Pharmacological interventions for early-stage frozen shoulder: a systematic review and network meta-analysis.

OBJECTIVES: To evaluate the efficacy of pharmacological interventions for treating early-stage, pain predominant, adhesive capsulitis, also known as frozen shoulder. METHODS: We performed a systematic review in accordance with PRSIMA guidelines. Searches were conducted on PUBMED, EMBASE and Cochrane Central Register of Controlled Trials on the 24th of February 2022. Outcomes were shoulder pain, shoulder function and range of movement. Synthesis involved both qualitative analysis for all studies and pairwise meta-analyses followed by a network meta-analysis for randomised controlled trials (RCTs). RESULTS: A total of 3,252 articles were found, of which 31 met inclusion criteria, and 22 of these were RCTs. Intraarticular (IA) injection of corticosteroids (8 RCTS, 340 participants) and IA injection of platelet-rich plasma (PRP) (3 RCTs, 177 participants) showed benefit at 12 weeks compared with physical therapy in terms of shoulder pain and function, while oral non-steroidal anti-inflammatories (NSAIDs) (2 RCTs, 44 participants) and IA injection of hyaluronate (2 RCTs, 42 participants) did not show a benefit. Only IA PRP showed benefit over physical therapy for shoulder range of movement. CONCLUSION: These results shows that IA corticosteroids IA PRP injections are beneficial for early-stage frozen shoulder. These findings should be appraised with care considering the risk of bias, heterogeneity, and inconsistency of the included studies. We believe that research focused on early interventions for frozen shoulder could improve patient outcomes and lead to cost-savings derived from avoiding long-term disability. Further well-designed studies comparing with standardised physical therapy or placebo are required to improve evidence to guide management.

Natural language processing to automate a web-based model of care and modernize skin cancer multidisciplinary team meetings.

BACKGROUND: Cancer multidisciplinary team (MDT) meetings are under intense pressure to reform given the rapidly rising incidence of cancer and national mandates for protocolized streaming of cases. The aim of this study was to validate a natural language processing (NLP)-based web platform to automate evidence-based MDT decisions for skin cancer with basal cell carcinoma as a use case. METHODS: A novel and validated NLP information extraction model was used to extract perioperative tumour and surgical factors from histopathology reports. A web application with a bespoke application programming interface used data from this model to provide an automated clinical decision support system, mapped to national guidelines and generating a patient letter to communicate ongoing management. Performance was assessed against retrospectively derived recommendations by two independent and blinded expert clinicians. RESULTS: There were 893 patients (1045 lesions) used to internally validate the model. High accuracy was observed when compared against human predictions, with an overall value of 0.92. Across all classifiers the virtual skin MDT was highly specific (0.96), while sensitivity was lower (0.72). CONCLUSION: This study demonstrates the feasibility of a fully automated, virtual, web-based service model to host the skin MDT with good system performance. This platform could be used to support clinical decision-making during MDTs as 'human in the loop' approach to aid protocolized streaming. Future prospective studies are needed to validate the model in tumour types where guidelines are more complex.

Service implications of the revised 2022 National Institute for Health and Care Excellence (NICE) follow-up guidelines for stage IA-IIC melanoma.

BACKGROUND: The 2022 National Institute for Health and Care Excellence melanoma guideline update made significant changes to follow-up. The aim of this study was to assess the impact these changes will have on a national melanoma cohort over a 5-year follow-up interval. METHODS: Anonymized, individual-level, population-scale, linkable primary and secondary care National Health Service data for an 18-year interval (2000-2018) in Wales, UK were analysed. These data were used to predict the number of patients over a 10-year interval (2020-2030) that would be diagnosed with melanoma. Follow-up schedules for the 2015 and 2022 National Institute for Health and Care Excellence melanoma guidelines were then used to calculate the number of clinician-led appointments, the number of radiological investigations, and the total healthcare cost between 2025 and 2030, corresponding to a 5-year patient follow-up interval, for those with stage IA-IIC melanoma. RESULTS: Between 2025 and 2030 it is predicted that implementation of the 2022 guidelines would lead to 21 122 (range 19 194-23 083) fewer clinician-led appointments for patients with stage IA-IIC melanoma. However, there would be a significant increase in the number of radiological investigations (7812; range 7444-8189). These changes would lead to a €2.74 million (€1.87 million-€3.61 million) reduction in the total cost of follow-up over the interval 2025-2030. CONCLUSION: Melanoma follow-up guideline changes will result in a substantial reduction in the number of clinical follow-up appointments, but a significant additional burden to radiological services. The overall cost of follow-up at a national level will be reduced.

