A cross-sectional evaluation of the current state of wound healing education in the United Kingdom's undergraduate medical curriculum.

Between 2013 and 2018, there has been a 71% increase in the number of patients who have required wound care in the NHS and such large numbers has placed a significant burden on healthcare systems. However, there is currently no evidence as to whether medical students are equipped with the necessary skills to deal with an increasing number of wound care related issues that patients present with. A total of 323 medical students across 18 UK medical schools completed an anonymous questionnaire evaluating the wound education received at their medical school, encompassing the volume, content, format and efficacy of teaching. 68.4% (221/323) of respondents had received some form of wound education during their undergraduate studies. On average students received 2.25 h of structured, preclinical teaching and only 1 h of clinical based teaching in total. All students that received wound education reported undertaking teaching on the physiology of, and factors affecting wound healing, with only 32.2% (n = 104) of students receiving clinically based wound education There was very weak correlation and no significant association in student's ability to assess wounds (R2 = 0.190, p = 0.013), manage wounds (R2 = 0.060, p = 0.37), and prescribe wound care products (R2 = 0.093, p = 0.18) with their stage of training. Students strongly agreed that wound education is an important part of the undergraduate curriculum and post graduate practice, and do not feel their learning needs have been met. This is the first study to assess the provision of wound education in the United Kingdom, demonstrating a clear deficit in the provision of wound education compared to expectation of junior doctors. Wound education is largely overlooked in the medical curriculum, lacks a clinical focus and does not prepare junior doctors with the necessary clinical abilities to deal with wound related pathology. Expert opinion to direct changes to future curriculum and further evaluation of teaching methodology is required to address this deficit and ensure students have the necessary clinical skills to excel as newly graduated doctors.

A remote speech-based AI system to screen for early Alzheimer's disease via smartphones.

Introduction: Artificial intelligence (AI) systems leveraging speech and language changes could support timely detection of Alzheimer's disease (AD). Methods: The AMYPRED study (NCT04828122) recruited 133 subjects with an established amyloid beta (Aß) biomarker (66 Aß+, 67 Aß-) and clinical status (71 cognitively unimpaired [CU], 62 mild cognitive impairment [MCI] or mild AD). Daily story recall tasks were administered via smartphones and analyzed with an AI system to predict MCI/mild AD and Aß positivity. Results: Eighty-six percent of participants (115/133) completed remote assessments. The AI system predicted MCI/mild AD (area under the curve [AUC] = 0.85, ±0.07) but not Aß (AUC = 0.62 ±0.11) in the full sample, and predicted Aß in clinical subsamples (MCI/mild AD: AUC = 0.78 ±0.14; CU: AUC = 0.74 ±0.13) on short story variants (immediate recall). Long stories and delayed retellings delivered broadly similar results. Discussion: Speech-based testing offers simple and accessible screening for early-stage AD.

Leveraging speech and artificial intelligence to screen for early Alzheimer's disease and amyloid beta positivity.

