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Background: The COVID-19 pandemic necessitated the widespread roll-out of teleconsultations across primary care services in the UK. The media's depiction of remote consultations, especially regarding their safety, is not well established. These insights are important: newspapers' coverage of healthcare-related news can influence public perception, national policy, and clinicians' job satisfaction. Aim: To explore how the national newspapers in the UK depicted both the direct and indirect consequences of the remote-first approach on patient safety. Design and setting: We performed thematic analysis of newspaper articles that discussed patient safety in primary care teleconsultations, which were published between 21 January 2021 and 22 April 2022. Method: We identified relevant articles using the LexisNexis Academic UK database. We categorised data from these articles into codes before developing these into emergent themes through an iterative process. Results: Across the 57 articles identified, the main safety concern identified was missed and/or delayed diagnoses over tele-appointment(s), while isolated cases of inappropriate prescribing were also reported. The media reported that the transition to a remote-first approach reduced the accessibility to primary care appointments for some groups (especially patients with lower digital literacy or access) and heightened the burden on other healthcare services; in particular, there were reports of patient care being compromised across NHS emergency departments. Conclusion: The print media predominantly reported negative impacts of remote consultations on patient safety, particularly involving missed and/ or delayed diagnoses. Our work highlights the importance of further exploration into the safety of remote consultations, and the impact of erroneous media reporting on policies and policymakers. [ABSTRACT FROM AUTHOR]

Background and Aims Digital collection of patient-reported outcome measures [PROMs] is largely unexplored as a basis for follow-up for patients with ulcerative colitis [UC]. Our aim was to develop a model to predict the likelihood of escalation of therapy or intervention at an outpatient appointment that may be used to rationalize follow-up. Methods TrueColours-IBD is a web-based, real-time, remote monitoring software that allows longitudinal collection of ePROMs. Data for prediction modelling were derived from a Development Cohort, guided by the TRIPOD statement. Logistic regression modelling used ten candidate items to predict escalation of therapy or intervention. An Escalation of Therapy or Intervention [ETI] calculator was developed, and applied in a Validation Cohort at the same centre. Results The Development Cohort [ n  = 66] was recruited in 2016 and followed for 6 months [208 appointments]. From ten items, four significant predictors of ETI were identified: SCCAI, IBD Control-8, faecal calprotectin, and platelets. For practicality, a model with only SCCAI and IBD Control-8, both entered remotely by the patient, without the need for faecal calprotectin or blood tests was selected. Between 2018 and 2020, a Validation Cohort of 538 patients [1188 appointments] was examined. A 5% threshold on the ETI calculator correctly identified 343/388 [88%] escalations and 274/484 [57%] non-escalations. Conclusions A calculator based on digital, patient-entered data on symptoms and quality of life can predict whether a patient with UC requires escalation of therapy or intervention at an outpatient appointment. This may be used to streamline outpatient appointments for patients with UC. [ABSTRACT FROM AUTHOR]

Faced with increasingly strict carbon emission control, high-emission enterprises need scientific and rational management systems and methods to strengthen carbon emission reduction management. Among the many management systems and methods, the carbon budget has become an effective emission reduction management tool, allowing the planning of carbon emissions and emission reduction activities and rational arrangement of economic inputs. However, judging from the research status and business practices in China and abroad, there is no general carbon budget system to guide the development of carbon emission and emission reduction activities. Based on this background, this paper first attempts to construct an enterprise carbon budget system comprising four sub-budgets: carbon emission, carbon emission reduction and cost, carbon emission rights trading, and carbon emission reduction net profit/loss. It draws on the idea of interactive control to consider the impact of changes in carbon prices, energy prices, and policy guidelines on carbon emission reductions and losses. A carbon budget management system based on interactive control is then constructed and applied to China National Aviation Holding Air China Group (AC Aviation). The research results show that the carbon budget system based on interactive control can dynamically adjust carbon emission reduction behavior based on changes in carbon and energy prices to make carbon budgeting a more viable carbon reduction tool and institutional arrangement. [ABSTRACT FROM AUTHOR]

