Wide-Awake Hand Trauma Surgery: Designing Strategies to Optimise Patient Experience.

INTRODUCTION: The regional hand trauma service in Greater Manchester, United Kingdom, underwent significant reorganisation early in the COVID-19 pandemic, with a shift from predominantly general anaesthesia (GA) procedures to the adoption of a Wide-Awake Local Anaesthetic No Tourniquet (WALANT) technique. We implemented strategies targeted towards optimising patient experience, largely applicable to most healthcare settings. METHODS: Four domains were explored: (i) compliance in timing to nationally agreed treatment guidelines, (ii) the role of patient information leaflets, (iii) the introduction of a post-operative analgesia protocol, and (iv) broadly evaluating the environmental impact following the implementation of a same-day 'see and treat' service. RESULTS: Following reorganisation to a predominantly WALANT service, we observed an increase in compliance with nationally agreed standards for the treatment of common hand injuries. Patient education and peri-operative counselling reduced anxiety, whereas post-operative pain was better managed with the introduction of an analgesic protocol. Using a travel carbon calculator, it can be inferred that there are significant reductions in carbon emissions generated when patients are evaluated and treated on the same day as their clinical presentation. CONCLUSIONS: It is widely acknowledged that WALANT benefits patients and the healthcare system. We contemplated whether further incremental changes in clinical practice could further improve patient experience. Given our findings, we advocate a multi-modal approach with a greater focus on patient outcomes (trials are currently underway, e.g., WAFER) supplemented by universally accepted validated patient-reported outcome measures (PROMs).

Data Infrastructure for Improvement in Perioperative Medicine: Experience at a London Tertiary Hospital.

Adoption of electronic health record systems offers an opportunity to collate massive volumes of complex information about patient care. Healthcare data can inform performance management, enable predictive analytics and enhance strategic decision making. A data-driven approach to improving patient care is vital to address the growing burden of morbidity and mortality associated with major surgery. We describe our methodology for transforming and utilising process of care data in an electronic health record system to develop a registry for quality improvement purposes in patients undergoing major surgery at a single UK hospital. We highlight development of our data-driven vision, technical aspects of processing raw data into metrics relevant to clinical decision making, alongside challenges encountered. Finally, we outline how our data infrastructure supports clinical governance, quality improvement and research. In sharing our experiences, we hope to enable others to embed and access the transformative clinical insights that healthcare data can yield.

Presentation and multidisciplinary management of a unique case of lower limb dysmelia resulting from amniotic band syndrome.

A neonate was born with a unique congenital lower limb dysmelia due to an abnormal presentation of amniotic band syndrome. An anomalous soft tissue tether from the plantar surface of the right foot to the right buttock caused extreme knee flexion, tibial rotation and malformation of the developing foot. This complex malformation required a multidisciplinary team (MDT) approach to decide between reconstruction and amputation. The band of tissue was released operatively at 73 days postdelivery, improving knee extension, and the tissue was banked on the thigh as a tube pedicle for future reconstruction. The patient underwent rehabilitation, which has been shown to be vital for synovial joint formation. At 18 months old, the decision was made to proceed with through-knee amputation and a prosthesis. The literature discussed shows the importance of an MDT approach in complex lower limb cases to give the best functional outcome for the patient.

Inverse planning of lung radiotherapy with photon and proton beams using a discrete ordinates Boltzmann solver.

