Background and AimsHereditary diffuse gastric cancer (HDGC) accounts for 1% of gastric cancer cases. For patients with a germline CDH1 mutation, risk-reducing gastrectomy is recommended. However, for those delaying surgery or for families with no causative mutation identified, regular endoscopy is advised. This study aimed to determine the yield of signet ring cell carcinoma (SRCC) foci in individuals with a CDH1 pathogenic variant compared with those without and how this varies with successive endoscopies.MethodsPatients fulfilling HDGC criteria were recruited to a prospective longitudinal cohort study. Endoscopy was performed according to a strict protocol with visual inspection followed by focal lesion and random biopsy sampling to detect foci of SRCC. Survival analysis determined progression to finding of SRCC according to CDH1 mutation status. The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and 36-item Short Form Health Survey questionnaires assessed quality of life before surveillance and each endoscopy.ResultsEighty-five individuals fulfilling HDGC criteria underwent 201 endoscopies; 54 (63.5%) tested positive for CDH1 mutation. SRCC yield was 61.1% in CDH1 mutation carriers compared with 9.7% in noncarriers, and mutation-positive patients had a 10-fold risk of SRCC on endoscopy compared with those with no mutation detected (P < .0005). Yield of SRCC decreased substantially with subsequent endoscopies. Surveillance was associated with improved psychological health.ConclusionsSRCC foci are prevalent in CDH1 mutation carriers and can be detected at endoscopy using a standardized, multiple biopsy sampling protocol. Decreasing yield over time suggests that the frequency of endoscopy might be reduced. For patients with no CDH1 pathogenic variant detected, the cost-to-benefit ratio needs to be assessed in view of the low yield.

Povidone-iodine (PVI) is principally used as an antimicrobial agent. It has been found that 0.5% PVI can attenuate congestion, edema and pain induced by pressure sores. Thus this study aimed to assess the effects of 0.5% PVI on acute skin wounds. Four full-thickness excisional wounds were generated on the dorsal skin of male Sprague-Dawley rats with a 10-mm sterile punch. Two wounds were left untreated and the other two were dressed with gauze with 0.5% PVI for 1 hour per day for the first 5 days after injury. 10-mm full-thickness excisional wounds were also generated on the dorsal skin of rats treated with 10 mg/kg SB431542 and all wounds were treated with 0.5% PVI for 5 days. PVI treatment enhanced wound healing via promotion of expression of α SMA and TGF β, neovascularization and re-epithelialization. Interleukin 6 was reduced following PVI treatment. Inhibition of TGF β abolished the effect of PVI treatment on wound closure. These data show that topical application of 0.5% PVI could promote acute skin wound healing though increased expression of TGF β leading to enhanced formation of granulation tissue, even in the absence of obvious infection.

BackgroundCOPD has significant psychosocial impact. Self-management support improves quality of life, but programs are not universally available. IT-based self-management interventions can provide home-based support, but have mixed results. We conducted a case series of an off-the-shelf Internet-based health-promotion program, The Preventive Plan (TPP), coupled with nurse-coach support, which aimed to increase patient activation and provide self-management benefits.Materials and methodsA total of 19 COPD patients were recruited, and 14 completed 3-month follow-up in two groups: groups 1 and 2 with more and less advanced COPD, respectively. Change in patient activation was determined with paired t-tests and Wilcoxon signed-rank tests. Benefits and user experience were explored in semistructured interviews, analyzed thematically.ResultsOnly group 1 improved significantly in activation, from a lower baseline than group 2; group 1 also improved significantly in mastery and anxiety. Both groups felt significantly more informed about COPD and reported physical functioning improvements. Group 1 reported improvements in mood and confidence. Overall, group 2 reported fewer benefits than group 1. Both groups valued nurse-coach support; for group 1, it was more important than TPP in building confidence to self-manage. The design of TPP and lack of motivation to use IT were barriers to use, but disease severity and poor IT skills were not.DiscussionOur findings demonstrate the feasibility of combining nurse-coach support aligned to an Internet-based health resource, TPP, in COPD and provide learning about the challenges of such an approach and the importance of the nurse-coach role.

The SARS-CoV-2 (COVID-19) novel corona virus represents a significant health risk, particularly in older patients. Cancer is one of the leading causes of death in most rich countries, and delivering chemotherapy may be associated with increased risk in the presence of a pandemic infection. Estimating this risk is crucial in making decisions about balancing risks and benefits from administering chemotherapy. However, there are no specific data about chemotherapy risks per se. Here we develop a simple model to estimate the potential harms in patients undergoing chemotherapy during a COVID outbreak. We use age-related case fatality rates as a basis for estimating risk, and use previous data from risk of death during influenza outbreaks to estimate the additional risk associated with chemotherapy. We use data from randomised trials to estimate benefit across a range of curative and palliative settings, and address the balance of benefit against the risk of harm. We then use those data to estimate the impact on national chemotherapy delivery patterns.

