No abstract

Background: Medical schools differ, particularly in their teaching, but it is unclear whether such differences matter, although influential claims are often made. The Medical School Differences (MedDifs) study brings together a wide range of measures of UK medical schools, including postgraduate performance, fitness to practise issues, specialty choice, preparedness, satisfaction, teaching styles, entry criteria and institutional factors. Method: Aggregated data were collected for 50 measures across 29 UK medical schools. Data include institutional history (e.g. rate of production of hospital and GP specialists in the past), curricular influences (e.g.

Background: What subjects UK medical schools teach, what ways they teach subjects, and how much they teach those subjects is unclear. Whether teaching differences matter is a separate, important question. This study provides a detailed picture of timetabled undergraduate teaching activity at 25 UK medical schools, particularly in relation to problem-based learning (PBL). Method: The Analysis of Teaching of Medical Schools (AToMS) survey used detailed timetables provided by 25 schools with standard 5-year courses. Timetabled teaching events were coded in terms of course year, duration, teaching format, and teaching content. Ten schools used PBL. Teaching times from timetables were validated against two other studies that had assessed GP teaching and lecture, seminar, and tutorial times. Results: A total of 47,258 timetabled teaching events in the academic year 2014/2015 were analysed, including SSCs (student-selected components) and elective studies. A typical UK medical student receives 3960 timetabled hours of teaching during their 5-year course. There was a clear difference between the initial 2 years which mostly contained basic medical science content and the later 3 years which mostly consisted of clinical teaching, although some clinical teaching occurs in the first 2 years. Medical schools differed in duration, format, and content of teaching. Two main factors underlay most of the variation between schools, Traditional vs PBL teaching and Structured vs Unstructured teaching. A curriculum map comparing medical schools was constructed using those factors. PBL schools differed on a number of measures, having more PBL teaching time, fewer lectures, more GP teaching, less surgery, less formal teaching of basic science, and more sessions with unspecified content. Discussion: UK medical schools differ in both format and content of teaching. PBL and non-PBL schools clearly differ, albeit with substantial variation within groups, and overlap in the middle. The important question of whether differences in teaching matter in terms of outcomes is analysed in a companion study (MedDifs) which examines how teaching differences relate to university infrastructure, entry requirements, student perceptions, and outcomes in Foundation Programme and postgraduate training.

Objectives The continuous supply of personal protective equipment (PPE) in the National Health Service (NHS) is paramount to reduce transmission of COVID-19 to patients, public, and staff. Methods A 16-question survey was created to assess the availability and personal thoughts of healthcare professionals regarding PPE supply in England. The survey was distributed via social media (Facebook© and Twitter©) to UK COVID-19 healthcare professional groups, with responses collected over 3 weeks in March 2020 during the beginning of the pandemic. Results A total of 121 responses from physicians in 35 different hospitals were collected (105 inpatient wards, 16 from intensive care units). In inpatient wards, eye and face protection were unavailable to 19% (20/105). Fluid-resistant surgical masks were available to 97% (102/105) whereas filtering facepiece class 3 (FFP3) respirator for 53% (56/105) of respondents. Gloves were accessible for all respondents (100%). Body protection was available primarily as a plastic apron 84% (88/105). All of respondents working in intensive care had access to full-body PPE, except FFP3 respirators (available in 88%, 14/16). PPE is ‘Always’ available for 30% (36/121) of all respondents. There was a statistically significant difference between London and non-London respondents that ‘Always’ had PPE available (44 versus 19%, P = 0.003). Conclusions Our survey demonstrated an overall lack of PPE volume supply in the UK hospitals during March 2020, demonstrating a lack of preparedness for a pandemic. PPE was more readily available in London which was the epicentre of the outbreak. Eye and full body protection are in most lack of supply.

This study evaluates the current clinical evidence of Negative Pressure Wound Therapy with Instillation and dwell time (NPWTi‐d) to establish its clinical application and efficacy. MEDLINE, EMBASE, and CENTRAL databases were searched from 1946 to July 2019 for studies reporting clinical outcomes on wounds treated with NPWTi‐d. The primary outcome was proportion of wounds with complete healing. The secondary outcomes were mean time for healing, NPWTi‐d settings, cost, length of stay, and adverse events. Thirteen articles were included with a total of 624 wounds in 542 patients involving wounds of various aetiology. The pooled proportion of wound that achieved complete healing was 93.65% (95%CI: 84.02‐99.04). Normal saline was the most commonly used instillation solution with the mean dwell time of 14.23 minutes (95%CI: 10.88‐17.59) and instillation cycle every 4.17 ± 2.32 hourly. The mean therapy duration was 10.69 days (95%CI: 10.46‐10.91) with daily cost of $194.80. The mean hospital stay was 18.1 days (95%CI: 17.20‐19.00). There were no severe adverse effects reported. NPWTi‐d is an adjuntive therapy to aid complete healing of the vast majority of wounds. However, the current data are limited by the lack of level 1 evidence.

