Changing Autonomy in Operative Experience Through UK General Surgery Training:A National Cohort Study

Objectives:To determine the operative experience of UK general surgery trainees and assess the changing procedural supervision and acquisition of competency assessments through the course of training.Background Summary Data: Competency assessment is changing with concepts of trainee autonomy decisions (termed entrustment decisions) being introduced to surgical training.Methods: Data from the Intercollegiate Surgical Curriculum Programme (ISCP) and the eLogbook databases for all UK General Surgery trainees registered from 1st August 2007 who had completed training were used. Total and index procedures (IP) were counted and variation by year of training assessed. Recorded supervision codes and competency assessment outcomes for IPs were assessed by year of training.Results: We identified 311 trainees with complete data. Appendicectomy was the most frequently undertaken IP during first year of training (mean procedures (mp) = 26) and emergency laparotomy during final year of training (mp = 27). The proportion of all IPs recorded as unsupervised increased through training (

Time Out of General Surgery Specialty training in the UK:A National Database Study

ObjectiveGeneral surgery specialty training in the United Kingdom takes 6 years and allows trainees to take time out of training. Studies from the United States have highlighted an increasing trend for taking time out of surgical training for research. This study aimed to evaluate trends in time out of training and the impact on the duration of UK general surgical specialty training.Design, setting, and participantsA cohort study using routinely collected surgical training data from the Intercollegiate Surgical Curriculum Program database for General surgery trainees registered from August 1, 2007. Trainees were classified as Completed Training or In-Training. Out of training periods were identified and time in training calculated (both unadjusted and adjusted for out of training periods) with a predicted time in training for those In-Training.ResultsOf the trainees still In-Training (n = 994), a greater proportion had taken time out of training compared with those who had completed training (n = 360; 54.5% vs 45.9%, p < 0.01). A greater proportion of the In-Training group had undertaken a formal research period compared with the Completed Training group (35.1% vs 6.1%, p < 0.01). Total unadjusted training time in the Completed Training group was a median 6.0 (interquartile range 6.0-7.0) years compared with a predicted unadjusted training time in the In-Training group, with an out of training period recorded, of a median 8.0 (interquartile range 7.0-9.0) years.ConclusionsTrainees are increasingly taking time out of surgical training, particularly for research, with a subsequent increase in total time of training. This should be considered when redesigning surgical training programs and planning the future surgical workforce

Factors Associated with Attrition and Performance Throughout Surgical Training:A Systematic Review and Meta-Analysis

Background Attrition within surgical training is a challenge. In the USA, attrition rates are as high as 20-26%. The factors predicting attrition are not well known. The aim of this systematic review is to identify factors that influence attrition or performance during surgical training. Method The review was performed in line with PRISMA guidelines and registered with the Open Science Framework (OSF). Medline, EMBASE, PubMed and the Cochrane Central Register of Controlled Trials were searched for articles. Risk of bias was assessed using the Newcastle-Ottawa scale. Pooled estimates were calculated using random effects meta-analyses in STATA version 15 (Stata Corp Ltd). A sensitivity analysis was performed including only multi-institutional studies. Results The searches identified 3486 articles, of which 31 were included, comprising 17,407 residents. Fifteen studies were based on multi-institutional data and 16 on single-institutional data. Twenty-nine of the studies are based on US residents. The pooled estimate for overall attrition was 17% (95% CI 14-20%). Women had a significantly higher pooled attrition than men (24% vs 16%, p \ 0.001). Some studies reported Hispanic residents had a higher attrition rate than non-Hispanic residents. There was no increased risk of attrition with age, marital or parental status. Factors reported to affect performance were non-white ethnicity and faculty assessment of clinical performance. Childrearing was not associated with performance. Conclusion Female gender is associated with higher attrition in general surgical residency. Longitudinal studies of contemporary surgical cohorts are needed to investigate the complex multi-factorial reasons for failing to complete surgical residency

Frailty assessed by administrative tools and mortality in patients with pneumonia admitted to the hospital and ICU in Wales