Objective. A discrete ordinates Boltzmann solver has recently been developed for use as a fast and accurate dose engine for calculation of photon and proton beams. The purpose of this study is to apply the algorithm to the inverse planning process for photons and protons and to evaluate the impact that this has on the quality of the final solution.Approach.The method was implemented into an iterative least-squares inverse planning optimiser, with the Boltzmann solver used every 20 iterations over the total of 100 iterations. Elemental dose distributions for the intensity modulation and the dose changes at the intermediate iterations were calculated by a convolution algorithm for photons and a simple analytical model for protons. The method was evaluated for 12 patients in the heterogeneous tissue environment encountered in radiotherapy of lung tumours. Photon arc and proton arc treatments were considered in this study. The results were compared with those for use of the Boltzmann solver solely at the end of inverse planning or not at all.Main results.Application of the Boltzmann solver at the end of inverse planning shows the dose heterogeneity in the planning target volume to be greater than calculated by convolution and empirical methods, with the median root-mean-square dose deviation increasing from 3.7 to 5.3 for photons and from 1.9 to 3.4 for proton arcs. Use of discrete ordinates throughout inverse planning enables homogeneity of target coverage to be maintained throughout, the median root-mean-square dose deviation being 3.6 for photons and 2.3 for protons. Dose to critical structures is similar with discrete ordinates and conventional methods. Time for inverse planning with discrete ordinates takes around 1-2 h using a contemporary computing environment.Significance.By incorporating the Boltzmann solver into an iterative least squares inverse planning optimiser, accurate dose calculation in a heterogeneous medium is obtained throughout inverse planning, with the result that the final dose distribution is of the highest quality.

Functional lung avoidance in radiotherapy using optimisation of biologically effective dose with non-coplanar beam orientations.

Background and purpose: In external beam radiotherapy for non-small cell lung cancer, dose to functioning lung should be minimised to reduce lung morbidity. This study aimed to develop a method for avoiding beam delivery through functional lung and to quantify the possible benefit to the patients. Materials and methods: Twelve patients that were treated as part of a clinical trial of single photon emission computed tomography (SPECT) functional lung avoidance were retrospectively studied. During treatment planning, the dose in the lung was weighted by the relative intensity of the functional image. A single conformal beam was scanned systematically around the planning target volume to find optimum orientations and the resulting map of functional dose variation with gantry and couch angle was used to select five non-coplanar intensity-modulated beams, taking into account directions prohibited due to collision risk. Expected reduction in pneumonitis risk was calculated using a logistic model. Results: The volume of lung irradiated to a functionally weighted dose of 5 Gy was 11.8 % (range 3.5 %-22.0 %) for functional plans, versus 20.9 % (range 4.9 %-33.3 %) for conventional plans (p = 0.002). Mean functionally weighted dose was 4.1 Gy (range 1.3 Gy-7.2 Gy) for functional plans, versus 4.5 Gy (range 1.5 Gy-8.3 Gy) for conventional plans (p = 0.002). Predicted pneumonitis risk was reduced by 4.3 % (range 0.4 %-15.6 %) (p = 0.002). Conclusions: By seeking the optimum non-coplanar beam orientations, it is possible to reduce dose/volume lung parameters by 10% or more, consistently in all patients, regardless of the pattern of lung perfusion. A prediction model indicates that this will improve radiation-associated lung injury.

A discrete ordinates Boltzmann solver for application to inverse planning of photons and protons.

The aim of this work is to develop a discrete ordinates Boltzmann solver that can be used for calculation of absorbed dose from both photons and protons within an inverse planning optimiser, so as to perform accurate dose calculation throughout the whole of the inverse planning process. With photons, five transport sweeps were performed to obtain scattered photon fluence, and unscattered electron fluence was then obtained and used as a fixed source for solution of the electron transport equations. With protons, continuous slowing down was treated as a fixed source, and five transport sweeps were used to calculate scattered fluence. The total electron or proton fluence was multiplied by the stopping power ratio for the transport medium to obtain absorbed dose. The method was evaluated in homogeneous media and in a lung case where the planning target volume was surrounded by low-density lung material. Photon arc, proton passive scattering and proton arc treatments were considered. The results were compared to a clinically validated convolution dose calculation for photons, and with an analytical method for protons. In water-equivalent media, the discrete ordinates method agrees with the alternative algorithms to within 2%. Convergence is found to be sufficiently complete for water-, lung- and bone-equivalent materials after five iterations. The dose calculated by the relatively simple angular quadrature is seen to be very close to that calculated by a more comprehensive quadrature. For inhomogeneous lung plans, the method shows more heterogeneity of dose to the planning target volume than the comparative methods. The discrete ordinates Boltzmann solver provides a general framework for dose calculation with both photons and protons. The method is suitable for incorporation into an inverse planning optimiser, so that accurate dose calculation in a heterogeneous medium can be obtained throughout inverse planning, with the result that the final dose distribution is as predicted by the optimiser.

