Automated detection and classification of concealed objects using infrared thermography and convolutional neural networks

This paper presents a study on the effectiveness of a convolutional neural network (CNN) in classifying infrared images for security scanning. Infrared thermography was explored as a non-invasive security scanner for stand-off and walk-through concealed object detection. Heat generated by human subjects radiates off the clothing surface, allowing detection by an infrared camera. However, infrared lacks in penetration capability compared to longer electromagnetic waves, leading to less obvious visuals on the clothing surface. ResNet-50 was used as the CNN model to automate the classification process of thermal images. The ImageNet database was used to pre-train the model, which was further fine-tuned using infrared images obtained from experiments. Four image pre-processing approaches were explored, i.e., raw infrared image, subject cropped region-of-interest (ROI) image, K-means, and Fuzzy-c clustered images. All these approaches were evaluated using the receiver operating characteristic curve on an internal holdout set, with an area-under-the-curve of 0.8923, 0.9256, 0.9485, and 0.9669 for the raw image, ROI cropped, K-means, and Fuzzy-c models, respectively. The CNN models trained using various image pre-processing approaches suggest that the prediction performance can be improved by the removal of non-decision relevant information and the visual highlighting of features.

Exploring the effectiveness of virtual and in-person instruction in culinary medicine: a survey-based study

BACKGROUND

Culinary medicine, which has recently increased in popularity in medical education, incorporates food and nutritional interventions with principles of disease prevention and treatment. The ultimate goal is to improve overall health outcomes. The growing prevalence of diet-related chronic diseases indicates the need for physicians to have a deeper understanding of the interplay between nutrition and disease. Incorporating culinary medicine into medical education can equip medical students with the necessary skills and knowledge to promote better patient outcomes. The purpose of this study was to evaluate students' perceptions of their foundational knowledge of a culinary medicine course after completion of the course for first- and second-year medical students at the PCOM (Philadelphia College of Osteopathic Medicine). We will also examine the difference between methods of instruction in relation to constructs discussed of knowledge gained and enjoyment of the course.

METHODS

This retrospective cohort study was conducted using SurveyMonkey by Momentive. Data were collected from osteopathic medical students who enrolled in a culinary medicine course at the PCOM from 2018 to 2022 through the completion of a post-course survey. The methods of instruction included either a virtual or in-person classroom. The statistical analysis for this study was conducted using IBM SPSS Statistics version 28. To compare methods of instruction, the statistical analyses used included descriptive statistics, chi-square analysis, one-way ANOVA, and independent sample one-sided t tests.

RESULTS

A total of 360 out of 430 participants, spanning the years 2018 to 2022, completed the course requirements and participated in the online survey. There was a valid sample size of 249 for the in-person group and 111 for the virtual instruction group. The knowledge gained construct consisted of five survey questions, for a total possible score of 25, while the enjoyment construct consisted of two questions, for a total possible score of 10. A statistically significant difference in knowledge gained was identified by one-way ANOVA, F (4,355) = 3.853, p =.004. Additionally, there was a statistically significant difference in enjoyment of the course between class years, F (4,356) = 11.977, p <.001. Independent sample t-tests revealed a statistically significant difference in enjoyment between the two methods (p <.001) even after accounting for unequal variances, with Cohen's d equal to 0.807, indicating a moderate effect size.

CONCLUSIONS

The findings of this study suggest that overall, students were highly satisfied with the Culinary Medicine course over a five-year period. The study suggested that students who participated in in-person courses benefitted more than did the virtual students in terms of knowledge gained and enjoyment. The 360 students who completed the Culinary Medicine course were highly satisfied with the information and skills they acquired.

Examining accurate diagnosis of complex PTSD in ICD-11

BACKGROUND

Complex posttraumatic stress disorder (complex PTSD), the most frequently suggested new category for inclusion by mental health professionals, has been included in the Eleventh Revision of the World Health Organization's International Classification of Diseases (ICD-11). Research has yet to explore whether clinicians' recognition of the distinct complex PTSD symptoms predicts giving the correct diagnosis. The present study sought to determine if international mental health professionals were able to accurately diagnose complex PTSD and identify the shared PTSD features and three essential diagnostic features, specific to complex PTSD.

METHODS

Participants were randomly assigned to view two vignettes and tasked with providing a diagnosis (or indicating that no diagnosis was warranted). Participants then answered a series of questions regarding the presence or absence of each of the essential diagnostic features specific to the diagnosis they provided.

RESULTS

Clinicians who recognized the presence or absence of complex PTSD specific features were more likely to arrive at the correct diagnostic conclusion. Complex PTSD specific features were significant predictors while the shared PTSD features were not, indicating that attending to each of the specific symptoms was necessary for diagnostic accuracy of complex PTSD.

LIMITATIONS

The use of written case vignettes including only adult patients and a non-representative sample of mental health professionals may limit the generalizability of the results.

CONCLUSIONS

Findings support mental health professionals' ability to accurately identify specific features of complex PTSD. Future work should assess whether mental health providers can effectively identify symptoms of complex PTSD in a clinical setting.

Painful schwannoma of scalp: A case report

Schwannoma, also known as neurilemmoma, is a benign neoplasm of Schwann cells of the cranial or peripheral nerve sheath. Scalp involvement has been reported in 25% of patients with extracranial head and neck schwannomas, which can be misdiagnosed clinically as epidermal cyst or lipoma. In this article, we report a 32-year-old male presenting with a slow-growing painful subcutaneous mass on the left occipital scalps without any neurological symptoms. Pathological findings confirmed the diagnosis of schwannoma, and surgical removal resulted in the resolution of pain and lack of recurrence.

Cold indoor temperatures and their association with health and well-being: a systematic literature review

OBJECTIVE

The study aimed to identify, appraise and update evidence on the association between cold temperatures (i.e. <18°C) within homes (i.e. dwellings) and health and well-being outcomes.

