The Updated Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT 2.0).

The Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT) has been expanded to include more patients and CT attenuation correction imaging. We present the design and initial results from the updated registry. Methods: The updated REFINE SPECT is a multicenter, international registry with clinical data and image files. SPECT images were processed by quantitative software and CT images by deep learning software detecting coronary artery calcium (CAC). Patients were followed for major adverse cardiovascular events (MACEs) (death, myocardial infarction, unstable angina, late revascularization). Results: The registry included scans from 45,252 patients from 13 centers (55.9% male, 64.7 ± 11.8 y). Correlating invasive coronary angiography was available for 3,786 (8.4%) patients. CT attenuation correction imaging was available for 13,405 patients. MACEs occurred in 6,514 (14.4%) patients during a median follow-up of 3.6 y (interquartile range, 2.5-4.8 y). Patients with a stress total perfusion deficit of 5% to less than 10% (unadjusted hazard ratio [HR], 2.42; 95% CI, 2.23-2.62) and a stress total perfusion deficit of at least 10% (unadjusted HR, 3.85; 95% CI, 3.56-4.16) were more likely to experience MACEs. Patients with a deep learning CAC score of 101-400 (unadjusted HR, 3.09; 95% CI, 2.57-3.72) and a CAC of more than 400 (unadjusted HR, 5.17; 95% CI, 4.41-6.05) were at increased risk of MACEs. Conclusion: The REFINE SPECT registry contains a comprehensive set of imaging and clinical variables. It will aid in understanding the value of SPECT myocardial perfusion imaging, leverage hybrid imaging, and facilitate validation of new artificial intelligence tools for improving prediction of adverse outcomes incorporating multimodality imaging.

Heat stress analysis suggests a genetic basis for tolerance in Macrocystis pyrifera across developmental stages.

Kelps are vital for marine ecosystems, yet the genetic diversity underlying their capacity to adapt to climate change remains unknown. In this study, we focused on the kelp Macrocystis pyrifera a species critical to coastal habitats. We developed a protocol to evaluate heat stress response in 204 Macrocystis pyrifera genotypes subjected to heat stress treatments ranging from 21 °C to 27 °C. Here we show that haploid gametophytes exhibiting a heat-stress tolerant (HST) phenotype also produced greater biomass as genetically similar diploid sporophytes in a warm-water ocean farm. HST was measured as chlorophyll autofluorescence per genotype, presented here as fluorescent intensity values. This correlation suggests a predictive relationship between the growth performance of the early microscopic gametophyte stage HST and the later macroscopic sporophyte stage, indicating the potential for selecting resilient kelp strains under warmer ocean temperatures. However, HST kelps showed reduced genetic variation, underscoring the importance of integrating heat tolerance genes into a broader genetic pool to maintain the adaptability of kelp populations in the face of climate change.

Baseline Predictors of Adverse Outcomes for Transthyretin Amyloidosis Cardiomyopathy Patients Treated and Untreated with Tafamidis: A Canadian Referral Center Experience.

Background: Tafamidis is a costly therapy that improves outcomes for patients with transthyretin amyloidosis cardiomyopathy (ATTR-CM), although significant knowledge gaps exist for predicting longer-term response to treatment. The purpose of this study was to examine baseline predictors of adverse outcomes and their association with tafamidis treatment in comparison with those untreated in a clinical cohort from a Canadian ATTR-CM referral center. Methods: Patients with a confirmed diagnosis of ATTR-CM were included. Multivariable modeling was used to identify baseline variables associated with the primary outcome of all-cause mortality and secondary outcomes of cardiovascular mortality or hospitalization. Cox proportional hazard and competing risk analyses were used, with tafamidis modeled as a time-varying covariate. Results: In total, 139 ATTR-CM patients were included, with a median age of 80.9 years [74.3-86.6 years], from 2011 to 2022. The mean follow-up was 2.9 ± 1.8 years. Eighty (55%) patients were treated with tafamidis. All-cause mortality and cardiovascular mortality alone were associated with the following baseline variables: age, clinical frailty scale, systolic blood pressure, renal function, and right ventricular size and function (all p < 0.05), with no identified interactions with tafamidis treatment. Only baseline renal function was associated with cardiovascular hospitalization (p < 0.05). Conclusion: Important baseline variables associated with adverse ATTR-CM disease outcomes included renal function, systolic blood pressure, frailty, and right ventricular size and function. The risk factors were independent of treatment with tafamidis. These findings may help improve risk stratification for determining eligibility for ATTR-CM therapies.

