Oral challenge vs routine care to assess low-risk penicillin allergy in critically ill hospital patients (ORACLE): a pilot safety and feasibility randomised controlled trial.

PURPOSE: Critically ill patients are vulnerable to penicillin allergy labels that may be incorrect. The validity of skin testing in intensive care units (ICUs) is uncertain. Many penicillin allergy labels are low risk, and validated tools exist to identify those amenable to direct oral challenge. This pilot randomised controlled trial explored the feasibility, safety, and validity of direct enteral challenge for low-risk penicillin allergy labels in critical illness. METHODS: Consenting patients with a low-risk penicillin allergy label (PAL) (PEN-FAST risk assessment score < 3) in four ICUs (Melbourne, Australia) were randomised 1:1 to penicillin (250 mg amoxicillin or implicated penicillin) direct enteral challenge versus routine care (2-h post-randomisation observation for each arm). Repeat challenge was performed post -ICU in the intervention arm. Patients were reviewed at 24 h and 5 days after each challenge/observation. RESULTS: We screened 533 patients. 130 (24.4%) were eligible and 80/130 (61.5%) enrolled (age median 64.5 years (interquartile range, IQR 53.5, 74), PEN-FAST median 1 (IQR 0,1)), with 40 (50%) randomised to direct enteral challenge. A positive challenge rate of 2.5% was identified. No antibiotic-associated serious adverse events were identified. 32/40 (80%) received a repeat challenge (zero positive). Post-randomisation, 13 (32%) of the intervention arm and 4 (10%) of the control arm received penicillin (odds ratio, OR 4.33 [1.27, 14.78] p = 0.019). CONCLUSION: These findings support the safety, validity, and feasibility of direct enteral challenge for critically ill patients with PEN-FAST assessed low-risk penicillin allergy. The absence of false negative results was confirmed by subsequent negative repeat challenges. A relatively low recruitment to screened ratio suggests that more inclusive eligibility criteria and integration of allergy assessment into routine ICU processes are needed to optimise allergy delabelling in critical illness.

Oral challenge vs routine care to assess low-risk penicillin allergy in critically ill hospital patients (ORACLE): a pilot randomised controlled trial.

BACKGROUND: Self-reported penicillin allergies are highly prevalent in hospitalised patients and are associated with poor health and health service outcomes. Critically ill patients have historically been underrepresented in prospective delabelling studies in part due to concerns around clinical stability and reliability of penicillin skin testing. Allergy assessment tools exist to identify low-risk penicillin allergy phenotypes and facilitate direct oral challenge delabelling. PEN-FAST is a clinical decision rule that has been validated to predict true penicillin allergy in a cohort of non-critically ill patients. There is however limited evidence regarding the feasibility, safety and efficacy of direct oral challenges and the use of delabelling clinical decisions rules in the intensive care setting. METHODS: Critically ill patients in the intensive care unit (ICU) with low-risk penicillin allergy phenotypes (PEN-FAST score < 3) will be randomised 1:1 to direct oral penicillin challenge (single dose 250 mg oral amoxicillin or implicated penicillin) or routine care, followed by a 2-h observation period. Patients will receive a second oral challenge/observation prior to hospital discharge (with subsequent observation for 2 h). An assessment for antibiotic-associated adverse events will also be undertaken at 24 h and 5 days post each challenge/observation and again at 90 days post-randomisation. The primary outcome measures are feasibility (proportion of eligible patients recruited and protocol compliance) and safety (proportion of patients who experience an antibiotic-associated immune-mediated adverse event or serious adverse event). DISCUSSION: We will report the feasibility and safety of point-of-care penicillin direct oral challenge in this first randomised controlled trial of low-risk penicillin allergy in critically ill hospitalised patients. Upon completion of the project, important findings will inform the design of planned large prospective multi-centre clinical trials in Australian and international ICUs, further examining safety and efficacy and exploring antimicrobial prescribing-related outcomes following penicillin oral challenge. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry Registration Number: ACTRN12621000051842 Date registered: 20/01/2021 https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=379735&isReview=true.

Best Practices for Clinical Skin Image Acquisition in Translational Artificial Intelligence Research.