STUDY DESIGN

This study was a systematic review.

METHODS

Seven databases (MEDLINE, Embase, Cochrane Database of Systematic Reviews, CINAHL, APA PsycInfo, Applied Social Sciences Index and Abstracts, Coronavirus Research Database) were searched for studies published between 2014 and 2022, which explored the association between cold indoor temperatures and health and well-being outcomes. Studies were limited to those conducted in temperate and colder climates due to the increased risk of morbidity and mortality during winter in those climatic zones. Studies were independently quality assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies.

RESULTS

Of 1209 studies, 20 were included for review. Study outcomes included cardiovascular (blood pressure, electrocardiogram abnormalities, blood platelet count), respiratory (chronic obstructive pulmonary disease symptoms, respiratory viral infection), sleep, physical performance and general health. Seventeen studies found exposure to cold indoor temperatures was associated with negative effects on health outcomes studied. Older individuals and those with chronic health problems were found to be more vulnerable to negative health outcomes.

CONCLUSION

Evidence suggests that indoor temperatures <18°C are associated with negative health effects. However, the evidence is insufficient to allow clear conclusions regarding outcomes from specific temperature thresholds for different population groups. Significant gaps in the current evidence base are identified, including research on the impacts of cold indoor temperatures on mental health and well-being, studies involving young children, and the long-term health effects of cold indoor temperatures.

Active Reduction of Apparent Cable Capacitance

This paper presents a method for reducing apparent cable capacitance seen by sensors. The proposed method is designed for sensing in extreme environments including ultra-high temperatures, but can be applied in benign environments as well. By reducing the cable capacitance, high speed signals can be transmitted over longer distances, allowing the application of advanced control systems that require high bandwidth data for stable operation. A triaxial cable with an associated guard circuit is developed that actively reduces cable capacitance while also rejecting extraneous electric and magnetic interference on the signal. The active capacitance reduction method developed is tested experimentally and shown to reduce apparent cable capacitance to two percent of the static value.

The impact of imputation quality on machine learning classifiers for datasets with missing values

BACKGROUND

Classifying samples in incomplete datasets is a common aim for machine learning practitioners, but is non-trivial. Missing data is found in most real-world datasets and these missing values are typically imputed using established methods, followed by classification of the now complete samples. The focus of the machine learning researcher is to optimise the classifier's performance.

METHODS

We utilise three simulated and three real-world clinical datasets with different feature types and missingness patterns. Initially, we evaluate how the downstream classifier performance depends on the choice of classifier and imputation methods. We employ ANOVA to quantitatively evaluate how the choice of missingness rate, imputation method, and classifier method influences the performance. Additionally, we compare commonly used methods for assessing imputation quality and introduce a class of discrepancy scores based on the sliced Wasserstein distance. We also assess the stability of the imputations and the interpretability of model built on the imputed data.

RESULTS

The performance of the classifier is most affected by the percentage of missingness in the test data, with a considerable performance decline observed as the test missingness rate increases. We also show that the commonly used measures for assessing imputation quality tend to lead to imputed data which poorly matches the underlying data distribution, whereas our new class of discrepancy scores performs much better on this measure. Furthermore, we show that the interpretability of classifier models trained using poorly imputed data is compromised.

CONCLUSIONS

It is imperative to consider the quality of the imputation when performing downstream classification as the effects on the classifier can be considerable.

PSMA PET Guided Salvage Radiotherapy Among Prostate Cancer Patients in the Post-Prostatectomy Setting: A Single Center Post-Hoc Analysis

PURPOSE/OBJECTIVE(S)

Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) shows improved sensitivity and specificity for detection of locoregional and distant metastatic prostate cancer (PCa) compared to conventional imaging, especially at lower PSA levels as is often the case in the biochemically recurrent (BCR), post radical prostatectomy (RP) setting. Providers are now utilizing PSMA PET findings to guide their salvage radiotherapy (sRT) treatment fields and doses, although it is not well understood how PSMA PET guided sRT impacts patient outcomes.

MATERIALS/METHODS

This was a post-hoc analysis of 5 prospective studies of PSMA PET conducted at UCLA from 2016 to 2021 that included patients with recurrent PCa following RP. Patients were included in this retrospective study if they initiated sRT within 3 months of PSMA PET, had at least 12 months of follow up after sRT completion, had available sRT treatment details, and did not have distant metastases (DM) by conventional imaging on upfront staging. Patients treated with palliative RT were excluded. BCR following sRT was defined as an increase in PSA of 0.2 ng/ml above the post sRT nadir. Metastasis directed therapy (MDT) was defined as sRT to all PSMA+ N1 and M1 lesions. Baseline patient demographics, PSMA PET findings, sRT & ADT treatment details, and patient outcome data were collected.

RESULTS

A total of 176 patients were included in this study. Median time between RP and PSMA PET was 38 months (range 1-329). Median PSA at the time of the PSMA PET was 0.625 ng/mL (range 0.063-35). PSMA PET was positive in 128 patients (73%): 21 (12%) miT+N0M0, 55 (31%) miTxN1M0 and 52 (30%) miTxNxM1 with 19 (11%) miTxNxM1a, 31 (18%) miTxNxM1b, and 2 (1%) miTxNxM1c. Median number of lesions seen on positive PSMA scans was 1 (range 1-8). 39 (22%) patients were subsequently treated with sRT to the prostate bed (PB) only, 59 (34%) to PB + pelvic lymph nodes (PLNs), 33 (19%) to PLNs only, 7 (4%) to PB + PLNs + DM, 7 (4%) to PLNs + DM, and 31 (18%) to DM only. 59 (34%) patients were treated with concurrent ADT at a median duration of 6 months (range 1-39). At a median follow-up of 32 months (range 12-70) after sRT, 80 patients (45%) did not develop BCR or imaging relapse (IR) following sRT, 24 patients (14%) developed BCR but not IR, 1 patient (<1%) developed IR only, and 70 patients (40%) developed both BCR and IR. The median time to BCR and IR following sRT was 15 months (range 1-48) and 19 months (range 6-61), respectively. 1 year post sRT biochemical recurrence free survival was 77%. Of the 83 patients treated with MDT, 32 (39%) did not develop subsequent disease relapse.