AI for Multistructure Incidental Findings and Mortality Prediction at Chest CT in Lung Cancer Screening.

Background Incidental extrapulmonary findings are commonly detected on chest CT scans and can be clinically important. Purpose To integrate artificial intelligence (AI)-based segmentation for multiple structures, coronary artery calcium (CAC), and epicardial adipose tissue with automated feature extraction methods and machine learning to detect extrapulmonary abnormalities and predict all-cause mortality (ACM) in a large multicenter cohort. Materials and Methods In this post hoc analysis, baseline chest CT scans in patients enrolled in the National Lung Screening Trial (NLST) from August 2002 to September 2007 were included from 33 participating sites. Per scan, 32 structures were segmented with a multistructure model. For each structure, 15 clinically interpretable radiomic features were quantified. Four general codes describing abnormalities reported by NLST radiologists were applied to identify extrapulmonary significant incidental findings on the CT scans. Death at 2-year and 10-year follow-up and the presence of extrapulmonary significant incidental findings were predicted with ensemble AI models, and individualized structure risk scores were evaluated. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the performance of the models for prediction of ACM and extrapulmonary significant incidental findings. The Pearson χ2 test and Kruskal-Wallis rank sum test were used for statistical analyses. Results A total of 24 401 participants (median age, 61 years [IQR, 57-65 years]; 14 468 male) were included. In 3880 of 24 401 participants (16%), 4283 extrapulmonary significant incidental findings were reported. During the 10-year follow-up, 3389 of 24 401 participants (14%) died. CAC had the highest feature importance for predicting the three study end points. The 10-year ACM model demonstrated the best AUC performance (0.72; per-year mortality of 2.6% above and 0.8% below the risk threshold), followed by 2-year ACM (0.71; per-year mortality of 1.13% above and 0.3% below the risk threshold) and prediction of extrapulmonary significant incidental findings (0.70; probability of occurrence of 25.4% above and 9.6% below the threshold). Conclusion A fully automated AI model indicated extrapulmonary structures at risk on chest CT scans and predicted ACM with explanations. ClinicalTrials.gov Identifier: NCT00047385 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Yanagawa and Hata in this issue.

A Case Demonstration of the Open Health Natural Language Processing Toolkit From the National COVID-19 Cohort Collaborative and the Researching COVID to Enhance Recovery Programs for a Natural Language Processing System for COVID-19 or Postacute Sequelae of SARS CoV-2 Infection: Algorithm Development and Validation.

