Midland Regional Hospital, Tullamore

Abstract Background/Aims: Background Axial Spondyloarthritis (AxSpA) is a chronic inflammatory rheumatic disease affecting the axial skeleton that can cause both extra musculoskeletal (EMMs) and extra articular manifestations (EAMs) (Wright et al 2020). Nurse-led care (NLC) has demonstrated non-inferiority to consultant-led care in Rheumatoid Arthritis patient cohorts for over a decade (Ndosi et al, 2014, Lopatina et al, 2021), with a paucity of data in comparable inflammatory diseases. Treatment with non-steroidal anti-inflammatory drugs (NSAIDs), physiotherapy, and biologic medications have been the standard of care. While ASAS guidelines recommend multidisciplinary care, nursing input is not specifically referred to in this guidance (Ramiro et al, 2023), however the EULAR recommendations for role of the nurse in management of chronic inflammatory arthritis advocates for shared decision making between nurse and patient, and timely access to nursing care (Bech et al, 2020). Aim To demonstrate efficacy of NLC for AxSpA patients through year 1 post diagnosis; by demonstrating reduction in patient reported outcome measures/ NSAID use and maximising treatment persistence. Methods Following confirmation of AxSpA diagnosis, patients were referred to join the NLC pathway. Across 3/4 appointments, outcome measures were collected and patients received education about their diagnosis and management plan, trial of minimum 1 NSAID and/or biologic initiation/ switch where appropriate, EMMs/ EAMs assessment, comorbidity screening, lifestyle (including family planning) and vaccine advice to reduce infection risk and medication reconciliation. Patients were referred for physiotherapy at their closest centre to home as per Slaintecare recommendations, and if appropriate were encouraged to stop smoking. Results From January-December 2024, 60 patients enrolled with an average age at diagnosis of 38 years. 60% (36) of patients were male, and of the sixty patients, 77% (46) attended minimum 3 visits. NSAID use reduced from 50% regular use at visit 1 to 68% rare use by visit 3. Biologic use was maintained at 80% across visit 2 and 3, with 70% (42) same biologic persistence achieved. 53% (32) confirmed physiotherapy review by visit 2. Average outcome measures at each visit are as follows; Visit 1 BASDAI 4.53, BASFI 3.71, BAS-G 5.41, BASMI 2.92; Visit 2 BASDAI 3.55, BASFI 2.72, BAS-G 4.26, BASMI 2.55; and Visit 3 BASDAI 3.50, BASFI 2.80, BAS-G 3.57, BASMI 2.30. Further analysis is ongoing. Conclusion NLC has been shown to have a positive impact on a number of relevant patient outcomes in this cohort. Challenges included maintaining dedicated clinic time which is essential to meeting review deadlines, and changes have been made locally while data collection is ongoing. While further research is needed to confirm non-inferiority to consultant-led care, we propose that AxSpA patients are a suitable cohort for NLC. Disclosure E. Shinners: Honoraria; ES has received honaria from Roche, Pfizer, Johnson & Johnson. Grants/research support; ES has received unrestricted educational grant from Johnson & Johnson. A. Gorman: None.

Artificial Intelligence (AI) driven documentation systems are positioned to enhance documentation efficiency and reduce documentation burden in the healthcare setting. The administrative burden associated with clinical documentation has been identified as a major contributor to health care professional (HCP) burnout. The current systematic review aims to evaluate the efficiency, quality, and stakeholder opinion regarding the use of AI-driven documentation systems. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines a comprehensive search was conducted across PubMed, Embase and Cochrane library. Two independent reviewers applied inclusion and exclusion criteria to identify eligible studies. Details of AI technology, document type, document quality and stakeholder experience were extracted. The review included 11 studies. All included studies utilised Chat generated pretrained transformer (Chat GPT, Open AI, CA, USA) or an ambient AI technology. Both forms of AI demonstrated significant potential to improve documentation efficiency. Despite efficiency gains, the quality of AI-generated documentation varied across studies. The heterogeneity of methods utilised to assess document quality influenced interpretation of results. HCP opinion was generally positive, users highlighted ease of use and reduced task load as primary benefits. However, HCPs also expressed concerns about the reliability and validity of AI-generated documentation. Chat GPT and ambient AI show promise in enhancing the efficiency and quality of clinical documentation. While the efficiency benefits are clear, the challenges associated with accuracy and consistency need to be addressed. HCP experiences indicate a cautious optimism towards AI integration, however reliability will depend on continued refinement and validation of the technology.