CONCLUSION

This post hoc analysis assessed the outcomes of 176 patients treated with PSMA PET guided salvage RT, proving it to be an effective method for treating both pelvic and extrapelvic recurrent PCa. Further investigation is needed to assess the full extent of patient outcomes in this population.

Common methodological pitfalls in ICI pneumonitis risk prediction studies

Background

Pneumonitis is one of the most common adverse events induced by the use of immune checkpoint inhibitors (ICI), accounting for a 20% of all ICI-associated deaths. Despite numerous efforts to identify risk factors and develop predictive models, there is no clinically deployed risk prediction model for patient risk stratification or for guiding subsequent monitoring. We believe this is due to systemic suboptimal approaches in study designs and methodologies in the literature. The nature and prevalence of different methodological approaches has not been thoroughly examined in prior systematic reviews.

Methods

The PubMed, medRxiv and bioRxiv databases were used to identify studies that aimed at risk factor discovery and/or risk prediction model development for ICI-induced pneumonitis (ICI pneumonitis). Studies were then analysed to identify common methodological pitfalls and their contribution to the risk of bias, assessed using the QUIPS and PROBAST tools.

Results

There were 51 manuscripts eligible for the review, with Japan-based studies over-represented, being nearly half (24/51) of all papers considered. Only 2/51 studies had a low risk of bias overall. Common bias-inducing practices included unclear diagnostic method or potential misdiagnosis, lack of multiple testing correction, the use of univariate analysis for selecting features for multivariable analysis, discretization of continuous variables, and inappropriate handling of missing values. Results from the risk model development studies were also likely to have been overoptimistic due to lack of holdout sets.

Conclusions

Studies with low risk of bias in their methodology are lacking in the existing literature. High-quality risk factor identification and risk model development studies are urgently required by the community to give the best chance of them progressing into a clinically deployable risk prediction model. Recommendations and alternative approaches for reducing the risk of bias were also discussed to guide future studies.

A pipeline to further enhance quality, integrity and reusability of the NCCID clinical data

The National COVID-19 Chest Imaging Database (NCCID) is a centralized UK database of thoracic imaging and corresponding clinical data. It is made available by the National Health Service Artificial Intelligence (NHS AI) Lab to support the development of machine learning tools focused on Coronavirus Disease 2019 (COVID-19). A bespoke cleaning pipeline for NCCID, developed by the NHSx, was introduced in 2021. We present an extension to the original cleaning pipeline for the clinical data of the database. It has been adjusted to correct additional systematic inconsistencies in the raw data such as patient sex, oxygen levels and date values. The most important changes will be discussed in this paper, whilst the code and further explanations are made publicly available on GitLab. The suggested cleaning will allow global users to work with more consistent data for the development of machine learning tools without being an expert. In addition, it highlights some of the challenges when working with clinical multi-center data and includes recommendations for similar future initiatives.

Abstract 1431: Sprouty 2 expression attenuates proliferation in nras-driven acute myeloid leukemia cell lines

Oncogenic mutations in the NRAS gene are found in many cancers including a subset of acute myeloid leukemias (AML). Established AML cell lines exhibiting hyperactive signaling through the RAS-RAF-MEK-ERK pathway show constitutive ERK activation generating a transcriptome that mediates escape from programmed cell death and continuous proliferation. It has been established that exposure of many AML cell lines to phorbol esters such as phorbol-12-myristate-13-acetate (PMA) mediates cell cycle arrest, myeloid differentiation, and apoptosis. This effect seems counterintuitive given that PMA irreversibly activates protein kinase C (PKC), which enhances ERK activity leading to transcriptional upregulation of target genes controlled by ERK activated transcription factors, many of which promote proliferation. Here we define a set of PMA response genes in AML cell lines driven by oncogenic NRAS that encode negative regulators of RAS-RAF-MEK-ERK signaling, including SPRY2, RASA1, DUSP 5, and DUSP6. Additionally, we show that overexpression of SPRY2 alone attenuates proliferation by inhibiting ERK activation and altering the AML cell transcriptome through the activation of genes encoding members of the AP-1 transcription factor family, FOS, JUNB, and JUND, and the cyclin-CDK inhibitors CDKN1A and CDKN2B. We hypothesize that oncogenic NRAS signaling is overridden by PMA treatment through the activation of ERK target genes that ultimately inhibit the MAPK-ERK pathway, such as SPRY2. Finally, we show that SPRY 2 expression in AML patient samples represents a survival prognostic indicator where higher expression levels correlate with improved overall survival.

Citation Format: Michael Roberts, Sher Bahadur, Coltin Albitz, Jae Chung, Samantha Garcia, Cuong Nguyen, Sophia Kovatsis. Sprouty 2 expression attenuates proliferation in nras-driven acute myeloid leukemia cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1431.

