Crystal Structure of a Full-Length Human Tetraspanin Reveals a Cholesterol-Binding Pocket.

Tetraspanins comprise a diverse family of four-pass transmembrane proteins that play critical roles in the immune, reproductive, genitourinary, and auditory systems. Despite their pervasive roles in human physiology, little is known about the structure of tetraspanins or the molecular mechanisms underlying their various functions. Here, we report the crystal structure of human CD81, a full-length tetraspanin. The transmembrane segments of CD81 pack as two largely separated pairs of helices, capped by the large extracellular loop (EC2) at the outer membrane leaflet. The two pairs of helices converge at the inner leaflet to create an intramembrane pocket with additional electron density corresponding to a bound cholesterol molecule within the cavity. Molecular dynamics simulations identify an additional conformation in which EC2 separates substantially from the transmembrane domain. Cholesterol binding appears to modulate CD81 activity in cells, suggesting a potential mechanism for regulation of tetraspanin function.

Enterococci enhance Clostridioides difficile pathogenesis.

Enteric pathogens are exposed to a dynamic polymicrobial environment in the gastrointestinal tract1. This microbial community has been shown to be important during infection, but there are few examples illustrating how microbial interactions can influence the virulence of invading pathogens2. Here we show that expansion of a group of antibiotic-resistant, opportunistic pathogens in the gut-the enterococci-enhances the fitness and pathogenesis of Clostridioides difficile. Through a parallel process of nutrient restriction and cross-feeding, enterococci shape the metabolic environment in the gut and reprogramme C. difficile metabolism. Enterococci provide fermentable amino acids, including leucine and ornithine, which increase C. difficile fitness in the antibiotic-perturbed gut. Parallel depletion of arginine by enterococci through arginine catabolism provides a metabolic cue for C. difficile that facilitates increased virulence. We find evidence of microbial interaction between these two pathogenic organisms in multiple mouse models of infection and patients infected with C. difficile. These findings provide mechanistic insights into the role of pathogenic microbiota in the susceptibility to and the severity of C. difficile infection.

A putative de novo evolved gene required for spermatid chromatin condensation in Drosophila melanogaster.

Comparative genomics has enabled the identification of genes that potentially evolved de novo from non-coding sequences. Many such genes are expressed in male reproductive tissues, but their functions remain poorly understood. To address this, we conducted a functional genetic screen of over 40 putative de novo genes with testis-enriched expression in Drosophila melanogaster and identified one gene, atlas, required for male fertility. Detailed genetic and cytological analyses showed that atlas is required for proper chromatin condensation during the final stages of spermatogenesis. Atlas protein is expressed in spermatid nuclei and facilitates the transition from histone- to protamine-based chromatin packaging. Complementary evolutionary analyses revealed the complex evolutionary history of atlas. The protein-coding portion of the gene likely arose at the base of the Drosophila genus on the X chromosome but was unlikely to be essential, as it was then lost in several independent lineages. Within the last ~15 million years, however, the gene moved to an autosome, where it fused with a conserved non-coding RNA and evolved a non-redundant role in male fertility. Altogether, this study provides insight into the integration of novel genes into biological processes, the links between genomic innovation and functional evolution, and the genetic control of a fundamental developmental process, gametogenesis.

Priorities and Progress in Gram-positive Bacterial Infection Research by the Antibacterial Resistance Leadership Group: A Narrative Review.

The Antibacterial Resistance Leadership Group (ARLG) has prioritized infections caused by gram-positive bacteria as one of its core areas of emphasis. The ARLG Gram-positive Committee has focused on studies responding to 3 main identified research priorities: (1) investigation of strategies or therapies for infections predominantly caused by gram-positive bacteria, (2) evaluation of the efficacy of novel agents for infections caused by methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci, and (3) optimization of dosing and duration of antimicrobial agents for gram-positive infections. Herein, we summarize ARLG accomplishments in gram-positive bacterial infection research, including studies aiming to (1) inform optimal vancomycin dosing, (2) determine the role of dalbavancin in MRSA bloodstream infection, (3) characterize enterococcal bloodstream infections, (4) demonstrate the benefits of short-course therapy for pediatric community-acquired pneumonia, (5) develop quality of life measures for use in clinical trials, and (6) advance understanding of the microbiome. Future studies will incorporate innovative methodologies with a focus on interventional clinical trials that have the potential to change clinical practice for difficult-to-treat infections, such as MRSA bloodstream infections.