Abstract The ideal method of identifying frailty is uncertain, and data on long-term outcomes is relatively limited. We examined frailty indices derived from population-scale linked data on Intensive Care Unit (ICU) and hospitalised non-ICU patients with pneumonia to elucidate the influence of frailty on mortality. Longitudinal cohort study between 2010–2018 using population-scale anonymised data linkage of healthcare records for adults admitted to hospital with pneumonia in Wales. Primary outcome was in-patient mortality. Odds Ratios (ORs [95% confidence interval]) for age, hospital frailty risk score (HFRS), electronic frailty index (eFI), Charlson comorbidity index (CCI), and social deprivation index were estimated using multivariate logistic regression models. The area under the receiver operating characteristic curve (AUC) was estimated to determine the best fitting models. Of the 107,188 patients, mean (SD) age was 72.6 (16.6) years, 50% were men. The models adjusted for the two frailty indices and the comorbidity index had an increased odds of in-patient mortality for individuals with an ICU admission (ORs for ICU admission in the eFI model 2.67 [2.55, 2.79], HFRS model 2.30 [2.20, 2.41], CCI model 2.62 [2.51, 2.75]). Models indicated advancing age, increased frailty and comorbidity were also associated with an increased odds of in-patient mortality (eFI, baseline fit, ORs: mild 1.09 [1.04, 1.13], moderate 1.13 [1.08, 1.18], severe 1.17 [1.10, 1.23]. HFRS, baseline low, ORs: intermediate 2.65 [2.55, 2.75], high 3.31 [3.17, 3.45]). CCI, baseline  10 2.50 [2.41, 2.60]). For predicting inpatient deaths, the CCI and HFRS based models were similar, however for longer term outcomes the CCI based model was superior. Frailty and comorbidity are significant risk factors for patients admitted to hospital with pneumonia. Frailty and comorbidity scores based on administrative data have only moderate ability to predict outcome

Deriving household composition using population-scale electronic health record data—A reproducible methodology

BackgroundPhysical housing and household composition have an important role in the lives of individuals and drive health and social outcomes, and inequalities. Most methods to understand housing composition are based on survey or census data, and there is currently no reproducible methodology for creating population-level household composition measures using linked administrative data.MethodsUsing existing, and more recent enhancements to the address-data linkage methods in the SAIL Databank using Residential Anonymised Linking Fields we linked individuals to properties using the anonymised Welsh Demographic Service data in the SAIL Databank. We defined households, household size, and household composition measures based on adult to child relationships, and age differences between residents to create relative age measures.ResultsTwo relative age-based algorithms were developed and returned similar results when applied to population and household-level data, describing household composition for 3.1 million individuals within 1.2 million households in Wales. Developed methods describe binary, and count level generational household composition measures.ConclusionsImproved residential anonymised linkage field methods in SAIL have led to improved property-level data linkage, allowing the design and application of household composition measures that assign individuals to shared residences and allow the description of household composition across Wales. The reproducible methods create longitudinal, household-level composition measures at a population-level using linked administrative data. Such measures are important to help understand more detail about an individual's home and area environment and how that may affect the health and wellbeing of the individual, other residents, and potentially into the wider community

Validating the QCOVID risk prediction algorithm for risk of mortality from COVID-19 in the adult population in Wales, UK.