Recent advances in artificial intelligence research have led to an increase in the development of algorithms for detecting malignancies from clinical and dermoscopic images of skin diseases. These methods are dependent on the collection of training and testing data. There are important considerations when acquiring skin images and data for translational artificial intelligence research. In this paper, we discuss the best practices and challenges for light photography image data collection, covering ethics, image acquisition, labeling, curation, and storage. The purpose of this work is to improve artificial intelligence for malignancy detection by supporting intentional data collection and collaboration between subject matter experts, such as dermatologists and data scientists.

Impact of virtual visits on primary care physician work flows.

OBJECTIVE: To understand the impact of virtual visits on primary care physician (PCP) work flows. DESIGN: Qualitative semistructured interviews. SETTING: Primary care practices within 5 regions in southern Ontario. PARTICIPANTS: Physicians representing primary care practices of various sizes and remuneration models (eg, capitation and fee-for-service models). METHODS: Interviews were conducted with PCPs involved in a large-scale pilot project implementing virtual visits (via a Web-based application) into clinical practices. Convenience and purposive sampling were used to recruit PCPs between January 2018 and March 2019. To obtain a representative sample, participants were sought from a variety of practice types and geographic regions. High and low users of virtual visits were included. Interviews were audiorecorded and transcribed. An inductive thematic analysis was used to identify prominent themes and subthemes. MAIN FINDINGS: Twenty-six physicians were interviewed (n=15 using convenience sampling and n=11 through purposive sampling). Four themes were identified: PCPs employ diverse approaches to integrate virtual care into their work flow; PCPs recognize that implementing virtual visits requires upfront time and effort but have variable perceptions regarding long-term impact of virtual care on processes; asynchronous messaging is preferable to synchronous audio or video visits; and strategies were identified to improve the integration of virtual visits. CONCLUSION: The potential of virtual care to improve work flow is dependent on the way these visits are implemented and used. Dedicated time for implementation, emphasis on using asynchronous secure messaging, and access to clinical champions and structured change management support were associated with more seamless integration of virtual visits.

Redesigning primary care: Provider perspectives on the clinical utility of virtual visits.

OBJECTIVE: To explore primary care physician (PCP) perspectives on the clinical utility of virtual visits. DESIGN: Qualitative design involving semistructured interviews. SETTING: Primary care practices within 5 regions in southern Ontario. PARTICIPANTS: Primary care physicians representing different practice sizes and remuneration models. METHODS: Interviews were conducted with PCPs who were involved in a large-scale pilot implementation of virtual visits (patient-provider asynchronous messaging, or synchronous audio or video communication). The first phase involved a convenience sample of users in the first 2 regions where the pilot was initiated; after implementation in all 5 regions, purposive sampling was used to ensure diversity within the sample (eg, physicians representing different use frequencies of virtual visits, regions, and remuneration models). Interviews were audiorecorded and transcribed. An inductive thematic analysis was used to identify prominent themes and subthemes. MAIN FINDINGS: Twenty-six physicians were interviewed. Fifteen were recruited using convenience sampling and 11 through purposive sampling. Four themes regarding the clinical utility of virtual visits were identified: virtual visits can effectively resolve many patient concerns, with some variation in PCP comfort using virtual visits for specific conditions; virtual visits are beneficial for a range of patients but some patients might overuse or inappropriately use them; PCPs prefer to use asynchronous messaging (eg, text or online messaging) because of its convenience and flexibility; and virtual visits can provide value at the patient, provider, and health system levels. CONCLUSION: While participants believed that virtual visits can be appropriately used to resolve a variety of clinical concerns, they found in practice that virtual visits are fundamentally different from face-to-face encounters. Professional guidelines on appropriate use cases should be established to develop a standard framework for virtual care.

Development and Clinical Evaluation of an Artificial Intelligence Support Tool for Improving Telemedicine Photo Quality.