Using deep learning-derived image features in radiologic time series to make personalised predictions: proof of concept in colonic transit data.

OBJECTIVES: Siamese neural networks (SNN) were used to classify the presence of radiopaque beads as part of a colonic transit time study (CTS). The SNN output was then used as a feature in a time series model to predict progression through a CTS. METHODS: This retrospective study included all patients undergoing a CTS in a single institution from 2010 to 2020. Data were partitioned in an 80/20 Train/Test split. Deep learning models based on a SNN architecture were trained and tested to classify images according to the presence, absence, and number of radiopaque beads and to output the Euclidean distance between the feature representations of the input images. Time series models were used to predict the total duration of the study. RESULTS: In total, 568 images of 229 patients (143, 62% female, mean age 57) patients were included. For the classification of the presence of beads, the best performing model (Siamese DenseNET trained with a contrastive loss with unfrozen weights) achieved an accuracy, precision, and recall of 0.988, 0.986, and 1. A Gaussian process regressor (GPR) trained on the outputs of the SNN outperformed both GPR using only the number of beads and basic statistical exponential curve fitting with MAE of 0.9 days compared to 2.3 and 6.3 days (p < 0.05) respectively. CONCLUSIONS: SNNs perform well at the identification of radiopaque beads in CTS. For time series prediction our methods were superior at identifying progression through the time series compared to statistical models, enabling more accurate personalised predictions. CLINICAL RELEVANCE STATEMENT: Our radiologic time series model has potential clinical application in use cases where change assessment is critical (e.g. nodule surveillance, cancer treatment response, and screening programmes) by quantifying change and using it to make more personalised predictions. KEY POINTS: • Time series methods have improved but application to radiology lags behind computer vision. Colonic transit studies are a simple radiologic time series measuring function through serial radiographs. • We successfully employed a Siamese neural network (SNN) to compare between radiographs at different points in time and then used the output of SNN as a feature in a Gaussian process regression model to predict progression through the time series. • This novel use of features derived from a neural network on medical imaging data to predict progression has potential clinical application in more complex use cases where change assessment is critical such as in oncologic imaging, monitoring for treatment response, and screening programmes.

Cybersecurity considerations for radiology departments involved with artificial intelligence.

Radiology artificial intelligence (AI) projects involve the integration of integrating numerous medical devices, wireless technologies, data warehouses, and social networks. While cybersecurity threats are not new to healthcare, their prevalence has increased with the rise of AI research for applications in radiology, making them one of the major healthcare risks of 2021. Radiologists have extensive experience with the interpretation of medical imaging data but radiologists may not have the required level of awareness or training related to AI-specific cybersecurity concerns. Healthcare providers and device manufacturers can learn from other industry sector industries that have already taken steps to improve their cybersecurity systems. This review aims to introduce cybersecurity concepts as it relates to medical imaging and to provide background information on general and healthcare-specific cybersecurity challenges. We discuss approaches to enhancing the level and effectiveness of security through detection and prevention techniques, as well as ways that technology can improve security while mitigating risks. We first review general cybersecurity concepts and regulatory issues before examining these topics in the context of radiology AI, with a specific focus on data, training, data, training, implementation, and auditability. Finally, we suggest potential risk mitigation strategies. By reading this review, healthcare providers, researchers, and device developers can gain a better understanding of the potential risks associated with radiology AI projects, as well as strategies to improve cybersecurity and reduce potential associated risks. CLINICAL RELEVANCE STATEMENT: This review can aid radiologists' and related professionals' understanding of the potential cybersecurity risks associated with radiology AI projects, as well as strategies to improve security. KEY POINTS: • Embarking on a radiology artificial intelligence (AI) project is complex and not without risk especially as cybersecurity threats have certainly become more abundant in the healthcare industry. • Fortunately healthcare providers and device manufacturers have the advantage of being able to take inspiration from other industry sectors who are leading the way in the field. • Herein we provide an introduction to cybersecurity as it pertains to radiology, a background to both general and healthcare-specific cybersecurity challenges; we outline general approaches to improving security through both detection and preventative techniques, and instances where technology can increase security while mitigating risks.

DEEP MOVEMENT: Deep learning of movie files for management of endovascular thrombectomy.