Early detection of Alzheimer's disease is required to identify patients suitable for disease-modifying medications and to improve access to non-pharmacological preventative interventions. Prior research shows detectable changes in speech in Alzheimer's dementia and its clinical precursors. The current study assesses whether a fully automated speech-based artificial intelligence system can detect cognitive impairment and amyloid beta positivity, which characterize early stages of Alzheimer's disease. Two hundred participants (age 54-85, mean 70.6; 114 female, 86 male) from sister studies in the UK (NCT04828122) and the USA (NCT04928976), completed the same assessments and were combined in the current analyses. Participants were recruited from prior clinical trials where amyloid beta status (97 amyloid positive, 103 amyloid negative, as established via PET or CSF test) and clinical diagnostic status was known (94 cognitively unimpaired, 106 with mild cognitive impairment or mild Alzheimer's disease). The automatic story recall task was administered during supervised in-person or telemedicine assessments, where participants were asked to recall stories immediately and after a brief delay. An artificial intelligence text-pair evaluation model produced vector-based outputs from the original story text and recorded and transcribed participant recalls, quantifying differences between them. Vector-based representations were fed into logistic regression models, trained with tournament leave-pair-out cross-validation analysis to predict amyloid beta status (primary endpoint), mild cognitive impairment and amyloid beta status in diagnostic subgroups (secondary endpoints). Predictions were assessed by the area under the receiver operating characteristic curve for the test result in comparison with reference standards (diagnostic and amyloid status). Simulation analysis evaluated two potential benefits of speech-based screening: (i) mild cognitive impairment screening in primary care compared with the Mini-Mental State Exam, and (ii) pre-screening prior to PET scanning when identifying an amyloid positive sample. Speech-based screening predicted amyloid beta positivity (area under the curve = 0.77) and mild cognitive impairment or mild Alzheimer's disease (area under the curve = 0.83) in the full sample, and predicted amyloid beta in subsamples (mild cognitive impairment or mild Alzheimer's disease: area under the curve = 0.82; cognitively unimpaired: area under the curve = 0.71). Simulation analyses indicated that in primary care, speech-based screening could modestly improve detection of mild cognitive impairment (+8.5%), while reducing false positives (-59.1%). Furthermore, speech-based amyloid pre-screening was estimated to reduce the number of PET scans required by 35.3% and 35.5% in individuals with mild cognitive impairment and cognitively unimpaired individuals, respectively. Speech-based assessment offers accessible and scalable screening for mild cognitive impairment and amyloid beta positivity.

Validation of a Remote and Fully Automated Story Recall Task to Assess for Early Cognitive Impairment in Older Adults: Longitudinal Case-Control Observational Study.

BACKGROUND: Story recall is a simple and sensitive cognitive test that is commonly used to measure changes in episodic memory function in early Alzheimer disease (AD). Recent advances in digital technology and natural language processing methods make this test a candidate for automated administration and scoring. Multiple parallel test stimuli are required for higher-frequency disease monitoring. OBJECTIVE: This study aims to develop and validate a remote and fully automated story recall task, suitable for longitudinal assessment, in a population of older adults with and without mild cognitive impairment (MCI) or mild AD. METHODS: The "Amyloid Prediction in Early Stage Alzheimer's disease" (AMYPRED) studies recruited participants in the United Kingdom (AMYPRED-UK: NCT04828122) and the United States (AMYPRED-US: NCT04928976). Participants were asked to complete optional daily self-administered assessments remotely on their smart devices over 7 to 8 days. Assessments included immediate and delayed recall of 3 stories from the Automatic Story Recall Task (ASRT), a test with multiple parallel stimuli (18 short stories and 18 long stories) balanced for key linguistic and discourse metrics. Verbal responses were recorded and securely transferred from participants' personal devices and automatically transcribed and scored using text similarity metrics between the source text and retelling to derive a generalized match score. Group differences in adherence and task performance were examined using logistic and linear mixed models, respectively. Correlational analysis examined parallel-forms reliability of ASRTs and convergent validity with cognitive tests (Logical Memory Test and Preclinical Alzheimer's Cognitive Composite with semantic processing). Acceptability and usability data were obtained using a remotely administered questionnaire. RESULTS: Of the 200 participants recruited in the AMYPRED studies, 151 (75.5%)-78 cognitively unimpaired (CU) and 73 MCI or mild AD-engaged in optional remote assessments. Adherence to daily assessment was moderate and did not decline over time but was higher in CU participants (ASRTs were completed each day by 73/106, 68.9% participants with MCI or mild AD and 78/94, 83% CU participants). Participants reported favorable task usability: infrequent technical problems, easy use of the app, and a broad interest in the tasks. Task performance improved modestly across the week and was better for immediate recall. The generalized match scores were lower in participants with MCI or mild AD (Cohen d=1.54). Parallel-forms reliability of ASRT stories was moderate to strong for immediate recall (mean rho 0.73, range 0.56-0.88) and delayed recall (mean rho=0.73, range=0.54-0.86). The ASRTs showed moderate convergent validity with established cognitive tests. CONCLUSIONS: The unsupervised, self-administered ASRT task is sensitive to cognitive impairments in MCI and mild AD. The task showed good usability, high parallel-forms reliability, and high convergent validity with established cognitive tests. Remote, low-cost, low-burden, and automatically scored speech assessments could support diagnostic screening, health care, and treatment monitoring.