BACKGROUND: A wealth of clinically relevant information is only obtainable within unstructured clinical narratives, leading to great interest in clinical natural language processing (NLP). While a multitude of approaches to NLP exist, current algorithm development approaches have limitations that can slow the development process. These limitations are exacerbated when the task is emergent, as is the case currently for NLP extraction of signs and symptoms of COVID-19 and postacute sequelae of SARS-CoV-2 infection (PASC). OBJECTIVE: This study aims to highlight the current limitations of existing NLP algorithm development approaches that are exacerbated by NLP tasks surrounding emergent clinical concepts and to illustrate our approach to addressing these issues through the use case of developing an NLP system for the signs and symptoms of COVID-19 and PASC. METHODS: We used 2 preexisting studies on PASC as a baseline to determine a set of concepts that should be extracted by NLP. This concept list was then used in conjunction with the Unified Medical Language System to autonomously generate an expanded lexicon to weakly annotate a training set, which was then reviewed by a human expert to generate a fine-tuned NLP algorithm. The annotations from a fully human-annotated test set were then compared with NLP results from the fine-tuned algorithm. The NLP algorithm was then deployed to 10 additional sites that were also running our NLP infrastructure. Of these 10 sites, 5 were used to conduct a federated evaluation of the NLP algorithm. RESULTS: An NLP algorithm consisting of 12,234 unique normalized text strings corresponding to 2366 unique concepts was developed to extract COVID-19 or PASC signs and symptoms. An unweighted mean dictionary coverage of 77.8% was found for the 5 sites. CONCLUSIONS: The evolutionary and time-critical nature of the PASC NLP task significantly complicates existing approaches to NLP algorithm development. In this work, we present a hybrid approach using the Open Health Natural Language Processing Toolkit aimed at addressing these needs with a dictionary-based weak labeling step that minimizes the need for additional expert annotation while still preserving the fine-tuning capabilities of expert involvement.

Intercellular Adhesion Molecule 1 (ICAM-1): An Inflammatory Regulator with Potential Implications in Ferroptosis and Parkinson's Disease.

Intercellular adhesion molecule 1 (ICAM-1/CD54), a transmembrane glycoprotein, has been considered as one of the most important adhesion molecules during leukocyte recruitment. It is encoded by the ICAM1 gene and plays a central role in inflammation. Its crucial role in many inflammatory diseases such as ulcerative colitis and rheumatoid arthritis are well established. Given that neuroinflammation, underscored by microglial activation, is a key element in neurodegenerative diseases such as Parkinson's disease (PD), we investigated whether ICAM-1 has a role in this progressive neurological condition and, if so, to elucidate the underpinning mechanisms. Specifically, we were interested in the potential interaction between ICAM-1, glial cells, and ferroptosis, an iron-dependent form of cell death that has recently been implicated in PD. We conclude that there exist direct and indirect (via glial cells and T cells) influences of ICAM-1 on ferroptosis and that further elucidation of these interactions can suggest novel intervention for this devastating disease.

AI-Derived Left Ventricular Mass From Noncontrast Cardiac CT: Correlation With Contrast CT Angiography and CMR.

Background: Noncontrast computed tomography (CT) scans are not used for evaluating left ventricle myocardial mass (LV mass), which is typically evaluated with contrast CT or cardiovascular magnetic resonance imaging (CMR). Objectives: The purpose of the study was to assess the feasibility of LV mass estimation from standard, ECG-gated, noncontrast CT using an artificial intelligence (AI) approach and compare it with coronary CT angiography (CTA) and CMR. Methods: We enrolled consecutive patients who underwent coronary CTA, which included noncontrast CT calcium scanning and contrast CTA, and CMR. The median interval between coronary CTA and CMR was 22 days (interquartile range: 3-76). We utilized a no new UNet AI model that automatically segmented noncontrast CT structures. AI measurement of LV mass was compared to contrast CTA and CMR. Results: A total of 316 patients (age: 57.1 ± 16.7 years, 56% male) were included. The AI segmentation took on average 22 seconds per case. An excellent correlation was observed between AI and contrast CTA LV mass measures (r = 0.84, P < 0.001), with no significant differences (136.5 ± 55.3 g vs 139.6 ± 56.9 g, P = 0.133). Bland-Altman analysis showed minimal bias of 2.9. When compared to CMR, measured LV mass was higher with AI (136.5 ± 55.3 g vs 127.1 ± 53.1 g, P < 0.001). There was an excellent correlation between AI and CMR (r = 0.85, P < 0.001), with a small bias (-9.4). There were no statistical differences between the correlations of LV mass between contrast CTA and CMR or AI and CMR. Conclusions: The AI-based automated estimation of LV mass from noncontrast CT demonstrated excellent correlations and minimal biases when compared to contrast CTA and CMR.