OBJECTIVES: Treatment and outcomes of acute stroke have been revolutionised by mechanical thrombectomy. Deep learning has shown great promise in diagnostics but applications in video and interventional radiology lag behind. We aimed to develop a model that takes as input digital subtraction angiography (DSA) videos and classifies the video according to (1) the presence of large vessel occlusion (LVO), (2) the location of the occlusion, and (3) the efficacy of reperfusion. METHODS: All patients who underwent DSA for anterior circulation acute ischaemic stroke between 2012 and 2019 were included. Consecutive normal studies were included to balance classes. An external validation (EV) dataset was collected from another institution. The trained model was also used on DSA videos post mechanical thrombectomy to assess thrombectomy efficacy. RESULTS: In total, 1024 videos comprising 287 patients were included (44 for EV). Occlusion identification was achieved with 100% sensitivity and 91.67% specificity (EV 91.30% and 81.82%). Accuracy of location classification was 71% for ICA, 84% for M1, and 78% for M2 occlusions (EV 73, 25, and 50%). For post-thrombectomy DSA (n = 194), the model identified successful reperfusion with 100%, 88%, and 35% for ICA, M1, and M2 occlusion (EV 89, 88, and 60%). The model could also perform classification of post-intervention videos as mTICI < 3 with an AUC of 0.71. CONCLUSIONS: Our model can successfully identify normal DSA studies from those with LVO and classify thrombectomy outcome and solve a clinical radiology problem with two temporal elements (dynamic video and pre and post intervention). KEY POINTS: • DEEP MOVEMENT represents a novel application of a model applied to acute stroke imaging to handle two types of temporal complexity, dynamic video and pre and post intervention. • The model takes as an input digital subtraction angiograms of the anterior cerebral circulation and classifies according to (1) the presence or absence of large vessel occlusion, (2) the location of the occlusion, and (3) the efficacy of thrombectomy. • Potential clinical utility lies in providing decision support via rapid interpretation (pre thrombectomy) and automated objective gradation of thrombectomy outcomes (post thrombectomy).

COVID vaccine-associated myocarditis in an 8-year-old patient.

COVID vaccine-associated myocarditis was first identified in March 2021. There have been numerous case reports that detail the clinical course of paediatric patients older than age 12 with COVID vaccine-associated myocarditis. There are still very few reports of children between the ages of 5 and 11 with COVID vaccine-associated myocarditis. We present an 8 year- old with COVID vaccine-associated myocarditis after his second vaccination against SARS-CoV-2.

Respiratory Microbiome Disruption and Risk for Ventilator-Associated Lower Respiratory Tract Infection.

BACKGROUND: Ventilator-associated lower respiratory tract infection (VA-LRTI) is common among critically ill patients and has been associated with increased morbidity and mortality. In acute critical illness, respiratory microbiome disruption indices (MDIs) have been shown to predict risk for VA-LRTI, but their utility beyond the first days of critical illness is unknown. We sought to characterize how MDIs previously shown to predict VA-LRTI at initiation of mechanical ventilation change with prolonged mechanical ventilation, and if they remain associated with VA-LRTI risk. METHODS: We developed a cohort of 83 subjects admitted to a long-term acute care hospital due to their prolonged dependence on mechanical ventilation; performed dense, longitudinal sampling of the lower respiratory tract, collecting 1066 specimens; and characterized the lower respiratory microbiome by 16S rRNA sequencing as well as total bacterial abundance by 16S rRNA quantitative polymerase chain reaction. RESULTS: Cross-sectional MDIs, including low Shannon diversity and high total bacterial abundance, were associated with risk for VA-LRTI, but associations had wide posterior credible intervals. Persistent lower respiratory microbiome disruption showed a more robust association with VA-LRTI risk, with each day of (base e) Shannon diversity <2.0 associated with a VA-LRTI odds ratio of 1.36 (95% credible interval, 1.10-1.72). The observed association was consistent across multiple clinical definitions of VA-LRTI. CONCLUSIONS: Cross-sectional MDIs have limited ability to discriminate VA-LRTI risk during prolonged mechanical ventilation, but persistent lower respiratory tract microbiome disruption, best characterized by consecutive days with low Shannon diversity, may identify a population at high risk for infection and may help target infection-prevention interventions.

Stopping Hospital Infections With Environmental Services (SHINE): A Cluster-randomized Trial of Intensive Monitoring Methods for Terminal Room Cleaning on Rates of Multidrug-resistant Organisms in the Intensive Care Unit.