Common to all inflammatory arthritides, namely rheumatoid arthritis, psoriatic arthritis, axial spondyloarthritis, and juvenile idiopathic arthritis, is a potential for reduced mobility that manifests through joint pain, swelling, stiffness, and ultimately joint damage. Across these conditions, consensus has been reached on the need to capture outcomes related to mobility, such as functional capacity and physical activity, as core domains in randomised controlled trials. Existing endpoints within these core domains rely wholly on self-reported questionnaires that capture patients' perceptions of their symptoms and activities. These questionnaires are subjective, inherently vulnerable to recall bias, and do not capture the granularity of fluctuations over time. Several early adopters have integrated sensor-based digital health technology (DHT)-derived endpoints to measure physical function and activity in randomised controlled trials for conditions including Parkinson's disease, Duchenne's muscular dystrophy, chronic obstructive pulmonary disease, and heart failure. Despite these applications, there have been no sensor-based DHT-derived endpoints in clinical trials recruiting patients with inflammatory arthritis. Borrowing from case studies across medicine, we outline the opportunities and challenges in developing novel sensor-based DHT-derived endpoints that capture the symptoms and disease manifestations most relevant to patients with inflammatory arthritis., Competing Interests: Declaration of interests HY reports receiving a personal payment via the University of Oxford for developed software licenses. APC reports being employed by the University of Oxford at the time of submission and was partially funded by GSK, at the time of publication they are employed by Sanome and no company mentioned is involved or affiliated with this Review. JG reports being an unpaid volunteer member on the Board of Directors for the Digital Medicine Society and Coalition for Health AI. WGD reports receiving consultancy fees from Google unrelated to this work. AD is supported by the Wellcome Trust [223100/Z/21/Z], Novo Nordisk, Swiss Re, the British Heart Foundation Centre of Research Excellence (grant number RE/18/3/34214), and Health Data Research UK; AD's research group reports receiving funding from GSK; reports receiving personal payments via the University of Oxford for consulting services provided to Harvard University and the University of Wisconsin; reports receiving a personal payment via the University of Oxford for developed software licenses. LCC reports receiving research grants from AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, and UCB; reports receiving consulting fees from AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Gilead, Galapagos, Janssen, Moonlake, Novartis, Pfizer, and UCB; reports receiving payment for lectures and presentations from AbbVie, Amgen, Biogen, Celgene, Eli Lilly, Galapagos, Gilead, GSK, Janssen, Medac, Novartis, Pfizer, and UCB. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Introduction: Late presentation of multiple myeloma (MM) heightens the risk of complication risks, including end-organ damage. This study aimed to: 1) detail the diagnostic journey of MM patients, encompassing symptoms, initial diagnoses, and healthcare professionals met; 2) establish the median duration from symptom onset to MM diagnosis; and 3) examine factors linked to timely MM diagnosis within 12 weeks., Methods: A total of 300 adults self-reporting MM were analysed from the Rare and Undiagnosed Diseases cohort Study (RUDY). The RUDY study is a web-based platform, where participants provide dynamic consent and self-report their MM diagnosis and information about their diagnostic journey. This includes the estimated date of initial potential first symptoms, descriptions of these symptoms, the healthcare professionals they consulted, and other diagnoses received before the MM diagnosis. Descriptive statistics, combinatorial analyses and logistic regression analyses were used to describe and examine the diagnostic journey of individuals with MM., Results: Overall, 52% of the participants reported other diagnoses before MM diagnosis, with musculoskeletal disorders (47.8%), such as osteoporosis, costochondritis, or muscle strains, being the most common. The most prevalent initial reported symptom was back pain/vertebral fractures (47%), followed by chest/shoulder pain, including rib pain and fractures (20%), and fatigue/tiredness (19.7%). 40% of participants were diagnosed by direct referral from primary care to haematology without seeing other healthcare professionals whilst 60% consulted additional specialists before diagnosis. The median time from symptom onset to MM diagnosis was 4 months (IQR 2-10 months, range 0-172). Seeing an Allied Healthcare Professional such as a physiotherapist, chiropractor or an osteopath (OR = 0.25, 95% CI [0.12, 0.47], p <0.001), experiencing infection symptoms (OR = 0.32, 95% CI [0.13, 0.76], p = 0.013), and having chest or shoulder pain (OR = 0.45, 95% CI [0.23, 0.86], p = 0.020) were associated with a lower likelihood of being diagnosed with MM within 12 weeks. Older age (OR = 1.04, 95% CI [1.02, 1.07], p = 0.001) was associated with a higher likelihood of diagnosis within 12 weeks., Discussion: Developing resources for allied health professionals may improve early recognition of MM., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2023 Vijjhalwar, Song, Shrestha, Bowcock, Sanchez-Santos, Ramasamy and Javaid.)