Risk of tuberculosis after initiation of antiretroviral therapy among persons with HIV in Europe.

OBJECTIVES: Tuberculosis (TB) risk after initiation of antiretroviral treatment (ART) is not well described in a European setting, with an average TB incidence of 25/105 in the background population. METHODS: We included all adult persons with HIV starting ART in the RESPOND cohort between 2012 and 2020. TB incidence rates (IR) were assessed for consecutive time intervals post-ART initiation. Risk factors for TB within 6 months from ART initiation were evaluated using Poisson regression models. RESULTS: Among 8441 persons with HIV, who started ART, 66 developed TB during 34,239 person-years of follow-up (PYFU), corresponding to 1.87/1000 PYFU (95% confidence interval [CI]: 1.47-2.37). TB IR was highest in the first 3 months after ART initiation (14.41/1000 PY (95%CI 10.08-20.61]) and declined at 3-6, 6-12, and >12 months post-ART initiation (5.89 [95%CI 3.35-10.37], 2.54 [95%CI 1.36-4.73] and 0.51 [95%CI 0.30-0.86]), respectively. Independent risk factors for TB within the first 6 months after ART initiation included follow-up in Northern or Eastern Europe region, African origin, baseline CD4 count <200 cells/mm3, HIV RNA >100,000 copies/mL, injecting drug use and heterosexual transmission. CONCLUSIONS: TB IR was highest in the first 3 months post-ART initiation and was associated with baseline risk factors, highlighting the importance of thorough TB risk assessment at ART initiation.

A systematic review of clinical and laboratory studies comparing vascularised versus non-vascularised nerve grafts in peripheral nerve reconstruction.

BACKGROUND: Peripheral nerve injuries (PNIs) are common, with complex defects posing a significant reconstructive challenge. Although vascularised (VNGs) and non-vascularised nerve grafts (NVNGs) are established treatment options, there is no comprehensive summary of the evidence supporting their clinical, electrophysiological, and histological outcomes. This review aims to systematically evaluate the clinical and laboratory literature comparing VNGs and NVNGs to inform future clinical practice and research. METHODS: This review was prospectively registered and reported according to PRISMA guidelines. PubMed, EMBASE, SCOPUS, and the Cochrane Register were systematically searched. Studies comparing VNGs and NVNGs in PNIs were included. Meta-analyses were performed for outcomes reported in ≥3 laboratory studies. Functional outcomes were synthesised by vote-counting based on direction of effect for clinical studies. Risk-of-bias was assessed using RoB2, ROBINS-I, and SYRCLE, and the certainty of evidence was evaluated using GRADE. RESULTS: Seven clinical and 34 laboratory studies were included. Of the clinical comparisons, 90% and 56% identified an effect on recovery of sensibility (p = 0.01) and motor function (p = 0.05), respectively, that favoured VNGs. Nine (of 13) separate meta-analyses of laboratory studies demonstrated reduced muscular atrophy, superior axonal regeneration, and remyelination in VNGs. VNGs eliminated the 3-day interval of ischaemia otherwise sustained by NVNGs. Overall, the quality of evidence was low. CONCLUSION: This systematic review indicates that VNGs may offer some advantages over NVNGs in PNI reconstruction. However, due to the low quality of evidence, significant statistical heterogeneity, and clinical diversity of the included studies, these conclusions should be interpreted with caution. Further high-quality clinical trials are necessary to validate these findings.

Muscle and tendon morphology of a world strongman and deadlift champion.