Detection of locally adapted genomic regions in wild rice (Oryza rufipogon) using environmental association analysis.

Oryza rufipogon is the wild progenitor of cultivated rice Oryza sativa and exhibits high levels of genetic diversity across its distribution, making it a useful resource for the identification of abiotic stress-tolerant varieties and genes that could limit future climate-changed-induced yield losses. To investigate local adaptation in O. rufipogon, we analyzed single nucleotide polymorphism (SNP) data from a panel of 286 samples located across a diverse range of climates. Environmental association analysis (EAA), a genome-wide association study (GWAS)-based method, was used and revealed 15 regions of the genome significantly associated with various climate factors. Genes within these environmentally associated regions have putative functions in abiotic stress response, phytohormone signaling, and the control of flowering time. This provides an insight into potential local adaptation in O. rufipogon and reveals possible locally adaptive genes that may provide opportunities for breeding novel rice varieties with climate change-resilient phenotypes.

Mycobacterium abscessus skin and soft tissue infection following autologous fat grafting in Kurdistan treated with an antibiotic combination including Imipenem-Relebactam and Rifabutin.

Medical tourism is becoming increasingly popular. The most popularly sought operations are cosmetic procedures. With the increase in cosmetic tourism, it is unsurprising that there has also been a rise in skin and soft tissue infections caused by nontuberculous mycobacteria (NTM); in particular by the rapidly growing mycobacteria species. Here we provide a case of a 35 year-old woman who presented after autologous fat grafting with multiple painful, violaceous, and purulent nodules on her arms, legs, and breasts. Infection was found to be due to Mycobacterium abscessus. She was successfully treated with azithromycin, clofazimine, rifabutin, amikacin, imipenem-cilastatin-relebactam (Recarbrio™) and imipenem-cilastatin. This is the first described case of a M. abscessus infection successfully treated using this combination.

Benchmarking Tests of Contemporary SRS Platforms: Have Technological Developments Resulted in Improved Treatment Plan Quality?

PURPOSE: Stereotactic radiosurgery treatment delivery can be performed with a range of devices, each of which have evolved over recent years. We sought to evaluate the differences in performance of contemporary stereotactic radiosurgery platforms and also to compare them with earlier platform iterations from a previous benchmarking study. METHODS AND MATERIALS: The following platforms were selected as "state of the art" in 2022: Gamma Knife Icon (GK), CyberKnife S7 (CK), Brainlab Elements (Elekta VersaHD and Varian TrueBeam), Varian Edge with HyperArc (HA), and Zap-X. Six benchmarking cases were used from a 2016 study. To reflect the evolution of increasing numbers of metastases treated per patient, a 14-target case was added. The 28 targets among the 7 patients ranged from 0.02 to 7.2 cc in volume. Participating centers were sent images and contours for each patient and asked to plan them to the best of their ability. Although some variation in local practice was allowed (eg, margins), groups were asked to prescribe a specified dose to each target and tolerance doses to organs at risk were agreed upon. Parameters compared included coverage, selectivity, Paddick conformity index, gradient index (GI), R50%, efficiency index, doses to organs at risk, and planning and treatment times. RESULTS: Mean coverage for all targets ranged from 98.2% (Brainlab/Elekta) to 99.7% (HA-6X). Paddick conformity index values ranged from 0.722 (Zap-X) to 0.894 (CK). GI ranged from a mean of 3.52 (GK), representing the steepest dose gradient, to 5.08 (HA-10X). The GI appeared to follow a trend with beam energy, with the lowest values from the lower energy platforms (GK, 1.25 MeV; Zap-X, 3 MV) and the highest value from the highest energy (HA-10X). Mean R50% values ranged from 4.48 (GK) to 5.98 (HA-10X). Treatment times were lowest for C-arm linear accelerators. CONCLUSIONS: Compared with earlier studies, newer equipment appears to deliver higher quality treatments. CyberKnife and linear accelerator platforms appear to give higher conformity whereas lower energy platforms yield a steeper dose gradient.

The incidence and management of peripheral nerve injury in England (2005-2020).

