Royal Liverpool and Broadgreen University Hospitals NHS Trust

Objectives Higher specialty trainees are expected to achieve clinical and non-clinical skills during training in preparation for a consultant role. However, evidence from many specialties from different countries suggests that new consultants are less prepared in non-clinical skills. The transition from trainee to a consultant phase can be challenging. The study aims to identify if new UK Palliative Medicine consultants, within 5 years of their appointment, feel prepared in clinical and non-clinical skills after completing specialty training and understand the support available for them.Method An online survey, designed using previous literature, was distributed via the Association for Palliative Medicine email and social media. Five-point Likert scales and drop-down options to record preparedness were used. Ethics approval was obtained.Results Forty-four participants from different UK regions completed the survey; 80% were female. The majority felt very/extremely prepared in audit (84%), clinical skills (71%), interaction with colleagues (70%). Majority moderate preparation was human resources (50%), organisation structure (68%) and leadership (52%). Most were not at all or slightly prepared in financial management (70%) and in complaint management (43%). The majority (75%) reported that departmental colleagues gave the most support in stressful situations but almost 49% did not have formal support.Conclusion New palliative medicine consultants require support with some non-clinical roles such as management of complaints and finances. This is consistent with findings from other specialties. New consultants would benefit from formal support. Future research could focus on how trainees could be supported to gain more experience in non-clinical domains.

OBJECTIVE:To characterise contemporary practice patterns in female radical cystectomy (RC) across the UK and Ireland, focusing on preoperative counselling, operative strategies, and postoperative care. SUBJECTS AND METHODS:A 36-item survey was distributed to consultant urologists performing RC, identified via the British Association of Urological Surgeons (BAUS) and Cancer Alliances. The questionnaire addressed surgeon demographics, preoperative assessment and counselling, operative decision-making including organ- and nerve-sparing techniques, and survivorship care. Responses were analysed descriptively; group comparisons were made using the Wilcoxon rank-sum and Fisher's exact tests. RESULTS:A total of 64 surgeons responded (56.1% [64/114]), representing 41 cystectomy centres (70.7% [41/58]). Preoperative assessment of sexual activity (68.8%) and menopausal status (78.1%) was common, whereas sexual orientation (15.6%) and prolapse (26.6%) were rarely addressed. Female surgeons were significantly more likely to enquire about menopausal status (P = 0.025). Counselling on sexual dysfunction (98.4%) and vaginal shortening (96.9%) was routine, but other complications, including prolapse (68.8%), menopause (82.8%), or fistula (6.3%), were inconsistently discussed. Organ-sparing practice varied: 28.1% rarely or never performed organ preservation, citing oncological concerns. High-volume centres were more likely to offer organ-sparing RC (P = 0.013). Over half reported inadequate access to female-specific rehabilitation services, with most centres lacking formal pathways for vaginal complications. CONCLUSIONS:Female RC practice across the UK and Ireland is heterogeneous, with clear gaps in preoperative counselling, uptake of organ-sparing techniques, and survivorship care. There is an urgent need for standardised, evidence-based pathways and consensus guidance to optimise outcomes for female patients.

A survey of UK and Irish healthcare professionals was distributed via the UK Dermatology Clinical Trials Network, British Society for Paediatric and Adolescent Dermatologists, Irish Association of Dermatologists and other regional groups. The aim was to understand how healthcare professionals prescribe spironolactone for female patients, with a particular focus on those aged ≤ 18 years, as well as concerns regarding side effects and thoughts about a future clinical trial. A total of 116 responses were received from healthcare professionals, including dermatologists, dermatology nurses, paediatricians, general practitioners and pharmacists. The results showed that there is varied clinical practice and confidence among healthcare professionals treating this population with spironolactone, with the main safety concerns being around hormonal implications, future pregnancies and lack of long-term data.

INTRODUCTION:There is an unmet need for simple tools to predict development of hepatic decompensation among patients with compensated cirrhosis. We applied machine learning to several international Data sets to develop and validate a straightforward predictive model of decompensation. METHODS:We used routinely available clinical and laboratory data from 575 patients with compensated cirrhosis from the training cohorts in Nottingham (United Kingdom) and Modena (Italy), with a median follow-up of 4 years. Based on these data, we developed a predictive model using a random forest classifier and validated it across independent international populations involving over 2,100 patients from Dublin (Ireland), Menoufia (Egypt), Leeds (UK), and Ogaki (Japan). RESULTS:In the training cohorts, 22% of patients developed liver decompensation. Using machine learning, we developed risk of decompensation in cirrhosis (RODIC), a well-calibrated model based on albumin, bilirubin, and the Fib-4 value (area under the receiver operating characteristic curve = 0.86; weighted F1 score = 0.82) which predicts the risk of decompensation within 3 years (access free of charge at: https://antonkaly.pythonanywhere.com/predict ). RODIC showed strong performance across all validation sets, with area under the receiver operating characteristic curve scores ranging from 0.67 to 0.80 and weighted F1 scores from 0.70 to 0.81. Moreover, the model was effective regardless of cirrhosis etiology. For hepatitis C virus-positive patients, RODIC remained reliable irrespective of whether they achieved sustained virologic response. DISCUSSION:Our validated machine learning model based on readily available clinical, and laboratory features accurately quantitates the risk of liver decompensation in patients with compensated hepatic cirrhosis.