Balancing the management of powerline right-of-way corridors for humans and nature

Green space in electric powerline rights of way (ROWs) can be a source of both ecosystem services and disservices in developed landscapes. Vegetation management within the ROW may influence tradeoffs that maximize potential services or disservices. Frequently mowed ROWs managed as lawn harbor less biodiversity than ROWs with taller vegetation, but may be preferred by people for aesthetic reasons and because they provide space for recreational activities. We conducted a survey of residents living by ROWs in the Chicago, Illinois USA metropolitan area to determine if residents prefer ROWs managed as lawn over those managed as native prairies or allowed to grow freely with only woody vegetation removed ("old-field ROWs"). We found that respondents did not prefer mowed over prairie or old-field ROWs. Furthermore, respondents living near mowed ROWs were least likely to think that the ROW is attractive, while those living near prairie ROWs were most likely to. Survey respondents tended to believe it was important for ROWs to provide habitat for wildlife, and wildlife observation was the most frequently reported activity conducted in the ROW. Finally, we found that a respondent's perception of biodiversity in the ROW was more closely correlated with positive feelings about the ROW than measured biodiversity levels. Our results suggest that managing ROWs for wildlife habitat is fully compatible with managing them for human enjoyment. We therefore recommend that where possible, ROW vegetation is managed in a more "natural" way than lawn because it has the potential to benefit both wildlife and people.

Perspectives of Dermatology Program Directors on the Impact of Step 1 Pass/Fail

INTRODUCTION

The shift of Step 1 to Pass/Fail has generated several questions and concerns about obtaining residency positions among allopathic and osteopathic students alike. Determining the perspectives of Dermatology Program Directors in regards to post-Step 1 Pass/Fail is critical for students to better prepare for matching into dermatology.

METHODS

After receiving Institutional Review Board (IRB) exemption status, the program directors were chosen from 144 Accreditation Council for Graduate Medical Education (ACGME) and 27 American Osteopathic Association (AOA) Dermatology programs using contact information from their respective online website databases. An eight-item survey was constructed on a three-point Likert scale, one free text response, and four demographic questions. The anonymous survey was sent out over the course of three weeks with weekly individualized reminder requests for participation.

RESULTS

A total of 54.54% of responders had "Letters of Recommendation" in their top 3. Forty-five percent of responders had "Completed Audition Rotation at Program" in their top 3. And, 38.09% of responders had "USMLE Step 2 CK Scores" in their top 3.

CONCLUSION

Approximately 50% of responders agreed that all medical students will have more difficulty matching dermatology. Based on the survey study, Dermatology program directors want to focus more on letters of recommendation, audition rotations, and Step 2 CK scores. Because each field seems to prioritize different aspects of an application, students should attempt to gain as much exposure to different fields such as through research and shadowing to narrow down their ideal specialties. Consequently, the student will have more time to tailor their applications to what residency admissions are looking for.

Professional identity formation: linking meaning to well-being

Trainee distress and burnout continue to be serious concerns for educational programs in medicine, prompting the implementation of numerous interventions. Although an expansive body of literature suggests that the experience of meaning at work is critical to professional wellbeing, relatively little attention has been paid to how this might be leveraged in the educational milieu. We propose that professional identity formation (PIF), the process by which trainees come to not only attain competence, but additionally to "think, act and feel" like physicians, affords us a unique opportunity to ground trainees in the meaningfulness of their work. Using the widely accepted tri-partite model of meaning, we outline how this process can contribute to wellbeing. We suggest strategies to optimize the influence of PIF on wellbeing, offering curricular suggestions, as well as ideas regarding the respective roles of communities of practice, teachers, and formative educational experiences. Collectively, these encourage trainees to act as intentional agents in the making of their novel professional selves, anchoring them to the meaningfulness of their work, and supporting their short and long-term wellbeing.

Variation in blubber cortisol levels in a recovering humpback whale population inhabiting a rapidly changing environment

Glucocorticoids are regularly used as biomarkers of relative health for individuals and populations. Around the Western Antarctic Peninsula (WAP), baleen whales have and continue to experience threats, including commercial harvest, prey limitations and habitat change driven by rapid warming, and increased human presence via ecotourism. Here, we measured demographic variation and differences across the foraging season in blubber cortisol levels of humpback whales (Megaptera novaeangliae) over two years around the WAP. Cortisol concentrations were determined from 305 biopsy samples of unique individuals. We found no significant difference in the cortisol concentration between male and female whales. However, we observed significant differences across demographic groups of females and a significant decrease in the population across the feeding season. We also assessed whether COVID-19-related reductions in tourism in 2021 along the WAP correlated with lower cortisol levels across the population. The decline in vessel presence in 2021 was associated with a significant decrease in humpback whale blubber cortisol concentrations at the population level. Our findings provide critical contextual data on how these hormones vary naturally in a population over time, show direct associations between cortisol levels and human presence, and will enable comparisons among species experiencing different levels of human disturbance.

Multicenter validation of a machine learning phase space electro-mechanical pulse wave analysis to predict elevated left ventricular end diastolic pressure at the point-of-care

BACKGROUND

Phase space is a mechanical systems approach and large-scale data representation of an object in 3-dimensional space. Whether such techniques can be applied to predict left ventricular pressures non-invasively and at the point-of-care is unknown.

OBJECTIVE

This study prospectively validated a phase space machine-learned approach based on a novel electro-mechanical pulse wave method of data collection through orthogonal voltage gradient (OVG) and photoplethysmography (PPG) for the prediction of elevated left ventricular end diastolic pressure (LVEDP).

METHODS

Consecutive outpatients across 15 US-based healthcare centers with symptoms suggestive of coronary artery disease were enrolled at the time of elective cardiac catheterization and underwent OVG and PPG data acquisition immediately prior to angiography with signals paired with LVEDP (IDENTIFY; NCT #03864081). The primary objective was to validate a ML algorithm for prediction of elevated LVEDP using a definition of ≥25 mmHg (study cohort) and normal LVEDP ≤ 12 mmHg (control cohort), using AUC as the measure of diagnostic accuracy. Secondary objectives included performance of the ML predictor in a propensity matched cohort (age and gender) and performance for an elevated LVEDP across a spectrum of comparative LVEDP (<12 through 24 at 1 mmHg increments). Features were extracted from the OVG and PPG datasets and were analyzed using machine-learning approaches.