Peripheral nerve injury (PNI) is a significant health problem that confers lifelong impact on those injured. Current interventions are purely surgical; however, outcomes remain poor. There is a lack of high-quality epidemiological data that is needed to identify populations involved, current healthcare demands, and ensure resources are distributed to the greatest effect, to reduce the injury burden. METHODS: Anonymized hospital episode statistical (HES) data on admitted patient care was obtained from NHS Digital for all National Health Service (NHS) patients sustaining PNI of all body regions between 2005 and 2020. Total numbers of finished consultant episodes (FCEs) or FCEs/100,000 population were used to demonstrate changes in demographic variables, anatomical locations of injury, mechanisms of injury, speciality, and main operation. RESULTS: There was a mean national incidence of 11.2 (95% CI 10.9, 11.6) events per 100,000 population per year. Males were at least twice as likely (p < 0.0001) to sustain a PNI. Upper limb nerves at or distal to the wrist were most commonly injured. Knife injuries increased (p < 0.0001), whereas glass injuries decreased (p < 0.0001). Plastic surgeons increasingly managed PNI (p = 0.002) as opposed to orthopaedic surgeons (p = 0.006) or neurosurgeons (p = 0.001). There was an increase in neurosynthesis (p = 0.022) and graft procedures (p < 0.0001) during the study period. DISCUSSION: PNI is a significant national healthcare problem predominantly affecting distal, upper limb nerves of men of working age. Injury prevention strategies, improved targeted funding and rehabilitation pathways are needed to reduce the injury burden and improve patient care.

The Perioperative Quality Improvement Programme (PQIP patient study): protocol for a UK multicentre, prospective cohort study to measure quality of care and outcomes after major surgery.

INTRODUCTION: Major surgery accounts for a substantial proportion of health service activity, due not only to the primary procedure, but the longer-term health implications of poor short-term outcome. Data from small studies or from outside the UK indicate that rates of complications and failure to rescue vary between hospitals, as does compliance with best practice processes. Within the UK, there is currently no system for monitoring postoperative complications (other than short-term mortality) in major non-cardiac surgery. Further, there is variation between national audit programmes, in the emphasis placed on quality assurance versus quality improvement, and therefore the principles of measurement and reporting which are used to design such programmes. METHODS AND ANALYSIS: The PQIP patient study is a multi-centre prospective cohort study which recruits patients undergoing major surgery. Patient provide informed consent and contribute baseline and outcome data from their perspective using a suite of patient-reported outcome tools. Research and clinical staff complete data on patient risk factors and outcomes in-hospital, including two measures of complications. Longer-term outcome data are collected through patient feedback and linkage to national administrative datasets (mortality and readmissions). As well as providing a uniquely granular dataset for research, PQIP provides feedback to participating sites on their compliance with evidence-based processes and their patients' outcomes, with the aim of supporting local quality improvement. ETHICS AND DISSEMINATION: Ethical approval has been granted by the Health Research Authority in the UK. Dissemination of interim findings (non-inferential) will form a part of the improvement methodology and will be provided to participating centres at regular intervals, including near-real time feedback of key process measures. Inferential analyses will be published in the peer-reviewed literature, supported by a comprehensive multi-modal communications strategy including to patients, policy makers and academic audiences as well as clinicians.

A phase space model of a Versa HD linear accelerator for application to Monte Carlo dose calculation in a real-time adaptive workflow.

PURPOSE: This study aims to develop and validate a simple geometric model of the accelerator head, from which a particle phase space can be calculated for application to fast Monte Carlo dose calculation in real-time adaptive photon radiotherapy. With this objective in view, the study investigates whether the phase space model can facilitate dose calculations which are compatible with those of a commercial treatment planning system, for convenient interoperability. MATERIALS AND METHODS: A dual-source model of the head of a Versa HD accelerator (Elekta AB, Stockholm, Sweden) was created. The model used parameters chosen to be compatible with those of 6-MV flattened and 6-MV flattening filter-free photon beams in the RayStation treatment planning system (RaySearch Laboratories, Stockholm, Sweden). The phase space model was used to calculate a photon phase space for several treatment plans, and the resulting phase space was applied to the Dose Planning Method (DPM) Monte Carlo dose calculation algorithm. Simple fields and intensity-modulated radiation therapy (IMRT) treatment plans for prostate and lung were calculated for benchmarking purposes and compared with the convolution-superposition dose calculation within RayStation. RESULTS: For simple square fields in a water phantom, the calculated dose distribution agrees to within ±2% with that from the commercial treatment planning system, except in the buildup region, where the DPM code does not model the electron contamination. For IMRT plans of prostate and lung, agreements of ±2% and ±6%, respectively, are found, with slightly larger differences in the high dose gradients. CONCLUSIONS: The phase space model presented allows convenient calculation of a phase space for application to Monte Carlo dose calculation, with straightforward translation of beam parameters from the RayStation beam model. This provides a basis on which to develop dose calculation in a real-time adaptive setting.