Importance: Telemedicine use accelerated during the COVID-19 pandemic, and skin conditions were a common use case. However, many images submitted may be of insufficient quality for making a clinical determination. Objective: To determine whether an artificial intelligence (AI) decision support tool, a machine learning algorithm, could improve the quality of images submitted for telemedicine by providing real-time feedback and explanations to patients. Design, Setting, and Participants: This quality improvement study with an AI performance component and single-arm clinical pilot study component was conducted from March 2020 to October 2021. After training, the AI decision support tool was tested on 357 retrospectively collected telemedicine images from Stanford telemedicine from March 2020 to June 2021. Subsequently, a single-arm clinical pilot study was conducted to assess feasibility with 98 patients in the Stanford Department of Dermatology across 2 clinical sites from July 2021 to October 2021. For the clinical pilot study, inclusion criteria for patients included being adults (aged ≥18 years), presenting to clinic for a skin condition, and being able to photograph their own skin with a smartphone. Interventions: During the clinical pilot study, patients were given a handheld smartphone device with a machine learning algorithm interface loaded and were asked to take images of any lesions of concern. Patients were able to review and retake photos prior to submitting, so each submitted photo met the patient's assumed standard of clinical acceptability. A machine learning algorithm then gave the patient feedback on whether the image was acceptable. If the image was rejected, the patient was provided a reason by the AI decision support tool and allowed to retake the photos. Main Outcomes and Measures: The main outcome of the retrospective image analysis was the receiver operator curve area under the curve (ROC-AUC). The main outcome of the clinical pilot study was the image quality difference between the baseline images and the images approved by AI decision support. Results: Of the 98 patients included, the mean (SD) age was 49.8 (17.6) years, and 50 (51%) of the patients were male. On retrospective telemedicine images, the machine learning algorithm effectively identified poor-quality images (ROC-AUC of 0.78) and the reason for poor quality (blurry ROC-AUC of 0.84; lighting issues ROC-AUC of 0.70). The performance was consistent across age and sex. In the clinical pilot study, patient use of the machine learning algorithm was associated with improved image quality. An AI algorithm was associated with reduction in the number of patients with a poor-quality image by 68.0%. Conclusions and Relevance: In this quality improvement study, patients use of the AI decision support with a machine learning algorithm was associated with improved quality of skin disease photographs submitted for telemedicine use.

Disparities in dermatology AI performance on a diverse, curated clinical image set.

An estimated 3 billion people lack access to dermatological care globally. Artificial intelligence (AI) may aid in triaging skin diseases and identifying malignancies. However, most AI models have not been assessed on images of diverse skin tones or uncommon diseases. Thus, we created the Diverse Dermatology Images (DDI) dataset-the first publicly available, expertly curated, and pathologically confirmed image dataset with diverse skin tones. We show that state-of-the-art dermatology AI models exhibit substantial limitations on the DDI dataset, particularly on dark skin tones and uncommon diseases. We find that dermatologists, who often label AI datasets, also perform worse on images of dark skin tones and uncommon diseases. Fine-tuning AI models on the DDI images closes the performance gap between light and dark skin tones. These findings identify important weaknesses and biases in dermatology AI that should be addressed for reliable application to diverse patients and diseases.

Partnering with a senior living community to optimise teledermatology via full body skin screening during the COVID-19 pandemic: A pilot programme.

Background: Elderly patients in senior communities faced high barriers to care during the COVID-19 pandemic, including increased vulnerability to COVID-19, long quarantines for clinic visits, and difficulties with telemedicine adoption. Objective: To pilot a new model of dermatologic care to overcome barriers for senior living communities during the COVID-19 pandemic and assess patient satisfaction. Methods: From 16 November 2020 to 9 July 2021, this quality improvement programme combined in-residence full body imaging with real-time outlier lesion identification and virtual teledermatology. Residents from the Sequoias Portola Valley Senior Living Retirement Community (Portola Valley, California) voluntarily enroled in the Stanford Skin Scan Programme. Non-physician clinical staff with a recent negative COVID-19 test travelled on-site to obtain in-residence full body photographs using a mobile app-based system on an iPad called SkinIO that leverages deep learning to analyse patient images and suggest suspicious, outlier lesions for dermoscopic photos. A single dermatologist reviewed photographs with the patient and provided recommendations via a video visit. Objective measures included follow-up course and number of skin cancers detected. Subjective findings were obtained through patient experience surveys. Results: Twenty-seven individuals participated, three skin cancers were identified, with 11 individuals scheduled for a follow up in-person visit and four individuals starting home treatment. Overall, 88% of patients were satisfied with the Skin Scan programme, with 77% likely to recommend the programme to others. 92% of patients agreed that the Skin Scan photographs were representative of their skin. In the context of the COVID-19 pandemic, 100% of patients felt the process was safer or comparable to an in-person visit. Despite overall appreciation for the programme, 31% of patients reported that they would prefer to see dermatologist in-person after the pandemic. Conclusions: This programme offers a framework for how a hybrid skin scan programme may provide high utility for individuals with barriers to accessing in-person clinics.