RESULTS

The study cohort consisted of 684 subjects stratified into three LVEDP categories, ≤12 mmHg (N = 258), LVEDP 13-24 mmHg (N = 347), and LVEDP ≥25 mmHg (N = 79). Testing of the ML predictor demonstrated an AUC of 0.81 (95% CI 0.76-0.86) for the prediction of an elevated LVEDP with a sensitivity of 82% and specificity of 68%, respectively. Among a propensity matched cohort (N = 79) the ML predictor demonstrated a similar result AUC 0.79 (95% CI: 0.72-0.8). Using a constant definition of elevated LVEDP and varying the lower threshold across LVEDP the ML predictor demonstrated and AUC ranging from 0.79-0.82.

CONCLUSION

The phase space ML analysis provides a robust prediction for an elevated LVEDP at the point-of-care. These data suggest a potential role for an OVG and PPG derived electro-mechanical pulse wave strategy to determine if LVEDP is elevated in patients with symptoms suggestive of cardiac disease.

A How to Guide: Clinical Population Test Development and Authorization of MALDI-ToF Mass Spectrometry-Based Screening Tests for Viral Infections

Applying MALDI-ToF mass spectrometry as a clinical diagnostic test for viruses is different from that of bacteria, fungi and other micro-organisms. This is because the systems biology of viral infections, the size and chemical nature of specific viral proteins and the mass spectrometry biophysics of how they are quantitated are fundamentally different. The analytical challenges to overcome when developing a clinical MALDI-ToF mass spectrometry tests for a virus, particularly human pathogenic enveloped viruses, are sample enrichment, virus envelope disruption, optimal matrix formulation, optimal MALDI ToF MS performance and optimal spectral data processing/bioinformatics. Primarily, the instrument operating settings have to be optimized to match the nature of the viral specific proteins, which are not compatible with setting established when testing for bacterial and many other micro-organisms. The capacity to be a viral infection clinical diagnostic instrument often stretches current mass spectrometers to their operational design limits. Finally, all the associated procedures, from sample collection to data analytics, for the technique have to meet the legal and operational requirement for often high-throughput clinical testing. Given the newness of the technology, clinical MALDI ToF mass spectrometry does not fit in with standard criteria applied by regulatory authorities whereby numeric outputs are compared directly to similar technology tests that have already been authorized for use. Thus, CLIA laboratory developed test (LDT) criteria have to be applied. This article details our experience of developing a SAR-CoV-2 MALDI-ToF MS test suitable for asymptomatic carrier infection population screening.

Development and validation of a machine learned algorithm to IDENTIFY functionally significant coronary artery disease

Introduction

Multiple trials have demonstrated broad performance ranges for tests attempting to detect coronary artery disease. The most common test, SPECT, requires capital-intensive equipment, the use of radionuclides, induction of stress, and time off work and/or travel. Presented here are the development and clinical validation of an office-based machine learned algorithm to identify functionally significant coronary artery disease without radiation, expensive equipment or induced patient stress.

Materials and methods

The IDENTIFY trial (NCT03864081) is a prospective, multicenter, non-randomized, selectively blinded, repository study to collect acquired signals paired with subject meta-data, including outcomes, from subjects with symptoms of coronary artery disease. Time synchronized orthogonal voltage gradient and photoplethysmographic signals were collected for 230 seconds from recumbent subjects at rest within seven days of either left heart catheterization or coronary computed tomography angiography. Following machine learning on a proportion of these data (N = 2,522), a final algorithm was selected, along with a pre-specified cut point on the receiver operating characteristic curve for clinical validation. An unseen set of subject signals (N = 965) was used to validate the algorithm.

Results

At the pre-specified cut point, the sensitivity for detecting functionally significant coronary artery disease was 0.73 (95% CI: 0.68–0.78), and the specificity was 0.68 (0.62–0.74). There exists a point on the receiver operating characteristic curve at which the negative predictive value is the same as coronary computed tomographic angiography, 0.99, assuming a disease incidence of 0.04, yielding sensitivity of 0.89 and specificity of 0.42. Selecting a point at which the positive predictive value is maximized, 0.12, yields sensitivity of 0.39 and specificity of 0.88.

Conclusion

The performance of the machine learned algorithm presented here is comparable to common tertiary center testing for coronary artery disease. Employing multiple cut points on the receiver operating characteristic curve can yield the negative predictive value of coronary computed tomographic angiography and a positive predictive value approaching that of myocardial perfusion imaging. As such, a system employing this algorithm may address the need for a non-invasive, no radiation, no stress, front line test, and hence offer significant advantages to the patient, their physician, and healthcare system.

CSF/plasma levels, transthyretin stabilisation and safety of multiple doses of tolcapone in subjects with hereditary ATTR amyloidosis

PURPOSE

To investigate the effect of tolcapone on cerebrospinal fluid (CSF) transthyretin (TTR) tetramer stability in patients with hereditary transthyretin (ATTRv) amyloidosis.

METHODS

A total of 9 patients were enrolled in the study (3 men, 50.3 ± 14.4 years old). Three patients had central nervous system (CNS) involvement. Patients were assigned to receive tolcapone 300 mg/day or 600 mg/day for 7 days. Plasma and CSF were collected at baseline and 2 h after the final tolcapone dose.

RESULTS

The mean CSF tolcapone and 3-O-Methyltolcapone (3-OMT) concentration were 39.4 ± 36.3 ng/mL and 26.0 ± 4.9 ng/mL, respectively, after 7 days of tolcapone dosing. Tolcapone and 3-OMT were detected in the CSF of patients with or without CNS symptoms. The mean total study drug (tolcapone + 3-OMT) to TTR molar ratio in CSF was 1.15 ± 0.59. Orally administered tolcapone significantly increased CSF TTR concentration and decreased monomer content under semi-denaturing conditions. Eight adverse events (AEs) were reported in 6 patients. All AEs were mild in severity and resolved.