Background: Patients requiring lower limb immobilization after injury have an increased venous thromboembolism (VTE) risk. The extent of this risk in published studies varies. The Thrombosis Risk Prediction for Patients with Cast Immobilization (TRiP[cast]) model quantifies VTE risk using clinical parameters. Delineating low-risk from high-risk patients remains challenging. Objectives: Determine the 90-day incidence of symptomatic VTE following temporary lower limb immobilization after injury in an unselected cohort. Prospectively collect data on risk factors, including those incorporated in the TRiP(cast) model, to calculate TRiP(cast) scores. Methods: TILLIRI is a multicenter, pragmatic, observational cohort study including 10 sites within the Irish Network for VTE Research. Patients aged >= 18 years with an immobilized injured lower limb were included. Twenty-one clinical variables were collected at presentation. Thromboprophylaxis was prescribed according to clinical gestalt. Patients were followed up at 90 days to determine if VTE occurred. Results: Between November 2018 and February 2023, 1242 patients were recruited. Follow-up was complete for 1199 patients (96.5%). Forty-three patients (3.5%) were lost to follow-up. Forty-four (3.6%) patients and 125 (10%) patients were prescribed anticoagulation and aspirin, respectively. Twenty-one patients receiving regular anticoagulation were removed from the final analysis. VTE incidence at 90-day follow-up was 6/1179 (0.51%; 95% CI, 0.1%-0.92%). TRiP(cast) scores were calculated for 1176/1221 patients. A total of 846 patients (71.9%) had a TRiP(cast) score < 7, received no prophylaxis, and had no VTE. Conclusion: TILLIRI indicates a low VTE incidence in an unselected cohort following lower limb immobilization with low rates of prophylaxis use. The proportion of patients with low TRiP(cast) scores and no symptomatic VTE suggests that thromboprophylaxis may be avoided in patients with TRiP(cast) scores < 7 with a low 90-day VTE risk.

Generative artificial intelligence (AI) models are increasingly used to create patient education materials (PEM), offering on-demand health information. These tools hold the potential to democratise access to medical information, but concerns remain regarding the quality, readability, and reliability of AI-generated PEM. Spinal fusion surgery, a complex procedure, necessitates clear, accurate educational materials to support informed decision-making. Despite their promise, the capacity of AI models to meet health literacy needs remains underexplored. This study aimed to evaluate and compare the readability and quality of PEM on spinal fusion surgery sourced from institution and society websites and those generated by three AI models (ChatGPT, Gemini, and Co-Pilot). Patient information on spinal fusion surgery was sourced from the British Association of Spinal Surgeons (BASS), American Academy of Orthopaedic Surgeons (AAOS), Cleveland Clinic, Mayo Clinic, and John Hopkins websites, and generated by AI models (Chat GPT, Co-Pilot Gemini) using a standard prompt on 15/12/24. Patient Education Materials Assessment Tool (PEMAT), JAMA benchmark criteria, and the DISCERN tool assessed quality. Readability was evaluated with the Flesch-Kincaid Grade Level (FKGL), Reading Ease (FKRE), and Gunning Fog Index (GFI). Mean quality and readability outcome measures of AI generated and institution or society sourced PEM were compared. Post Bonferroni correction, statistical significance was set at P < .0125 for quality and follow-up prompting assessments, and P < .0167 for readability assessments. Society and institution sourced PEM outperformed AI-generated content in readability and quality. Website-sourced materials scored significantly higher PEMAT (77.1

PurposeTiming of emergent surgery for lumbar disc herniations, such as cauda equina syndrome, remains a challenging aspect of best medical practice in spine surgery, with most authors recommending decompressive surgery as soon as feasible. The literature conflicts on the merit and potential risk of emergent, "out-of-hours" decompression. Our aim was to evaluate if there is a higher complication rate associated with out-of-hours decompressive surgery for emergent lumbar disc herniations.MethodsThis was a single-centre, retrospective cohort study in a tertiary referral spinal unit of patients who underwent emergency decompressive surgery for acute disc herniation. Demographic and clinical data, surgery type and level, timing, primary operator, intra-operative complications and revision surgery at 6 weeks and 1 year were recorded. Out-of-hours operating was defined as occurring between 20:00 and 08:00. Multivariable analysis was performed by multiple logistic regression. Statistical analysis was performed with R, version 4.4.1.ResultsThere were 344 sequential, emergency decompressions for acute disc herniation performed during the study period. The mean age was 46 years (SD: 14) and 53% were female. Of cases, 129 (38%) were performed out-of-hours, compared to 146 (42%) during normal working hours and 69 (20%) during daylight weekend hours. There were 35 (10%) intra-operative complications; while 29 (8%) patients required re-operation within 6 weeks. On multiple logistic regression, out-of-hours surgery was not associated with either frequency of intra-operative complications or re-operations at 6 weeks. There were no independent predictors of intra-operative complication or revision surgery at 6 weeks or 1 year among age, sex, indication for surgery or grade of primary operator.ConclusionIn this study, out-of-hours emergency decompression for acute lumbar disc herniation is not associated with intra-operative complication or revision surgery at one year.