Understanding Engagement and the Potential Impact of an Electronic Drug Repository: Multi-Methods Study.

BACKGROUND: Centralized drug repositories can reduce adverse events and inappropriate prescriptions by enabling access to dispensed medication data at the point of care; however, how they achieve this goal is largely unknown. OBJECTIVE: This study aims to understand the perceived clinical value; the barriers to and enablers of adoption; and the clinician groups for which a provincial, centralized drug repository may provide the most benefit. METHODS: A mixed methods approach, including a web-based survey and semistructured interviews, was used. Participants were clinicians (eg, nurses, physicians, and pharmacists) in Ontario who were eligible to use the digital health drug repository (DHDR), irrespective of actual use. Survey data were ranked on a 7-point adjectival scale and analyzed using descriptive statistics, and interviews were analyzed using qualitative descriptions. RESULTS: Of the 161 survey respondents, only 40 (24.8%) actively used the DHDR. Perceptions of the utility of the DHDR were neutral (mean scores ranged from 4.11 to 4.76). Of the 75.2% (121/161) who did not use the DHDR, 97.5% (118/121) rated access to medication information (eg, dose, strength, and frequency) as important. Reasons for not using the DHDR included the cumbersome access process and the perception that available data were incomplete or inaccurate. Of the 33 interviews completed, 26 (79%) were active DHDR users. The DHDR was a satisfactory source of secondary information; however, the absence of medication instructions and prescribed medications (which were not dispensed) limited its ability to provide a comprehensive profile to meaningfully support clinical decision-making. CONCLUSIONS: Digital drug repositories must be adjusted to align with the clinician's needs to provide value. Ensuring integration with point-of-care systems, comprehensive clinical data, and streamlined onboarding processes would optimize clinically meaningful use. The electronic provision of accessible drug information to providers across health care settings has the potential to improve efficiency and reduce medication errors.

Uptake and patient and provider communication modality preferences of virtual visits in primary care: a retrospective cohort study in Canada.

OBJECTIVES: To evaluate the uptake of a platform for virtual visits in primary care, examine patient and physician preferences for virtual communication methods and report on characteristics of visits and patients experience of care. DESIGN: A retrospective cohort study. SETTING: Primary care practices within five regions in Ontario, Canada after 18 months of access to virtual care services. PARTICIPANTS: 326 primary care providers and 14 291 registered patients. INTERVENTIONS: Providers used a platform that allowed them to connect with their patients through synchronous (audio/video) and/or asynchronous (secure messaging) communication. MAIN OUTCOME MEASURES: User-level data from the platforms including patient demographics, practice characteristics, communication modality used, visit characteristics and patients' satisfaction. RESULTS: Among the participants, 44% of registered patients and 60% of registered providers used the platform at least once. Among patient users, 51% completed at least one virtual visit. The majority of virtual visits (94%) involved secure messaging. The most common patient requests were for medication prescriptions (24%) and follow-up from previous appointment (22%). The most common provider request was to follow-up on test results (59%). Providers indicated that 81% of virtual visits required no follow-up for that issue and 99% of patients reported that they would use virtual care services again. CONCLUSIONS: While there are a growing number of primary care video visit services, our study found that both patients and providers in rostered practices prefer secure messaging over video. Despite fears that virtual visits would be overused by patients, when patients connected with their own primary care provider, many virtual visits appeared to replace in-person visits, and patients did not overwhelm physicians with requests. This approach may improve access and continuity in primary care.