A recurrent neural network for rapid detection of delivery errors during real-time portal dosimetry.

Background and purpose: Real-time portal dosimetry compares measured images with predicted images to detect delivery errors as the radiotherapy treatment proceeds. This work aimed to investigate the performance of a recurrent neural network for processing image metrics so as to detect delivery errors as early as possible in the treatment. Materials and methods: Volumetric modulated arc therapy (VMAT) plans of six prostate patients were used to generate sequences of predicted portal images. Errors were introduced into the treatment plans and the modified plans were delivered to a water-equivalent phantom. Four different metrics were used to detect errors. These metrics were applied to a threshold-based method to detect the errors as soon as possible during the delivery, and also to a recurrent neural network consisting of four layers. A leave-two-out approach was used to set thresholds and train the neural network then test the resulting systems. Results: When using a combination of metrics in conjunction with optimal thresholds, the median segment index at which the errors were detected was 107 out of 180. When using the neural network, the median segment index for error detection was 66 out of 180, with no false positives. The neural network reduced the rate of false negative results from 0.36 to 0.24. Conclusions: The recurrent neural network allowed the detection of errors around 30% earlier than when using conventional threshold techniques. By appropriate training of the network, false positive alerts could be prevented, thereby avoiding unnecessary disruption to the patient workflow.

Delivery of drinking, eating and mobilising (DrEaMing) and its association with length of hospital stay after major noncardiac surgery: observational cohort study.

BACKGROUND: Enhanced recovery pathways are associated with improved postoperative outcomes. However, as enhanced recovery pathways have become more complex and varied, compliance has reduced. The 'DrEaMing' bundle re-prioritises early postoperative delivery of drinking, eating, and mobilising. We investigated relationships between DrEaMing compliance, postoperative hospital length of stay (LOS), and complications in a prospective multicentre major surgical cohort. METHODS: We interrogated the UK Perioperative Quality Improvement Programme dataset. Analyses were conducted in four stages. In an exploratory cohort, we identified independent predictors of DrEaMing. We quantified the association between delivery of DrEaMing (and its component variables) and prolonged LOS in a homogenous colorectal subgroup and assessed generalisability in multispecialty patients. Finally, LOS and complications were compared across hospitals, stratified by DrEaMing compliance. RESULTS: The exploratory cohort comprised 22 218 records, the colorectal subgroup 7230, and the multispecialty subgroup 5713. DrEaMing compliance was 59% (13 112 patients), 60% (4341 patients), and 60% (3421), respectively, but varied substantially between hospitals. Delivery of DrEaMing predicted reduced odds of prolonged LOS in colorectal (odds ratio 0.51 [0.43-0.59], P<0.001) and multispecialty cohorts (odds ratio 0.47 [0.41-0.53], P<0.001). At the hospital level, complications were not the primary determinant of LOS after colorectal surgery, but consistent delivery of DrEaMing was associated with significantly shorter LOS. CONCLUSIONS: Delivery of bundled and unbundled DrEaMing was associated with substantial reductions in postoperative LOS, independent of the effects of confounder variables. Consistency of process delivery, and not complications, predicted shorter hospital-level length of stay. DrEaMing may be adopted by perioperative health systems as a quality metric to support improved patient outcomes and reduced hospital length of stay.

COP26 and the climate crisis: How can plastic surgeons do their bit?

In this piece of correspondence, the authors set out their strategies for how plastic surgery services can reduce their impact on the environment.