CONCLUSIONS

Tolcapone was able to cross the blood brain-barrier, highlighting its potential to decrease CNS manifestations of ATTRv amyloidosis. Tolcapone was well tolerated by patients with ATTRv amyloidosis.

Does Vitamin D Deficiency Contribute to COVID-19 Severity?

Objectives

In this systematic review, we assessed studies that probed at vitamin D deficiencies in both positive and negative COVID-19 cases. We compared vitamin D levels to see if there was a noticeable difference. Finally, through the review of several studies, we investigated whether more severe cases of COVID-19 were correlated with low vitamin D levels.

Methods

The mean and standard deviations of the vitamin D levels in patients who tested positive and negative for COVID-19 were analyzed. We used Practical Meta-Analysis Effect Size Calculator developed by David B. Wilson, Ph.D., George Mason University when looking at COVID-19 status and vitamin D (N = 50–80 nmol/L) deficient levels. In this systematic review, we measured mean, standard deviations, and 95% CI of many studies to determine if there is a consistent relationship between vitamin D levels and COVID-19. We also performed an independent sample t-test comparing non-survivors vs. survivors of COVID-19 and vitamin D levels, and when comparing moderate vs. severe COVID-19 symptoms and vitamin D levels.

Results

A few studies were compared to evaluate the difference in vitamin D levels (serum 25(OH)D, nmol/L) among those who tested positive for COVID-19 to those who tested negative. It was found that the average median serum 25(OH)D, nmol/L for patients who tested positive was 27.08 nmol/L (±0.58 SD, 95% CI: 1.88) and the average median of serum 25(OH)D, nmol/L for patients who tested negative was 48.67 nmol/L (±13.66 SD, 95% CI: 2.17) this difference was near significant (p = .059). When looking at the relationship between vitamin D levels and severity of COVID-19 progression the result was not statistically significant, t(df) = 0.84, p = .216. When comparing the average values of vitamin D level among those who survived COVID-19 vs. those who did not, the results were not statistically significant, t(269) = 0.17, p = .438.

Conclusions

It is apparent that there is a trend found in relationships among those who test positive for COVID-19 and their vitamin D levels. There seems to be a correlation between vitamin D deficiency and likelihood of developing severe illness of COVID-19 when observing studies individually. However, when comparing studies on a larger scale it seems that the significant difference seems to fade.

Funding Sources

None.

POS1495-HPR COVID-19, INFLUENZA AND PNEUMOCOCCUS VACCINATION UPTAKE IN PATIENTS WITH RHEUMATIC DISEASE: A PROSPECTIVE AUDIT

Background

Patients with autoimmune inflammatory rheumatic diseases are susceptible to infections. This could be attributed to theimmunosuppressive effect of the underlying condition or the use of immunomodulatory medications. According to the Department of Health guidelines inthe UK and the European League Against Rheumatism (EULAR), patients who are immunosuppressed should be vaccinated against influenza and pneumococcal infection, as well as COVID-19 infection.

Objectives

Our aim was to explore the Pneumococcal, Influenza and COVID-19 vaccination uptake of our patients with different autoimmune inflammatory rheumatological conditions. In addition, to assess the side effects profile and the status of their underlying rheumatological diseases following COVID-19 vaccination.

Methods

We undertook a prospective audit of consecutive patients with regards to their vaccination update for influenza, pneumococcus, and COVID-19, utilizing a standard questionnaire and compared the results to our 2017 data.

Results

Some 81% of patients received the influenza vaccination (compared to 47% in 2017) representing a 172% improvement, p<0.001. Some 53% received the pneumococcus vaccination compared to 28% in 2017, indicating a 185% improvement, p=0.003. With regards to COVID-19 vaccination, 98/101(97%) of eligible patients received at least one dose and 66% received two doses. 47% received Astra Zeneca, 52% Pfizer and 1% unsure. 46% of patients mentioned, no one specifically discussed the COVID vaccine with them - got information via SMS/ from media, However, 37% of patients were informed by GP Doctor/ Nurse, 14% from the person giving the vaccine, and 7% from specialist hospital doctor. Safety concerns were indicated by all 3 patients who deferred vaccination.

Most side-effects were observed following the first dose (74 patients) vs. the second dose (13 patients) and were mainly mild (66%), but also moderate (19%) and severe (15%). The sore arm was the commonest side-effect, whilst the majority of side-effects resolved within two days. Crucially, 28% reported a flare of the rheumatological condition following the vaccination. No patients receiving at least one dose were diagnosed with COVID-19 infection subsequently.

Conclusion

Vaccination rates for influenza and pneumococcus have improved substantially since 2017, although the population with rheumatic diseases still has low uptake in pneumococcal vaccination. The COVID-19 vaccination uptake has been extremely high in this cohort.

Disclosure of Interests

None declared

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions

Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse single modality multicentre datasets. However, these surveys rarely focused on evaluation metrics and lacked a checklist for computational data harmonisation studies. In this systematic review, we summarise the computational data harmonisation approaches for multi-modality data in the digital healthcare field, including harmonisation strategies and evaluation metrics based on different theories. In addition, a comprehensive checklist that summarises common practices for data harmonisation studies is proposed to guide researchers to report their research findings more effectively. Last but not least, flowcharts presenting possible ways for methodology and metric selection are proposed and the limitations of different methods have been surveyed for future research.

