Accuracy of an artificial intelligence as a medical device as part of a UK-based skin cancer teledermatology service.

Introduction: An artificial intelligence as a medical device (AIaMD), built on convolutional neural networks, has demonstrated high sensitivity for melanoma. To be of clinical value, it needs to safely reduce referral rates. The primary objective of this study was to demonstrate that the AIaMD had a higher rate of correctly classifying lesions that did not need to be referred for biopsy or urgent face-to-face dermatologist review, compared to teledermatology standard of care (SoC), while achieving the same sensitivity to detect malignancy. Secondary endpoints included the sensitivity, specificity, positive and negative predictive values, and number needed to biopsy to identify one case of melanoma or squamous cell carcinoma (SCC) by both the AIaMD and SoC. Methods: This prospective, single-centre, single-arm, masked, non-inferiority, adaptive, group sequential design trial recruited patients referred to a teledermatology cancer pathway (clinicaltrials.gov NCT04123678). Additional dermoscopic images of each suspicious lesion were taken using a smartphone with a dermoscopic lens attachment. The images were assessed independently by a consultant dermatologist and the AIaMD. The outputs were compared with the final histological or clinical diagnosis. Results: A total of 700 patients with 867 lesions were recruited, of which 622 participants with 789 lesions were included in the per-protocol (PP) population. In total, 63.3% of PP participants were female; 89.0% identified as white, and the median age was 51 (range 18-95); and all Fitzpatrick skin types were represented including 25/622 (4.0%) type IV-VI skin. A total of 67 malignant lesions were identified, including 8 diagnosed as melanoma. The AIaMD sensitivity was set at 91 and 92.5%, to match the literature-defined clinician sensitivity (91.46%) as closely as possible. In both settings, the AIaMD identified had a significantly higher rate of identifying lesions that did not need a biopsy or urgent referral compared to SoC (p-value = 0.001) with comparable sensitivity for skin cancer. Discussion: The AIaMD identified significantly more lesions that did not need to be referred for biopsy or urgent face-to-face dermatologist review, compared to teledermatologists. This has the potential to reduce the burden of unnecessary referrals when used as part of a teledermatology service.

Patient perspectives of artificial intelligence as a medical device in a skin cancer pathway.

The use of artificial intelligence as a medical device (AIaMD) in healthcare systems is increasing rapidly. In dermatology, this has been accelerated in response to increasing skin cancer referral rates, workforce shortages and backlog generated by the COVID-19 pandemic. Evidence regarding patient perspectives of AIaMD is currently lacking in the literature. Patient acceptability is fundamental if this novel technology is to be effectively integrated into care pathways and patients must be confident that it is implemented safely, legally, and ethically. A prospective, single-center, single-arm, masked, non-inferiority, adaptive, group sequential design trial, recruited patients referred to a teledermatology cancer pathway. AIaMD assessment of dermoscopic images were compared with clinical or histological diagnosis, to assess performance (NCT04123678). Participants completed an online questionnaire to evaluate their views regarding use of AIaMD in the skin cancer pathway. Two hundred and sixty eight responses were received between February 2020 and August 2021. The majority of respondents were female (57.5%), ranged in age between 18 and 93 years old, Fitzpatrick type I-II skin (81.3%) and all 6 skin types were represented. Overall, there was a positive sentiment regarding potential use of AIaMD in skin cancer pathways. The majority of respondents felt confident in computers being used to help doctors diagnose and formulate management plans (median = 70; interquartile range (IQR) = 50-95) and as a support tool for general practitioners when assessing skin lesions (median = 85; IQR = 65-100). Respondents were comfortable having their photographs taken with a mobile phone device (median = 95; IQR = 70-100), which is similar to other studies assessing patient acceptability of teledermatology services. To the best of our knowledge, this is the first comprehensive study evaluating patient perspectives of AIaMD in skin cancer pathways in the UK. Patient involvement is essential for the development and implementation of new technologies. Continued end-user feedback will allow refinement of services to ensure patient acceptability. This study demonstrates patient acceptability of the use of AIaMD in both primary and secondary care settings.

Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance.

Introduction: Deep Ensemble for Recognition of Malignancy (DERM) is an artificial intelligence as a medical device (AIaMD) tool for skin lesion assessment. Methods: We report prospective real-world performance from its deployment within skin cancer pathways at two National Health Service hospitals (UK) between July 2021 and October 2022. Results: A total of 14,500 cases were seen, including patients 18-100 years old with Fitzpatrick skin types I-VI represented. Based on 8,571 lesions assessed by DERM with confirmed outcomes, versions A and B demonstrated very high sensitivity for detecting melanoma (95.0-100.0%) or malignancy (96.0-100.0%). Benign lesion specificity was 40.7-49.4% (DERM-vA) and 70.1-73.4% (DERM-vB). DERM identified 15.0-31.0% of cases as eligible for discharge. Discussion: We show DERM performance in-line with sensitivity targets and pre-marketing authorisation research, and it reduced the caseload for hospital specialists in two pathways. Based on our experience we offer suggestions on key elements of post-market surveillance for AIaMDs.

Dynamic shapes of the zygote and two-cell mouse and human.

Mouse zygote morphokinetics were measured during interphase, the mitotic period, cytokinesis, and two-cell stage. Sequences of rounder-distorted-rounder shapes were revealed, as were changing patterns of cross section area. A calcium chelator and an actin-disrupting agent inhibited the area changes that occurred between pronuclear envelope breakdown and cytokinesis. During cell division, two vortices developed in each nascent cell and they rotated in opposite directions at each end of the cell, a pattern that sometimes persisted for up to 10 h. Exchange with the environment may have been promoted by these shape and area cycles and persisting circulation in the cytoplasm may have a similar function between a cell's interior and periphery. Some of these movements were sporadically also seen in human zygotes with abnormal numbers of pronuclei and the two-cell stages that developed from these compromised human zygotes.