Prevalence and odds of anxiety and depression in cutaneous malignant melanoma: a proportional meta-analysis and regression.

BACKGROUND: The psychological burden of cutaneous malignant melanoma (CM) is all-encompassing, affecting treatment adherence, recurrence and mortality. However, the prevalence and risk factors of anxiety and depression in CM remain unclear. OBJECTIVES: To establish a benchmark pooled prevalence of anxiety and depression in CM, to provide magnitudes of association for clinical, therapeutic and demographic correlates, and to elucidate temporal trends in anxiety and depression from the time of diagnosis. METHODS: This review followed the MOOSE guidelines. MEDLINE, Embase, PsychINFO, Web of Science and the Cochrane Library were queried from database inception to 24 August 2023. Study selection, data extraction and quality assessment were performed by two independent authors, utilizing both the Joanna Briggs Institute (JBI) and National Institutes of Health risk-of-bias tools for the latter. The GRADE approach was used to rate the certainty of evidence. Prevalence rates, 95% confidence intervals (CIs) and prediction intervals (PIs) were derived using a random-effects model and estimating between- and within-study variance. RESULTS: Nine longitudinal and 29 cross-sectional studies were included (7995 patients). Based on the JBI and NIH tools, respectively, quality assessment found 20 and 17 to be at low risk of bias, 12 and 15 to be at moderate risk and 6 and 5 to be at high risk of bias. The prevalence of anxiety [30.6% (95% CI 24.6-37.0; PI 18-47%)] and depression [18.4% (95% CI 13.4-23.9; PI 10-33%)] peaked during treatment, declining to pretreatment levels after 1 year [anxiety: 48% vs. 20% (P = 0.005); depression: 28% vs. 13% (P = 0.03)]. Female sex [odds ratio (OR) 1.8, 95% CI 1.4-2.3; P < 0.001], age < 60 years (OR 1.5, 95% CI 1.2-2.0; P = 0.002) and low educational level (OR 1.5, 95% CI 1.2-2.0; P < 0.001) were likely to result in a large increase in the odds of anxiety. Depression was 12.3% higher in those with stage IV vs. those with stage I CM (P = 0.05). Relative to immune checkpoint inhibition, the rates of depression were 22% (P = 0.002) and 34% (P < 0.001) higher among patients with advanced-stage CM receiving interferon-α and chemotherapy, respectively. A significant reduction in self-reported depression scores was demonstrated over time (P = 0.003). CONCLUSIONS: Notably, anxiety and depression in CM affect women, those younger than 60 years of age and the less educated, with up to 80% higher odds of anxiety in these groups. Anxiety and depression surge during chemotherapy and interferon treatment, especially in advanced CM. Our findings facilitate risk stratification and underscore the need for multidisciplinary vigilance.

Melanoma is a serious type of skin cancer that is becoming more prevalent, particularly in people with lighter skin. The UK-based ReconRegen research group conducted a study to understand the psychological impact of melanoma on people, focusing on anxiety and depression. To do this, a systematic review approach was used to analyse data from existing studies and gather a comprehensive perspective. The study discovered that 30% of people with melanoma are affected by anxiety and 18% by depression, significantly higher than the general population. Key risk factors for anxiety included being female, being younger than 60 years of age and having lower educational attainment. Women are 1.8 times more likely to experience anxiety than men, those under 60 years of age are 1.5 times more likely to experience it and individuals with lower educational levels are also 1.5 times more likely to experience anxiety. Findings showed that anxiety and depression levels peaked during treatment phases, especially in people undergoing chemotherapy and immunotherapy. This highlights the need for targeted mental health support during these treatment periods. The findings advocate for mental health considerations in melanoma care, suggesting regular mental health assessments, particularly for high-risk groups and during intense treatment phases. Highlighting the importance of a holistic treatment approach, the study suggests that future research should include long-term studies to understand the chronic impacts of anxiety and depression. Improved clarity and detail in research reporting are essential for developing effective mental health support for people with melanoma, enhancing overall patient care by addressing both physical and emotional health needs.

