participants reported scan confidence (0–100).ResultsAI assistance was associated with a higher rate of appropriate block view acquisition in both blinded and unblinded assessments (p=0.02 and <0.01, respectively). Participant confidence and expert rating scores were superior throughout (all p<0.01).ConclusionsAssistive AI was associated with superior ultrasound scanning performance 2 months after formal teaching. It may aid application of sonoanatomical knowledge and skills gained in teaching, to support delivery of UGRA beyond the immediate post-teaching period.Trial registration numberNCT05583032.

ObjectiveThe Global IDEAL Sub-Framework Study aimed to combine the intended effects of the 2009/2019 IDEAL (Idea, Development, Exploration, Assessment, Long-term study) Framework recommendations on evaluating surgical innovation with the vision outlined by the 2015 Lancet Commission on Global Surgery to provide recommendations for evaluating surgical innovation in low-resource environments.DesignA mixture of methods including an online global survey and semistructured interviews (SSIs). Quantitative data were summarized with descriptive statistics and qualitative data were analyzed using the Framework Method.ParticipantsSurgeons and surgical researchers from any country.Main outcome measuresFindings were used to suggest the nature of adaptations to the IDEAL Framework to address the particular problems of evaluation in low-resource settings.ResultsThe online survey yielded 66 responses representing experience from 40 countries, and nine individual SSIs were conducted. Most respondents (n=49; 74.2%) had experience evaluating surgical technologies across a range of life cycle stages. Innovation was most frequently adopted based on colleague recommendation or clinical evaluation in other countries. Four themes emerged, centered around: frugal innovation in technological development; evaluating the same technology/innovation in different contexts; additional methodologies important in evaluation of surgical innovation in low/middle-income countries; and support for low-income country researchers along the evaluation pathway.ConclusionsThe Global IDEAL Sub-Framework provides suggestions for modified IDEAL recommendations aimed at dealing with the special problems found in this setting. These will require validation in a stakeholder consensus forum, and qualitative assessment in pilot studies. From assisting researchers with identification of the correct evaluation stage, to providing context-specific recommendations relevant to the whole evaluation pathway, this process will aim to develop a comprehensive and applicable set of guidance that will benefit surgical innovation and patients globally.

Occupational back-support exoskeletons, categorized as active or passive, hold promise for mitigating work-related musculoskeletal disorders. However, their impact on combined physical and cognitive aspects of industrial work performance remains inadequately understood, especially regarding potential differences between exoskeleton categories. A randomized, counterbalanced cross-over study was conducted, comparing the active CrayX, passive Paexo Back, and a no exoskeleton condition. A 15-min dual task was used to simulate both cognitive and physical aspects of industrial work performance. Cognitive workload parameters included reaction time, accuracy, and subjective measures. Physical workload included movement duration, segmented in three phases: (1) walking to and grabbing the box, (2) picking up, carrying, and putting down the box, and (3) returning to the starting point. Comfort of both devices was also surveyed. The Paexo significantly increased movement duration in the first segment compared to NoExo (Paexo = 1.55 ± 0.19 s; NoExo = 1.32 ± 0.17 s; p  < .01). Moreover, both the Paexo and CrayX increased movement duration for the third segment compared to NoExo (CrayX = 1.70 ± 0.27 s; Paexo = 1.74 ± 0.27 s, NoExo = 1.54 ± 0.23 s; p  < .01). No significant impact on cognitive outcomes was observed. Movement Time 2 was not significantly affected by both exoskeletons. Results of the first movement segment suggest the Paexo may hinder trunk bending, favoring the active device for dynamic movements. Both devices may have contributed to a higher workload as the movement duration in the third segment increased compared to NoExo.

BackgroundIn France, 25% of healthcare emissions are attributed to the supply of medical devices, underscoring the necessity for the development of more sustainable procurement policies. However, comparing the carbon footprint of different devices, especially single-use devices versus reusable ones, presents challenges.ObjectiveTo assess the carbon footprint of single-use and reusable electrosurgical scalpels over 1 year of use in our hospital setting.DesignA cradle-to-grave analysis was conducted from May 1, 2022, to April 30, 2023.SettingNantes University Hospital, France.Main outcome measuresThe study quantifies carbon emissions across all life cycle stages: raw material extraction, manufacturing, transportation, use, maintenance, and disposal. For reusable devices, sterilization emissions were allocated based on the total annual workload of the Central Sterile Services Department. Carbon footprint values were derived from direct measurements, manufacturer and supplier data, and literature, with conversions using a public and national database (Base Empreinte, ADEME).ResultsThe carbon footprint of single-use devices was estimated at 4291 kg of carbon dioxide equivalent (CO2e), with 94% attributed to the production of the device itself. The carbon footprint related to the reusable device was estimated at 494 kg CO2e, with 86% stemming from handling at our sterilization unit.ConclusionsThese findings are contingent on our hospital’s practices and may vary based on several factors. Beyond estimating these carbon footprints, it provides a practical, decision-oriented analysis accessible for hospital leadership and healthcare professionals, supporting institutional change.

ObjectivesTo examine the current state of unique device identifier (UDI) implementation, including barriers and facilitators, among eight health systems participating in a research network committed to real-world evidence (RWE) generation for medical devices.DesignMixed methods, including a structured survey and semistructured interviews.SettingEight health systems participating in the National Evaluation System for health Technology research network within the USA.ParticipantsIndividuals identified as being involved in or knowledgeable about UDI implementation or medical device identification from supply chain, information technology and high-volume procedural area(s) in their health system.Main outcomes measuresInterview topics were related to UDI implementation, including barriers and facilitators; UDI use; benefits of UDI adoption; and vision for UDI implementation. Data were analysed using directed content analysis, drawing on prior conceptual models of UDI implementation and the Exploration, Preparation, Implementation, Sustainment framework. A brief survey of health system characteristics and scope of UDI implementation was also conducted.ResultsThirty-five individuals completed interviews. Three of eight health systems reported having implemented UDI. Themes identified about barriers and facilitators to UDI implementation included knowledge of the UDI and its benefits among decision-makers; organisational systems, culture and networks that support technology and workflow changes; and external factors such as policy mandates and technology. A final theme focused on the availability of UDIs for RWE; lack of availability significantly hindered RWE studies on medical devices.ConclusionsUDI adoption within health systems requires knowledge of and impetus to achieve operational and clinical benefits. These are necessary to support UDI availability for medical device safety and effectiveness studies and RWE generation.