First described by Polish Neurologist Łucja Frey in 1923, Frey’s syndrome (FS), or auriculotemporal syndrome, is a rare condition characterised by gustatory sweating, typically encountered as sequelae following invasive head and neck surgery. The pathophysiology of FS can be described by aberrant reinnervation of postganglionic parasympathetic neurons to the surrounding denervated sweat glands and cutaneous blood vessels. Multiple invasive procedures have been associated with FS ranging from salivary gland surgery to burn reconstruction and thoracoscopic sympathectomies. Rarely, FS can be secondary to trauma or non-surgical aetiologies, including diabetes and infection. Physical symptoms vary based on the severity and surface area affected by FS and range from mild symptoms to severe psychosocial morbidity for patients. Surgeons operating in the head and neck, including otolaryngologists, maxillofacial surgeons, and plastic surgeons, should be aware of this potential complication and be up to date with diagnosis and treatment strategies for FS. This review article summarises the literature relating to FS focusing on its aetiologies, symptomatology, prevention, and available treatments, aiming to provide an up-to-date review of this condition for surgeons operating in the head and neck region. Although various treatment options have been suggested, these are often limited to topical agents that require life-long administration for symptom control. Further research is recommended to identify the optimal treatment for this condition and the role of surgery as a treatment for severe or refractory cases.

BackgroundIn the absence of clear guidelines for facial aesthetic surgery, most surgeons rely on expert intuitive judgement when planning aesthetic and reconstructive surgery. One of the most famous theories regarding “ideal” facial proportions is that of the golden proportion. However, there are conflicting opinions as to whether it can be used to assess facial attractiveness. The aim of this investigation was to assess facial ratios of professional black models and to compare the ratios with the golden proportion.MethodsForty photographs of male and female professional black models were collected. Observers were asked to assign a score from 1 to 10 (1 = not very attractive, 10 = very attractive). A total of 287 responses were analysed for grading behaviour according to various demographic factors by two groups of observers. The best graded photographs were compared with the least well-graded photographs to identify any differences in their facial ratios. The models’ facial ratios were calculated and compared with the golden proportion.ResultsDifferences in grading behaviour were observed amongst the two assessment groups. Only one out of the 12 facial ratios was not significantly different from the golden proportion.ConclusionsOnly one facial ratio was observed to be similar to the golden proportion in professional model facial photographs. No correlation was found between facial ratios in professional black models with the golden proportion. It is proposed that an individualistic treatment for each ratio is a rather better method to guide future practice.

Introduction: Machine learning (ML) is a set of models and methods that can detect patterns in vast amounts of data and use this information to perform various kinds of decision-making under uncertain conditions. This review explores the current role of this technology in plastic surgery by outlining the applications in clinical practice, diagnostic and prognostic accuracies, and proposed future direction for clinical applications and research. Methods: EMBASE, MEDLINE, CENTRAL and ClinicalTrials.gov were searched from 1990 to 2020. Any clinical studies (including case reports) which present the diagnostic and prognostic accuracies of machine learning models in the clinical setting of plastic surgery were included. Data collected were clinical indication, model utilised, reported accuracies, and comparison with clinical evaluation. Results: The database identified 1181 articles, of which 51 articles were included in this review. The clinical utility of these algorithms was to assist clinicians in diagnosis prediction (n=22), outcome prediction (n=21) and pre-operative planning (n=8). The mean accuracy is 88.80%, 86.11% and 80.28% respectively. The most commonly used models were neural networks (n=31), support vector machines (n=13), decision trees/random forests (n=10) and logistic regression (n=9). Conclusions: ML has demonstrated high accuracies in diagnosis and prognostication of burn patients, congenital or acquired facial deformities, and in cosmetic surgery. There are no studies comparing ML to clinician's performance. Future research can be enhanced using larger datasets or utilising data augmentation, employing novel deep learning models, and applying these to other subspecialties of plastic surgery.