Undergraduate education of trauma and orthopaedic surgery in the UK : a systematic review.

AIMS: Evidence exists of a consistent decline in the value and time that medical schools place upon their undergraduate orthopaedic placements. This limited exposure to trauma and orthopaedics (T&O) during medical school will be the only experience in the speciality for the majority of doctors. This review aims to provide an overview of undergraduate orthopaedic training in the UK. METHODS: This review summarizes the relevant literature from the last 20 years in the UK. Articles were selected from database searches using MEDLINE, EMBASE, ERIC, Cochrane, and Web of Science. A total of 16 papers met the inclusion criteria. RESULTS: The length of exposure to T&O is declining; the mean total placement duration of two to three weeks is significantly less than the four- to six-week minimum advised by most relevant sources. The main teaching methods described in the literature included didactic lectures, bedside teaching, and small group case-based discussions. Students preferred interactive, blended learning teaching styles over didactic methods. This improvement in satisfaction was reflected in improvements in student assessment scores. However, studies failed to assess competencies in clinical skills and examinations, which is consistent with the opinions of UK foundation year doctors, approximately 40% of whom report a "poor" understanding of orthopaedics. Furthermore, the majority of UK doctors are not exposed to orthopaedics at the postgraduate level, which only serves to amplify the disparity between junior and generalist knowledge, and the standards expected by senior colleagues and professional bodies. CONCLUSION: There is a deficit in undergraduate orthopaedic training within the UK which has only worsened in the last 20 years, leaving medical students and foundation doctors with a potentially significant lack of orthopaedic knowledge. Cite this article: Bone Jt Open 2022;3(7):549-556.

Protocol for Rhapsody: a longitudinal observational study examining the feasibility of speech phenotyping for remote assessment of neurodegenerative and psychiatric disorders.

INTRODUCTION: Neurodegenerative and psychiatric disorders (NPDs) confer a huge health burden, which is set to increase as populations age. New, remotely delivered diagnostic assessments that can detect early stage NPDs by profiling speech could enable earlier intervention and fewer missed diagnoses. The feasibility of collecting speech data remotely in those with NPDs should be established. METHODS AND ANALYSIS: The present study will assess the feasibility of obtaining speech data, collected remotely using a smartphone app, from individuals across three NPD cohorts: neurodegenerative cognitive diseases (n=50), other neurodegenerative diseases (n=50) and affective disorders (n=50), in addition to matched controls (n=75). Participants will complete audio-recorded speech tasks and both general and cohort-specific symptom scales. The battery of speech tasks will serve several purposes, such as measuring various elements of executive control (eg, attention and short-term memory), as well as measures of voice quality. Participants will then remotely self-administer speech tasks and follow-up symptom scales over a 4-week period. The primary objective is to assess the feasibility of remote collection of continuous narrative speech across a wide range of NPDs using self-administered speech tasks. Additionally, the study evaluates if acoustic and linguistic patterns can predict diagnostic group, as measured by the sensitivity, specificity, Cohen's kappa and area under the receiver operating characteristic curve of the binary classifiers distinguishing each diagnostic group from each other. Acoustic features analysed include mel-frequency cepstrum coefficients, formant frequencies, intensity and loudness, whereas text-based features such as number of words, noun and pronoun rate and idea density will also be used. ETHICS AND DISSEMINATION: The study received ethical approval from the Health Research Authority and Health and Care Research Wales (REC reference: 21/PR/0070). Results will be disseminated through open access publication in academic journals, relevant conferences and other publicly accessible channels. Results will be made available to participants on request. TRIAL REGISTRATION NUMBER: NCT04939818.