This study compared the muscle and tendon morphology of an extraordinarily strong individual, a World's Strongest Man and deadlift champion (WSM), with that of various other athletic, trained, and untrained populations. The WSM completed the following: 1) 3.0-T MRI scans, to determine the volume of 22 individual lower limb muscles, 5 functional muscle groups, patellar tendon (PT) cross-sectional area (CSA), and PT moment arm; and 2) countermovement jumps (CMJ) and isometric midthigh pull (IMTP) contractions. The WSM was compared with previously assessed groups from our laboratory (muscle and tendon) and the wider research literature (CMJ and IMTP). The WSM's CMJ peak power (9,866 W) and gross (9,171 N) and net (7,480 N) IMTP peak forces were higher than any previously published values. The WSM's overall measured leg muscle volume was approximately twice that of untrained controls (+96%) but with pronounced anatomical variability in the extent of muscular development. The plantar flexor group (+120%) and the guy rope muscles (sartorius, gracilis, and semitendinosus: +140% to +202%), which stabilize the pelvis and femur, demonstrated the largest differences relative to that of untrained controls. The WSM's pronounced quadriceps size (greater than or equal to twofold vs. untrained) was accompanied by modest PT moment arm differences and, notably, was not matched by an equivalent difference in PT CSA (+30%). These results provide novel insight into the musculotendinous characteristics of an extraordinarily strong individual, which may be toward the upper limit of human variation, such that the WSM's very pronounced lower limb muscularity also exhibited distinct anatomical variability and with muscle size largely uncoupled from tendon size.NEW & NOTEWORTHY Lower-body muscle size of an extraordinarily strong individual, a World's Strongest Man and deadlift champion (WSM), was approximately twice that of controls but was underpinned by pronounced anatomical variability in the extent of muscular development (+23-202%): the plantar flexor group and guy rope muscles demonstrating the largest differences. The WSM's quadriceps size (more than or equal to twice that of controls) contrasted with modest differences in patella tendon moment arm (+18%) and was uncoupled from patellar tendon size (+30%).

AI-based volumetric six-tissue body composition quantification from CT cardiac attenuation scans enhances mortality prediction: multicenter study.

Background: Computed tomography attenuation correction (CTAC) scans are routinely obtained during cardiac perfusion imaging, but currently only utilized for attenuation correction and visual calcium estimation. We aimed to develop a novel artificial intelligence (AI)-based approach to obtain volumetric measurements of chest body composition from CTAC scans and evaluate these measures for all-cause mortality (ACM) risk stratification. Methods: We applied AI-based segmentation and image-processing techniques on CTAC scans from a large international image-based registry (four sites), to define chest rib cage and multiple tissues. Volumetric measures of bone, skeletal muscle (SM), subcutaneous, intramuscular (IMAT), visceral (VAT), and epicardial (EAT) adipose tissues were quantified between automatically-identified T5 and T11 vertebrae. The independent prognostic value of volumetric attenuation, and indexed volumes were evaluated for predicting ACM, adjusting for established risk factors and 18 other body compositions measures via Cox regression models and Kaplan-Meier curves. Findings: End-to-end processing time was <2 minutes/scan with no user interaction. Of 9918 patients studied, 5451(55%) were male. During median 2.5 years follow-up, 610 (6.2%) patients died. High VAT, EAT and IMAT attenuation were associated with increased ACM risk (adjusted hazard ratio (HR) [95% confidence interval] for VAT: 2.39 [1.92, 2.96], p<0.0001; EAT: 1.55 [1.26, 1.90], p<0.0001; IMAT: 1.30 [1.06, 1.60], p=0.0124). Patients with high bone attenuation were at lower risk of death as compared to subjects with lower bone attenuation (adjusted HR 0.77 [0.62, 0.95], p=0.0159). Likewise, high SM volume index was associated with a lower risk of death (adjusted HR 0.56 [0.44, 0.71], p<0.0001). Interpretations: CTAC scans obtained routinely during cardiac perfusion imaging contain important volumetric body composition biomarkers which can be automatically measured and offer important additional prognostic value.

Formation of a Pseudoaneurysm after a .22 Caliber Bullet Embolized to the Left Femoral Artery: A Case Report.