Practical application of international recommendations and safety standards in the systematic planning and implementation of remediation of sites or areas with residual radioactive material

The IAEA fundamental safety objective is'to protect people and the environment from harmful effects of ionizing radiation'and this must be done 'without unduly limiting the operation of facilities or the conduct of activities that give rise to radiation risks', while ensuring that people and the environment, present and future are protected against radiation risks (IAEA 2006Fundamental Safety Principles, Safety FundamentalsNo. SF-1). In addition,'protective actions to reduce existing or unregulated radiation risks must be justified and optimized'(IAEA 2006Fundamental Safety Principles, Safety FundamentalsNo. SF-1). An international system of radiological protection can be applied such that processes, such as remediation, can be systematically undertaken to address the wide range of'existing exposure situations'present globally. In doing so, decisions made regarding actions undertaken can be demonstrated to be'justified'and'optimized'(i.e. balanced), such that the amount of effort should be commensurate with the risk (applying a'graded approach'). In addition, protection of people and the environment can be demonstrated by comparing the actual exposure to appropriate criteria over the lifetime of remediation. This paper provides an overview of the current IAEA safety standards on remediation of sites or areas contaminated with residual radioactive material within the international system of radiological protection and provides practical examples of their application through case studies considered in IAEA international model validation programs.

Erratum: Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence

[This corrects the article DOI: 10.1038/s42256-021-00421-z.].

Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review

OBJECTIVES

We systematically reviewed the current literature evaluating the ability of fully-automated deep learning (DL) and semi-automated traditional machine learning (TML) MRI-based artificial intelligence (AI) methods to differentiate clinically significant prostate cancer (csPCa) from indolent PCa (iPCa) and benign conditions.

METHODS

We performed a computerised bibliographic search of studies indexed in MEDLINE/PubMed, arXiv, medRxiv, and bioRxiv between 1 January 2016 and 31 July 2021. Two reviewers performed the title/abstract and full-text screening. The remaining papers were screened by four reviewers using the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) for DL studies and Radiomics Quality Score (RQS) for TML studies. Papers that fulfilled the pre-defined screening requirements underwent full CLAIM/RQS evaluation alongside the risk of bias assessment using QUADAS-2, both conducted by the same four reviewers. Standard measures of discrimination were extracted for the developed predictive models.

RESULTS

17/28 papers (five DL and twelve TML) passed the quality screening and were subject to a full CLAIM/RQS/QUADAS-2 assessment, which revealed a substantial study heterogeneity that precluded us from performing quantitative analysis as part of this review. The mean RQS of TML papers was 11/36, and a total of five papers had a high risk of bias. AUCs of DL and TML papers with low risk of bias ranged between 0.80-0.89 and 0.75-0.88, respectively.

CONCLUSION

We observed comparable performance of the two classes of AI methods and identified a number of common methodological limitations and biases that future studies will need to address to ensure the generalisability of the developed models.

Sleep deprivation is associated with increased circulating levels of endogenous ouabain: Potential role in bipolar disorder

Endogenously produced cardiac glycosides, like endogenous ouabain (EO), are putative hormones that have been implicated in the pathophysiology of bipolar disorder. Individuals with bipolar disorder appear to be unable to sufficiently upregulate production of EO in situations of increased need. This study was performed to determine the effect of sleep deprivation on the circulating levels of EO. Plasma EO concentrations were measured by ouabain-radioimmunoassay in heterozygote Na,K-ATPase a2 knockout (KO) mice, which have been used as an animal model of mania, and wildtype siblings at baseline and after sleep fragmentation utilizing the moving bar method. a2 KO animals had elevated endogenous ouabain concentrations compared to wild type controls (0.82 ± SD 0.22 nM vs 0.26 ± 0.02, P = 0.03). Sleep fragmentation increased ouabain concentrations in wild type mice (0.53 ± 0.08 nM sleep fragmentation vs 0.26 ± 0.02 nM baseline, P = 0.04), but not in a2 KO mice (0.60 ± 0.07 nM sleep fragmentation vs 0.82 ± 0.22 nM baseline, P > 0.05). These studies demonstrate that sleep disturbance can increase EO in control mice but animals that exhibit some manic behaviors are unable to increase EO production.

A highly virulent variant of HIV-1 circulating in the Netherlands

We discovered a highly virulent variant of subtype-B HIV-1 in the Netherlands. One hundred nine individuals with this variant had a 0.54 to 0.74 log₁₀ increase (i.e., a ~3.5-fold to 5.5-fold increase) in viral load compared with, and exhibited CD4 cell decline twice as fast as, 6604 individuals with other subtype-B strains. Without treatment, advanced HIV-CD4 cell counts below 350 cells per cubic millimeter, with long-term clinical consequences-is expected to be reached, on average, 9 months after diagnosis for individuals in their thirties with this variant. Age, sex, suspected mode of transmission, and place of birth for the aforementioned 109 individuals were typical for HIV-positive people in the Netherlands, which suggests that the increased virulence is attributable to the viral strain. Genetic sequence analysis suggests that this variant arose in the 1990s from de novo mutation, not recombination, with increased transmissibility and an unfamiliar molecular mechanism of virulence.

Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence

Artificial intelligence provides a promising solution for streamlining COVID-19 diagnoses; however, concerns surrounding security and trustworthiness impede the collection of large-scale representative medical data, posing a considerable challenge for training a well-generalized model in clinical practices. To address this, we launch the Unified CT-COVID AI Diagnostic Initiative (UCADI), where the artificial intelligence (AI) model can be distributedly trained and independently executed at each host institution under a federated learning framework without data sharing. Here we show that our federated learning framework model considerably outperformed all of the local models (with a test sensitivity/specificity of 0.973/0.951 in China and 0.730/0.942 in the United Kingdom), achieving comparable performance with a panel of professional radiologists. We further evaluated the model on the hold-out (collected from another two hospitals without the federated learning framework) and heterogeneous (acquired with contrast materials) data, provided visual explanations for decisions made by the model, and analysed the trade-offs between the model performance and the communication costs in the federated training process. Our study is based on 9,573 chest computed tomography scans from 3,336 patients collected from 23 hospitals located in China and the United Kingdom. Collectively, our work advanced the prospects of utilizing federated learning for privacy-preserving AI in digital health.