IntroductionCOVID-19 risk prediction algorithms can be used to identify at-risk individuals from short-term serious adverse COVID-19 outcomes such as hospitalisation and death. It is important to validate these algorithms in different and diverse populations to help guide risk management decisions and target vaccination and treatment programs to the most vulnerable individuals in society.ObjectivesTo validate externally the QCOVID risk prediction algorithm that predicts mortality outcomes from COVID-19 in the adult population of Wales, UK.MethodsWe conducted a retrospective cohort study using routinely collected individual-level data held in the Secure Anonymised Information Linkage (SAIL) Databank. The cohort included individuals aged between 19 and 100 years, living in Wales on 24th January 2020, registered with a SAIL-providing general practice, and followed-up to death or study end (28th July 2020). Demographic, primary and secondary healthcare, and dispensing data were used to derive all the predictor variables used to develop the published QCOVID algorithm. Mortality data were used to define time to confirmed or suspected COVID-19 death. Performance metrics, including R2 values (explained variation), Brier scores, and measures of discrimination and calibration were calculated for two periods (24th January–30th April 2020 and 1st May–28th July 2020) to assess algorithm performance.Results1,956,760 individuals were included. 1,192 (0.06%) and 610 (0.03%) COVID-19 deaths occurred in the first and second time periods, respectively. The algorithms fitted the Welsh data and population well, explaining 68.8% (95% CI: 66.9-70.4) of the variation in time to death, Harrell’s C statistic: 0.929 (95% CI: 0.921-0.937) and D statistic: 3.036 (95% CI: 2.913-3.159) for males in the first period. Similar results were found for females and in the second time period for both sexes.ConclusionsThe QCOVID algorithm developed in England can be used for public health risk management for the adult Welsh population

Evidence generated from a realist synthesis of trials on educational weight loss interventions in type 2 diabetes mellitus

Background: Obesity and diabetes are major public health problems. Current approaches to weight loss show varying success. Complex community‐based interventions work through several interconnected stages. An individual’s actions in response to an intervention depend on many known and unknown factors, which vary among individuals.Aim: To conduct a realist synthesis to identify in which context, for whom, in what circumstances, and how weight loss interventions work in obese or overweight individuals with type 2 diabetes.Methods: A total of 49 trials identified during a systematic review were subsequently analysed using realist methodology. This iterative process involved hypothesis generation about how participants within a particular context respond to an intervention’s resources producing the outcomes. We used established behaviour change theory to look for repeating themes. Theory and ‘mechanisms’ were tested against the literature on what is shown to be effective. Where established theory was lacking, we discussed issues during discussion groups with individuals living with the condition to generate our own programme theories.Results: Mechanisms that were repeatedly identified included high‐frequency contact with those delivering the intervention, social support, education increasing awareness of diabetes‐related modifiable risk factors, motivational interviewing and counselling, goal‐setting, self‐monitoring and feedback and meal replacements. The central theme underlying successful mechanisms was personalizing each intervention component to the participants’ gender, culture and family setting.Conclusion: This is the first comprehensive realist synthesis in this field. Our findings suggest that, for weight loss interventions to be successful in those with diabetes, they must be personalized to the individual and their specific context

In vivo vitamin C supplementation increases phosphoinositol transfer protein expression in peripheral blood mononuclear cells from healthy individuals

Ascorbate can act as both a reducing and oxidising agent in vitro depending on its environment. It can modulate the intracellular redox environment of cells and therefore is predicted to modulate thiol-dependent cell signalling and gene expression pathways. Using proteomic analysis of vitamin C-treated T cells in vitro, we have previously reported changes in expression of five functional protein groups associated with signalling, carbohydrate metabolism, apoptosis, transcription and immune function. The increased expression of the signalling molecule phosphatidylinositol transfer protein (PITP) was also confirmed using Western blotting. Herein, we have compared protein changes elicited by ascorbate in vitro, with the effect of ascorbate on plasma potassium levels, on peripheral blood mononuclear cell (PBMC) apoptosis and PITP expression, in patients supplemented with vitamin C (0-2 g/d) for up to 10 weeks to investigate whether in vitro model systems are predictive of in vivo effects. PITP varied in expression widely between subjects at all time-points analysed but was increased by supplementation with 2 g ascorbate/d after 5 and 10 weeks. No effects on plasma potassium levels were observed in supplemented subjects despite a reduction of K+ channel proteins in ascorbate-treated T cells in vitro. Similarly, no effect of vitamin C supplementation on PBMC apoptosis was observed, whilst ascorbate decreased expression of caspase 3 recruitment domain protein in vitro. These data provide one of the first demonstrations that proteomics may be valuable in developing predictive markers of nutrient effects in vivo and may identify novel pathways for studying mechanisms of action in vivo