BACKGROUND: Multidrug-resistant organisms (MDROs) frequently contaminate hospital environments. We performed a multicenter, cluster-randomized, crossover trial of 2 methods for monitoring of terminal cleaning effectiveness. METHODS: Six intensive care units (ICUs) at 3 medical centers received both interventions sequentially, in randomized order. Ten surfaces were surveyed each in 5 rooms weekly, after terminal cleaning, with adenosine triphosphate (ATP) monitoring or an ultraviolet fluorescent marker (UV/F). Results were delivered to environmental services staff in real time with failing surfaces recleaned. We measured monthly rates of MDRO infection or colonization, including methicillin-resistant Staphylococcus aureus, Clostridioides difficile, vancomycin-resistant Enterococcus, and MDR gram-negative bacilli (MDR-GNB) during a 12-month baseline period and sequential 6-month intervention periods, separated by a 2-month washout. Primary analysis compared only the randomized intervention periods, whereas secondary analysis included the baseline. RESULTS: The ATP method was associated with a reduction in incidence rate of MDRO infection or colonization compared with the UV/F period (incidence rate ratio [IRR] 0.876; 95% confidence interval [CI], 0.807-0.951; P = .002). Including the baseline period, the ATP method was associated with reduced infection with MDROs (IRR 0.924; 95% CI, 0.855-0.998; P = .04), and MDR-GNB infection or colonization (IRR 0.856; 95% CI, 0.825-0.887; P < .001). The UV/F intervention was not associated with a statistically significant impact on these outcomes. Room turnaround time increased by a median of 1 minute with the ATP intervention and 4.5 minutes with UV/F compared with baseline. CONCLUSIONS: Intensive monitoring of ICU terminal room cleaning with an ATP modality is associated with a reduction of MDRO infection and colonization.

Partial ORF1ab Gene Target Failure with Omicron BA.2.12.1.

Mutations in the genome of SARS-CoV-2 can affect the performance of molecular diagnostic assays. In some cases, such as S-gene target failure, the impact can serve as a unique indicator of a particular SARS-CoV-2 variant and provide a method for rapid detection. Here, we describe partial ORF1ab gene target failure (pOGTF) on the cobas SARS-CoV-2 assays, defined by a ≥2-thermocycle delay in detection of the ORF1ab gene compared to that of the E-gene. We demonstrate that pOGTF is 98.6% sensitive and 99.9% specific for SARS-CoV-2 lineage BA.2.12.1, an emerging variant in the United States with spike L452Q and S704L mutations that may affect transmission, infectivity, and/or immune evasion. Increasing rates of pOGTF closely mirrored rates of BA.2.12.1 sequences uploaded to public databases, and, importantly, increasing local rates of pOGTF also mirrored increasing overall test positivity. Use of pOGTF as a proxy for BA.2.12.1 provides faster tracking of the variant than whole-genome sequencing and can benefit laboratories without sequencing capabilities.

Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE).

OBJECTIVE: There has been a large amount of research in the field of artificial intelligence (AI) as applied to clinical radiology. However, these studies vary in design and quality and systematic reviews of the entire field are lacking.This systematic review aimed to identify all papers that used deep learning in radiology to survey the literature and to evaluate their methods. We aimed to identify the key questions being addressed in the literature and to identify the most effective methods employed. METHODS: We followed the PRISMA guidelines and performed a systematic review of studies of AI in radiology published from 2015 to 2019. Our published protocol was prospectively registered. RESULTS: Our search yielded 11,083 results. Seven hundred sixty-seven full texts were reviewed, and 535 articles were included. Ninety-eight percent were retrospective cohort studies. The median number of patients included was 460. Most studies involved MRI (37%). Neuroradiology was the most common subspecialty. Eighty-eight percent used supervised learning. The majority of studies undertook a segmentation task (39%). Performance comparison was with a state-of-the-art model in 37%. The most used established architecture was UNet (14%). The median performance for the most utilised evaluation metrics was Dice of 0.89 (range .49-.99), AUC of 0.903 (range 1.00-0.61) and Accuracy of 89.4 (range 70.2-100). Of the 77 studies that externally validated their results and allowed for direct comparison, performance on average decreased by 6% at external validation (range increase of 4% to decrease 44%). CONCLUSION: This systematic review has surveyed the major advances in AI as applied to clinical radiology. KEY POINTS: • While there are many papers reporting expert-level results by using deep learning in radiology, most apply only a narrow range of techniques to a narrow selection of use cases. • The literature is dominated by retrospective cohort studies with limited external validation with high potential for bias. • The recent advent of AI extensions to systematic reporting guidelines and prospective trial registration along with a focus on external validation and explanations show potential for translation of the hype surrounding AI from code to clinic.

Diverse GPCRs exhibit conserved water networks for stabilization and activation.