Recognizing the Dying Patient, When Less Could be More: A Diagnostic Framework for Shared Decision-Making at the End of Life.

BACKGROUND: Recognizing dying patients is crucial to produce outcomes that are satisfactory to patients, their families, and clinicians. AIM: Earlier discussion of and shared decision-making around dying to improve these outcomes. DESIGN: In this study, we interviewed 16 senior clinicians to develop summaries of palliative care in 4 key specialties: Cardiology, Vascular Surgery, Emergency General Surgery, and Intensive Care. SETTING: Oxford University Hospitals. RESULTS: Based on themes common to our 4 clinical areas, we developed a novel diagnostic framework to support shared palliative decision-making that can be summarized as follows: 1) Is the acute pathology reversible? 2) What is the patient's physiological reserve? 3) What is important to the patient? Will they be fit enough for discharge for a reasonable length of time? CONCLUSIONS: We believe that education using this framework in the medical school and postgraduate curricula would significantly improve recognition of dying patients. This would serve to stimulate earlier conversations, more shared decision-making, and ultimately better outcomes in palliative care and patient experience.

Shared decision making and consent post-Montgomery, UK Supreme Court judgement supporting best practice.

The UK Supreme Court Montgomery judgement marks a decisive shift in the legal test of duty of care in the context of consent to treatment from the perspective of the clinician (as represented by Bolam rules) to that of the patient. This has important implications in the surgical field worldwide, where informed consent is critical. This paper aims to explain the ruling and how it impacts the consent process. The case and ruling are outlined and summarised as pertaining to consent and requirements for validity; a shift from the clinician's interpretation about what would be best for patients to the values of the particular patient concerned in the decision in question. A sample of recent commentaries is reviewed. Four examples illustrate some of the practical applications of the Montgomery ruling on consent and how the ruling can empower doctors and patients to make mutually beneficial shared decisions. Future consent should be obtained using a Montgomery compliant strategy in accordance with the principles of shared decision making.

Shared decision making in chronic medication use: Scenarios depicting exemplary care.

Patient-centred care includes patients and their values in the healthcare decision-making process. Shared decision-making is essential for patient satisfaction, medication adherence, and positive clinical outcomes. It also empowers patients to play an active role in managing their health condition by improving their sense of agency, allowing them to personalise their care. Long-term prescriptions are an unexplored area where shared decision-making could be impactful. This paper provides 5 common clinical prescription scenarios pertaining to route of administration, medication timing, side effects, and length of prescription. Minor tailoring of treatment plans could significantly improve clinical outcomes. These serve as exemplars as to how to personalise prescriptions through shared decision making in accordance with patient values.

Shared decision-making across the specialties: Much potential but many challenges.

Shared decision-making (SDM) is a collaborative process through which patients and clinicians work together to arrive at a mutually agreed-upon treatment plan. The use of SDM has gathered momentum, with it being legally mandated in some areas; however, despite being a ubiquitously applicable intervention, its maturity in use varies across the specialties and requires an appreciation of the nuanced and different challenges they each present. It is therefore our aim in this paper to review the current and potential use of SDM across a wide variety of specialties in order to understand its value and the challenges in its implementation. The specialties we consider are Primary Care, Mental Health, Paediatrics, Palliative Care, Medicine, and Surgery. SDM has been demonstrated to improve decision quality in many scenarios across all of these specialties. There are, however, many challenges to its successful implementation, including the need for high-quality decision aids, cultural shift, and adequate training. SDM represents a paradigm shift towards more patient-centred care but must be implemented with continued people centricity in order to realize its full potential.

Purple Urine Bag Syndrome: A Rare Spot Diagnosis.

Purple urine bag syndrome (PUBS) is a complication of urinary tract infections (UTIs) where catheter bags and tubing turn purple. It is alarming for patients, families, and clinicians; however, it is in itself a benign phenomenon. PUBS is the result of UTIs with specific bacteria that produce sulphatases and phosphatases which lead tryptophan metabolism to produce indigo (blue) and indirubin (red) pigments, a mixture of which becomes purple. Risk factors include female gender, immobility, constipation, chronic catheterisation, and renal disease. Management involves reassurance, antibiotics, and regular changing of catheters, although there are debates regarding how aggressively to treat and no official guidelines. Prognosis is good, but PUBS is associated with high morbidity and mortality due to the backgrounds of patients. Here, we review the literature available on PUBS, present a summary of case studies from the last five years, and propose the Oxford Urine Chart as a tool to aid such diagnoses.

What is the effect of fasting on the lifespan of neurons?

Medical advancements have increased life expectancy but have consequently increased the incidence of age-related disease. Fasting or dietary restriction (DR) can help prevent these via anti-ageing effects; however, these effects in neurons are less well characterized. Here, a series of animal and human studies of the effects of DR on the structural and functional integrity of neurons and the underlying mechanisms are analyzed. DR improves the integrity of animal neurons via a wide range of possible mechanisms including changes in metabolism, oxidative damage, stress responses, growth factors, and gene expression. These mechanisms are extensively interlinked and point to an optimum range of calorie intake, above calorie deprivation and below burdensome calorie excess. Human studies also suggest that DR improves neuron integrity; however, due to ethical and methodological limitations, the most conclusive data on DR hinge upon on-going life-long monkey experiments. Rather than developing pharmacological mimetics of DR, our focus should be on educating the public about DR in order to minimize age-related disease.