ObjectiveAnxiety and depression are highly prevalent in patients with COPD and their informal carers, and associated with numerous risk factors. However, few studies have investigated these in primary care or the link between patient and carer anxiety and depression. We aimed to determine this association and factors associated with anxiety and depression in patients, carers, and both (dyads), in a population-based sample.Materials and methodsThis was a prospective, cross-sectional study of 119 advanced COPD patients and their carers. Patient and carer scores ≥8 on the Hospital Anxiety and Depression Scale defined symptoms of anxiety and depression, χ2 tests determined associations between patient and carer symptoms of anxiety/depression, and χ2 and independent t-tests for normally distributed variables (otherwise Mann–Whitney U tests) were used to identify other variables significantly associated with these symptoms in the patient or carer. Patient–carer dyads were categorized into four groups relating to the presence of anxious/depressive symptoms in: both patient and carer, patient only, carer only, and neither. Factors associated with dyad symptoms of anxiety/depression were determined with χ2 tests and one-way analysis of variance for normally distributed variables (otherwise Kruskal–Wallis tests).ResultsPrevalence of symptoms of anxiety and depression was 46.4% (n=52) and 42.9% (n=48) in patients, and 46% (n=52) and 23% (n=26) in carers, respectively. Patient and carer symptoms of anxiety/depression were significantly associated. Anxious and depressive symptoms in the patient were also significantly associated with more physical comorbidities, more exacerbations, greater dyspnea, greater fatigue, poor mastery, and depressive symptoms with younger age. Symptoms of carer anxiety were significantly associated with being female and separated/divorced/widowed, and depressive symptoms with younger age, higher educational level, and more physical comorbidities, and symptoms of carer anxiety and depression with more unmet support needs, greater subjective caring burden, and poor patient mastery. Dyad symptoms of anxiety/depression were significantly associated with greater patient fatigue.ConclusionSymptoms of anxiety and depression in COPD patients and carers are significantly associated. Given their high prevalence, considerable impact on mortality, impact on quality of life and health care use, and associations with each other, screening for and addressing patient and carer anxiety and depression in advanced COPD is recommended.

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Background During the pandemic, remote consultations have become the norm for assessing patients with signs and symptoms of COVID-19 to decrease the risk of transmission. This has intensified the clinical uncertainty already experienced by primary care clinicians when assessing patients with suspected COVID-19 and has prompted the use of risk prediction scores, such as the National Early Warning Score (NEWS2), to assess severity and guide treatment. However, the risk prediction tools available have not been validated in a community setting and are not designed to capture the idiosyncrasies of COVID-19 infection. Objective The objective of this study is to produce a multivariate risk prediction tool, RECAP-V1 (Remote COVID-19 Assessment in Primary Care), to support primary care clinicians in the identification of those patients with COVID-19 that are at higher risk of deterioration and facilitate the early escalation of their treatment with the aim of improving patient outcomes. Methods The study follows a prospective cohort observational design, whereby patients presenting in primary care with signs and symptoms suggestive of COVID-19 will be followed and their data linked to hospital outcomes (hospital admission and death). Data collection will be carried out by primary care clinicians in four arms: North West London Clinical Commissioning Groups (NWL CCGs), Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), Covid Clinical Assessment Service (CCAS), and South East London CCGs (Doctaly platform). The study involves the use of an electronic template that incorporates a list of items (known as RECAP-V0) thought to be associated with disease outcome according to previous qualitative work. Data collected will be linked to patient outcomes in highly secure environments. We will then use multivariate logistic regression analyses for model development and validation. Results Recruitment of participants started in October 2020. Initially, only the NWL CCGs and RCGP RSC arms were active. As of March 24, 2021, we have recruited a combined sample of 3827 participants in these two arms. CCAS and Doctaly joined the study in February 2021, with CCAS starting the recruitment process on March 15, 2021. The first part of the analysis (RECAP-V1 model development) is planned to start in April 2021 using the first half of the NWL CCGs and RCGP RSC combined data set. Posteriorly, the model will be validated with the rest of the NWL CCGs and RCGP RSC data as well as the CCAS and Doctaly data sets. The study was approved by the Research Ethics Committee on May 27, 2020 (Integrated Research Application System number: 283024, Research Ethics Committee reference number: 20/NW/0266) and badged as National Institute of Health Research Urgent Public Health Study on October 14, 2020. Conclusions We believe the validated RECAP-V1 early warning score will be a valuable tool for the assessment of severity in patients with suspected COVID-19 in the community, either in face-to-face or remote consultations, and will facilitate the timely escalation of treatment with the potential to improve patient outcomes. Trial Registration ISRCTN registry ISRCTN13953727; https://www.isrctn.com/ISRCTN13953727 International Registered Report Identifier (IRRID) DERR1-10.2196/29072

Background Glioblastoma is the commonest malignant brain tumour. Sarcopenia is associated with worse cancer survival, but manually quantifying muscle on imaging is time-consuming. We present a deep learning-based system for quantification of temporalis muscle, a surrogate for skeletal muscle mass, and assess its prognostic value in glioblastoma. Methods A neural network for temporalis segmentation was trained with 366 MRI head images from 132 patients from 4 different glioblastoma data sets and used to quantify muscle cross-sectional area (CSA). Association between temporalis CSA and survival was determined in 96 glioblastoma patients from internal and external data sets. Results The model achieved high segmentation accuracy (Dice coefficient 0.893). Median age was 55 and 58 years and 75.6 and 64.7% were males in the in-house and TCGA-GBM data sets, respectively. CSA was an independently significant predictor for survival in both the in-house and TCGA-GBM data sets (HR 0.464, 95% CI 0.218–0.988, p = 0.046; HR 0.466, 95% CI 0.235–0.925, p = 0.029, respectively). Conclusions Temporalis CSA is a prognostic marker in patients with glioblastoma, rapidly and accurately assessable with deep learning. We are the first to show that a head/neck muscle-derived sarcopenia metric generated using deep learning is associated with oncological outcomes and one of the first to show deep learning-based muscle quantification has prognostic value in cancer.