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence

Artificial intelligence (AI) provides a promising substitution for streamlining COVID-19 diagnoses. However, concerns surrounding security and trustworthiness impede the collection of large-scale representative medical data, posing a considerable challenge for training a well-generalised model in clinical practices. To address this, we launch the Unified CT-COVID AI Diagnostic Initiative (UCADI), where the AI model can be distributedly trained and independently executed at each host institution under a federated learning framework (FL) without data sharing. Here we show that our FL model outperformed all the local models by a large yield (test sensitivity /specificity in China: 0.973/0.951, in the UK: 0.730/0.942), achieving comparable performance with a panel of professional radiologists. We further evaluated the model on the hold-out (collected from another two hospitals leaving out the FL) and heterogeneous (acquired with contrast materials) data, provided visual explanations for decisions made by the model, and analysed the trade-offs between the model performance and the communication costs in the federated training process. Our study is based on 9,573 chest computed tomography scans (CTs) from 3,336 patients collected from 23 hospitals located in China and the UK. Collectively, our work advanced the prospects of utilising federated learning for privacy-preserving AI in digital health.

Resisted adduction sit-up test (RASUT) as a screening tool for pelvic versus hip pathology

Groin pain is a common symptom in hip and pelvic pathology and differentiating between the two remains a challenge. The purpose of this study was to examine whether a test combining resisted adduction with a sit-up (RASUT) differentiates between pelvic and hip pathology. The RASUT was performed on 160 patients with complaints of hip or groin pain who subsequently had their diagnosis confirmed by magnetic resonance imaging (MRI) or surgery. Patients were categorized as having pelvic pathology (athletic pubalgia or other) or hip pathology (intra-articular or other). Athletic pubalgia was defined as any condition involving the disruption of the pubic aponeurotic plate. Sensitivity, specificity, positive predictive accuracy, negative predictive accuracy and diagnostic odds ratios were computed. Seventy-one patients had pelvic pathology (40 athletic pubalgia), 81 had hip pathology and 8 had both. The RASUT was effective in differentiating pelvic from hip pathology; 50 of 77 patients with a positive RASUT had pelvic pathology versus 29 of 83 patients with a negative test (P < 0.001). RASUT was diagnostic for athletic pubalgia (diagnostic odds ratio 6.08, P < 0.001); 35 of 45 patients with athletic pubalgia had a positive RASUT (78% sensitivity) and 73 of 83 patients with a negative RASUT did not have athletic pubalgia (88% negative predictive accuracy). The RASUT can be used to differentiate pelvic from hip pathology and to identify patients without athletic pubalgia. This is a valuable screening tool in the armamentarium of the sports medicine clinician.

Case Series of Perioral Dermatitis Caused by Improper Use of Activated Oxygen

BACKGROUND

Activated oxygen is an important chemical for disinfecting surfaces. In the last 10 years, it has become increasingly common in continuous positive airway pressure (CPAP) devices.

OBJECTIVE

We sought to treat three cases of perioral dermatitis with concomitant use of CPAP devices.

METHODS

Three patients presented to the clinic with the complaint of a burning and stinging skin irritation involving the bilateral malar cheeks. Physical exam revealed symmetric, scaling, well-demarcated, erythematous, and slightly indurated areas of skin involving the bilateral malar cheeks. Corticosteroids were prescribed and provided little relief. In all three cases, the CPAP masks were worn within one hour of completing the sanitizing cycle. Each patient was instructed to lengthen the time between completion of the sanitizing cycle and application of the mask to a minimum of four hours.

RESULTS

All patients had resolution of their symptoms within two weeks of the modification, measured by subjective resolution and photodocumentation with resolution of erythema and scaling.

CONCLUSION

Ozone follows common gas laws such that its decay time can be considered in terms of half-life. Ozone requires approximately 1,524 minutes (25.4 hours) to decay one-half life when other factors are controlled. The activated oxygen containers are a fixed environment that could be causing increased O₃ residue on the CPAP machines. The residual O₃ reacts with the natural oils on the insdividual's skin to cause perioral dermatitis.

Protect Our Kids: a novel program bringing hemorrhage control to schools

Background

Following the shooting at Sandy Hook Elementary School, the Hartford Consensus produced the Stop the Bleed program to train bystanders in hemorrhage control. In our region, the police bureau delivers critical incident training to public schools, offering instruction in responding to violent or dangerous situations. Until now, widespread training in hemorrhage control has been lacking. Our group developed, implemented and evaluated a novel program integrating hemorrhage control into critical incident training for school staff in order to blunt the impact of mass casualty events on children.

Methods

The staff of 25 elementary and middle schools attended a 90-minute course incorporating Stop the Bleed into the critical incident training curriculum, delivered on-site by police officers, nurses and doctors over a three-day period. The joint program was named Protect Our Kids. At the conclusion of the course, hemorrhage control kits and educational materials were provided and a four-question survey to assess the quality of training using a ten-point Likert scale was completed by participants and trainers.

Results

One thousand eighteen educators underwent training. A majority were teachers (78.2%), followed by para-educators (5.8%), counselors (4.4%) and principals (2%). Widely covered by local and state media, the Protect Our Kids program was rated as excellent and effective by a majority of trainees and all trainers rated the program as excellent.

Conclusions

Through collaboration between trauma centers, police and school systems, a large-scale training program for hemorrhage control and critical incident response can be effectively delivered to schools.