The "Flapbot": A Global Perspective on the Validity and Usability of a Flap Monitoring Chatbot.

BACKGROUND: The Flapbot chatbot assists in free-flap monitoring, emphasizing accessibility, user-friendliness, and global reliability. This study assesses Flapbot's worldwide validity and usability and uses qualitative analysis to identify areas for future enhancement. METHODS: Flapbot, built on Google's DialogFlow, was evaluated by international plastic surgeons. Invitations were sent to the International Lower Limb Reconstruction Collaborative (INTELLECT), International Confederation of Plastic Surgery Societies (ICOPLAST), and the International Microsurgery Club. Out of the 42 surgeons who agreed to participate, 21 tested the Flapbot and completed an online survey on its validity and usability. The survey had 13 validity items and 10 usability items. Data analysis involved computing the individual content validity index (I-CVI) and scale-wide content validity index (S-CVI) for validity, and the system usability score (SUS) for usability. Thematic analysis distilled free-text responses to identify key themes. RESULTS: Nine of 13 items had an I-CVI over 0.78, denoting significant relevance. The S-CVI score stood at 0.82, indicating high relevance. The SUS score was 68, representing average usability. Themes highlighted issues with the current model, development suggestions, and surgeons' concerns regarding growing reliance on digital tools in health care. CONCLUSION: Flapbot is a promising digital aid for free-flap monitoring. While it showcases notable validity and usability, improvements in functionality, usability, and accessibility are needed for broader global use.

Can Large Language Models Generate Outpatient Clinic Letters at First Consultation That Incorporate Complication Profiles From UK and USA Aesthetic Plastic Surgery Associations?

The importance of written communication between clinicians and patients, especially in the wake of the Supreme Court case of Montgomery vs Lanarkshire, has led to a shift toward patient-centric care in the United Kingdom. This study investigates the use of large language models (LLMs) like ChatGPT and Google Bard in enhancing clinic letters with gold-standard complication profiles, aiming to improve patients' understanding and save clinicians' time in aesthetic plastic surgery. The aim of this study is to assess the effectiveness of LLMs in integrating complication profiles from authoritative sources into clinic letters, thus enhancing patient comprehension and clinician efficiency in aesthetic plastic surgery. Seven widely performed aesthetic procedures were chosen, and complication profiles were sourced from the British Association of Aesthetic Plastic Surgeons (BAAPS) and the American Society of Plastic Surgeons (ASPS). We evaluated the proficiency of the ChatGPT4, ChatGPT3.5, and Google Bard in generating clinic letters which incorporated complication profiles from online resources. These letters were assessed for readability using an online tool, targeting a recommended sixth-grade reading level. ChatGPT4 achieved the highest compliance in integrating complication profiles from BAAPS and ASPS websites, with average readability grades between eighth and ninth. ChatGPT3.5 and Google Bard showed lower compliance, particularly when accessing paywalled content like the ASPS Informed Consent Bundle. In conclusion, LLMs, particularly ChatGPT4, show promise in enhancing patient communications in aesthetic plastic surgery by effectively incorporating standard complication profiles into clinic letters. This aids in informed decision making and time saving for clinicians. However, the study underscores the need for improvements in data accessibility, search capabilities, and ethical considerations for optimal LLM integration into healthcare communications. Future enhancements should focus on better interpretation of inaccessible formats and a Human in the Loop approach to combine Artifical Intelligence capabilities with clinician expertise.