Bullet embolization is a rare and potentially life-threatening complication of gunshot wounds, particularly in lowpowered and small-caliber bullets. When these small bullets enter a large elastic vessel, they have the potential to leave a small entrance hole that can form a traumatic pseudoaneurysm. These pseudoaneurysms, which may be life-protecting at first, may rupture and lead to exsanguination if not found. We report an interesting case of an 18-year-old male gunshot victim where a bullet formed an aortic pseudoaneurysm and subsequently embolized and present a review of the literature regarding bullet embolization and traumatic pseudoaneurysms.

Current status and future directions in artificial intelligence for nuclear cardiology.

INTRODUCTION: Myocardial perfusion imaging (MPI) is one of the most commonly ordered cardiac imaging tests. Accurate motion correction, image registration, and reconstruction are critical for high-quality imaging, but this can be technically challenging and has traditionally relied on expert manual processing. With accurate processing, there is a rich variety of clinical, stress, functional, and anatomic data that can be integrated to guide patient management. AREAS COVERED: PubMed and Google Scholar were reviewed for articles related to artificial intelligence in nuclear cardiology published between 2020 and 2024. We will outline the prominent roles for artificial intelligence (AI) solutions to provide motion correction, image registration, and reconstruction. We will review the role for AI in extracting anatomic data for hybrid MPI which is otherwise neglected. Lastly, we will discuss AI methods to integrate the wealth of data to improve disease diagnosis or risk stratification. EXPERT OPINION: There is growing evidence that AI will transform the performance of MPI by automating and improving on aspects of image acquisition and reconstruction. Physicians and researchers will need to understand the potential strengths of AI in order to benefit from the full clinical utility of MPI.

Evaluating AI Proficiency in Nuclear Cardiology: Large Language Models take on the Board Preparation Exam.

Background: Previous studies evaluated the ability of large language models (LLMs) in medical disciplines; however, few have focused on image analysis, and none specifically on cardiovascular imaging or nuclear cardiology. Objectives: This study assesses four LLMs - GPT-4, GPT-4 Turbo, GPT-4omni (GPT-4o) (Open AI), and Gemini (Google Inc.) - in responding to questions from the 2023 American Society of Nuclear Cardiology Board Preparation Exam, reflecting the scope of the Certification Board of Nuclear Cardiology (CBNC) examination. Methods: We used 168 questions: 141 text-only and 27 image-based, categorized into four sections mirroring the CBNC exam. Each LLM was presented with the same standardized prompt and applied to each section 30 times to account for stochasticity. Performance over six weeks was assessed for all models except GPT-4o. McNemar's test compared correct response proportions. Results: GPT-4, Gemini, GPT4-Turbo, and GPT-4o correctly answered median percentiles of 56.8% (95% confidence interval 55.4% - 58.0%), 40.5% (39.9% - 42.9%), 60.7% (59.9% - 61.3%) and 63.1% (62.5 - 64.3%) of questions, respectively. GPT4o significantly outperformed other models (p=0.007 vs. GPT-4Turbo, p<0.001 vs. GPT-4 and Gemini). GPT-4o excelled on text-only questions compared to GPT-4, Gemini, and GPT-4 Turbo (p<0.001, p<0.001, and p=0.001), while Gemini performed worse on image-based questions (p<0.001 for all). Conclusion: GPT-4o demonstrated superior performance among the four LLMs, achieving scores likely within or just outside the range required to pass a test akin to the CBNC examination. Although improvements in medical image interpretation are needed, GPT-4o shows potential to support physicians in answering text-based clinical questions.

Reference genes for RT-qPCR analysis in Musa acuminata genotypes contrasting in resistance to Fusarium oxysporum f. sp. cubense subtropical race 4.