Off-Label High-Dose Secukinumab for the Treatment of Moderate-to-Severe Psoriasis.

BACKGROUND: Secukinumab is an anti-IL-17A monoclonal antibody approved for the treatment of moderate-to-severe psoriasis in adult patients. Despite its favourable safety and efficacy profile in clinical trials, some patients in clinical practice fail to respond adequately to the approved maintenance regimen of 300 mg subcutaneous monthly. Some clinicians manage these patients by using off-label high-dose secukinumab regimens, which include shortening the dosing interval to 300 mg every 2 or 3 weeks instead of monthly, or increasing the monthly dose to 450 mg. OBJECTIVE: This study aims to investigate the safety and efficacy of high-dose secukinumab regimens for the treatment of psoriasis to inform real-world clinical practice. METHODS: We performed a retrospective chart review at 5 dermatology clinics for adult patients diagnosed with moderate-to-severe psoriasis treated with an off-label high-dose secukinumab regimen. Efficacy was measured using the Psoriasis Area and Severity Index or a Physician Global Assessment score of 0 or 1 after dose escalation. Adverse events were recorded to assess safety outcomes. RESULTS: Twenty-five patients were included in this case series, and 14 of them achieved efficacy from dose escalation with secukinumab based on our study endpoints. There was 1 case of the common cold and 1 upper respiratory tract infection reported after dose escalation. CONCLUSION: Our study provides evidence that dose escalation with secukinumab results in clinical benefit and is well tolerated among patients with moderate-to-severe psoriasis who failed to respond adequately to the approved regimen. This work necessitates larger studies to fully characterize the efficacy and long-term safety profile of secukinumab dose escalation.

Ixekizumab (Interleukin 17A Antagonist): 12-week Efficacy and Safety Outcomes in Real-world Clinical Practice.

BACKGROUND:: Current knowledge of the efficacy and safety of ixekizumab is limited to data from phase III randomized controlled trials (RCTs). A gap exists in our understanding of treatment outcomes of this newly available biologic in real-world clinical practice. OBJECTIVE:: This study explores the efficacy and safety of ixekizumab in non-RCT patients to compare real-world outcomes to those reported in RCTs. METHODS:: We conducted a multicentre, retrospective chart review of patients treated with ixekizumab therapy for moderate-to-severe plaque psoriasis. Efficacy (Psoriasis Area and Severity Index score of 75 or Physician Global Assessment of 0 or 1) and safety (reported adverse events [AEs]) were assessed following a 12-week treatment period. RESULTS:: Of the 60 patients included, 45 (75.0%) achieved efficacious outcomes after 12 weeks of ixekizumab treatment. Twenty-two (36.7%) patients experienced one or more AEs, of whom only 3 (5.0%) withdrew from treatment as a result. Common AEs included injection site reaction/erythema/pain (13.3%) and dermatitis (5.0%). CONCLUSION:: Ixekizumab has shown to be a safe and effective therapeutic option for plaque psoriasis in real-world practice. It does not appear that patients experience more AEs in real-world clinics than those in clinical trials.

In-vitro and in-vivo assays for angiogenesis-modulating drug discovery and development.

In the past 35 years, significant findings have been made in relation to angiogenesis, and how this usually normal physiological function is converted into an abnormal state in cancer. To search for agents that can inhibit angiogenesis, and thereby prevent a tumour from proliferation and spread that is ultimately fatal to the patient, various in-vitro assays have been developed. In addition, older assays have been refined usually into high throughput screening formats, mainly by the biopharmaceutical industry in their attempts to develop novel therapeutic molecules and maintain a pipeline of lead candidates. The central aim is to extract more accurate data that would facilitate the birth of innovative mechanisms to defeat aberrant angiogenesis in-vivo. At the same time, better in-vivo models have been established, with the goal to mimic as close as possible the natural progression of various types of neoplasms in response to a good angiogenic response. More clinically relevant models are needed as anti-angiogenesis drug discovery and drug development companies fast track their lead molecules from preclinical investigations to phase I clinical trials.