Banana (Musa spp.) is the most widely consumed fruit globally. Fusarium wilt, caused by Fusarium oxysporum f. sp. cubense (Foc), is a highly threatening disease to banana production. Resistance genes to Foc exist in wild Musa genotypes such as Musa acuminata subsp. burmannicoides var. Calcutta 4. Whilst real-time PCR (RT-qPCR) is appropriate for accurate analysis of gene expression in pathways involved in host defence responses, reference genes with stable expression under specific biotic stress conditions and host tissue types are necessary for normalization of sample variation. In this context, the stability in potential host reference genes ACT1, APT, EF1α, GAPDH, αTUB, RAN, UBIQ1, UBIQ2, ßTUB1, ßTUB3, L2 and ACTA1 was evaluated in total RNA samples from root tissues in Calcutta 4 (resistant) and Musa sp. cultivar Prata-anã (susceptible) extracted during interaction with Foc subtropical race 4 (STR4). Expression stability was calculated using the algorithms geNorm, NormFinder and BestKeeper. ßTUB3 and L2 were identified as the most stable in Calcutta 4, with ACTA1 and GAPDH the most stable in Prata-anã. These reference genes for analysis of gene expression modulation in the Musa-Foc STR4 pathosystem are fundamental for advancing understanding of host defence responses to this important pathogen.

Guidance on mucositis assessment from the MASCC Mucositis Study Group and ISOO: an international Delphi study.

Background: Mucositis is a common and highly impactful side effect of conventional and emerging cancer therapy and thus the subject of intense investigation. Although common practice, mucositis assessment is heterogeneously adopted and poorly guided, impacting evidence synthesis and translation. The Multinational Association of Supportive Care in Cancer (MASCC) Mucositis Study Group (MSG) therefore aimed to establish expert recommendations for how existing mucositis assessment tools should be used, in clinical care and trials contexts, to improve the consistency of mucositis assessment. Methods: This study was conducted over two stages (January 2022-July 2023). The first phase involved a survey to MASCC-MSG members (January 2022-May 2022), capturing current practices, challenges and preferences. These then informed the second phase, in which a set of initial recommendations were prepared and refined using the Delphi method (February 2023-May 2023). Consensus was defined as agreement on a parameter by >80% of respondents. Findings: Seventy-two MASCC-MSG members completed the first phase of the study (37 females, 34 males, mainly oral care specialists). High variability was noted in the use of mucositis assessment tools, with a high reliance on clinician assessment compared to patient reported outcome measures (PROMs, 47% vs 3%, 37% used a combination). The World Health Organization (WHO) and Common Terminology Criteria for Adverse Events (CTCAE) scales were most commonly used to assess mucositis across multiple settings. Initial recommendations were reviewed by experienced MSG members and following two rounds of Delphi survey consensus was achieved in 91 of 100 recommendations. For example, in patients receiving chemotherapy, the recommended tool for clinician assessment in clinical practice is WHO for oral mucositis (89.5% consensus), and WHO or CTCAE for gastrointestinal mucositis (85.7% consensus). The recommended PROM in clinical trials is OMD/WQ for oral mucositis (93.3% consensus), and PRO-CTCAE for gastrointestinal mucositis (83.3% consensus). Interpretation: These new recommendations provide much needed guidance on mucositis assessment and may be applied in both clinical practice and research to streamline comparison and synthesis of global data sets, thus accelerating translation of new knowledge into clinical practice. Funding: No funding was received.

Establishing the psychological impact of congenital upper limb differences on parents and families.

The aim of this prospective study was to report the psychological experiences of parents caring for children with a congenital upper limb difference and to compare these to population norms. Contributing factors were explored, including access to support and coping strategies. Finally, parents with a congenital upper limb difference themselves were compared to those without. Data recorded included demographics, a validated wellbeing and family impact measure, a unique measure of emotions experienced and exploratory questions. Wellbeing and family impact scores were significantly lower than populations norms. Mothers experienced significantly more negative emotions than fathers. There was no significant different between parents with and without a congenital upper limb difference. Of the parents, 68% felt there should be improved access to psychological support. This demonstrates that parents of children with congenital upper limb differences have unique psychological experiences and needs. They may benefit from specialist psychological support and further research is needed.Level of evidence: III.