G protein-coupled receptors (GPCRs) have evolved to recognize incredibly diverse extracellular ligands while sharing a common architecture and structurally conserved intracellular signaling partners. It remains unclear how binding of diverse ligands brings about GPCR activation, the common structural change that enables intracellular signaling. Here, we identify highly conserved networks of water-mediated interactions that play a central role in activation. Using atomic-level simulations of diverse GPCRs, we show that most of the water molecules in GPCR crystal structures are highly mobile. Several water molecules near the G protein-coupling interface, however, are stable. These water molecules form two kinds of polar networks that are conserved across diverse GPCRs: (i) a network that is maintained across the inactive and the active states and (ii) a network that rearranges upon activation. Comparative analysis of GPCR crystal structures independently confirms the striking conservation of water-mediated interaction networks. These conserved water-mediated interactions near the G protein-coupling region, along with diverse water-mediated interactions with extracellular ligands, have direct implications for structure-based drug design and GPCR engineering.

Psychiatry is essential for now but might eventually disappear (although this is unlikely to happen any time soon).

OBJECTIVE: To provide an overview of specific aspects of historical and possible future trajectories of psychiatry. CONCLUSIONS: Psychiatric treatments alleviate suffering, promote physical health, and are associated with increased longevity. As the biological underpinnings of mental illnesses are slowly uncovered, they generally cease to be primarily part of psychiatry (e.g. epilepsy, anti-NMDA receptor encephalitis). If this process continues, the biological basis of all symptom-based 'mental illnesses' might be described, and psychiatry absorbed into neurology and other disciplines. This will be a positive development if it provides better treatment for mental illness and psychiatric symptoms in other conditions, which is psychiatry's sole concern. Psychiatry's own survival as a distinct discipline is irrelevant if other disciplines can do the job better, possibly in collaboration. Given the tiny impact of neuroscience on psychiatry to date, the disappearance of psychiatry is unlikely to occur anytime soon, if ever. It is possible that human psychological functioning and psychiatric suffering are sufficiently complex and changeable as to defy complete, fine-grained, neuroscientific explanation. This would leave a role for psychiatry indefinitely, treating the immensely disabling, biologically unexplained clusters of symptoms that we currently call 'mental illnesses', increasingly in collaboration with, or absorbed within, other disciplines in medicine.

Capacity to consent to treatment in psychiatry inpatients - a systematic review.

BACKGROUND: Mental capacity for treatment decisions in psychiatry inpatients is an important ethical and legal concern, especially in light of changes in mental capacity legislation in many jurisdictions. AIMS: To conduct a systematic review of literature examining the prevalence of mental capacity for treatment decisions among voluntary and involuntary psychiatry inpatients, and to assess any correlations between research tools used to measure mental capacity and binary judgements using criteria such as those in capacity legislation. METHOD: We searched PsycINFO, Ovid MEDLINE and EMBASE for studies assessing mental capacity for treatment decisions in people admitted voluntarily and involuntarily to psychiatric hospitals. RESULTS: Forty-five papers emanating from 33 studies were identified. There was huge variability in study methods and often selective populations, but the prevalence of decision-making capacity varied between 5% and 83.7%. These figures resulted from studies using cut-off scores or categorical criteria only. The prevalence of decision-making capacity among involuntary patients ranged from 7.7% to 42%, and among voluntary patients ranged from 29% to 97.9%. Two papers showed positive correlations between clinicians' judgement of decision-making capacity and scores on the MacArthur Competence Assessment Tool for Treatment; two papers showed no such correlation. CONCLUSIONS: Not all voluntary psychiatry inpatients possess mental capacity and many involuntary patients do. This paradox needs to be clarified and resolved in mental health legislation; supported decision-making can help with this task.Key PointsLegislative changes for mental capacity are taking place in many jurisdictions.This is an important human rights issue for many people, including psychiatry inpatients.In our review, we found the prevalence of decision-making capacity varies between 5% and 83.7% in psychiatry inpatients.Not all voluntary inpatients have decision-making capacity.Many involuntary inpatients have mental capacity to make decisions.Supported decision-making can help those with impairments in their mental capacity.

Pulmonary Function Tests in Very Low Birth Weight Infants Screened for Pulmonary Hypertension: A Pilot Study.

OBJECTIVE: To compare pulmonary function tests (PFTs), specifically respiratory system resistance (Rrs) and compliance (Crs), in very low birth weight (VLBW) infants with and without pulmonary hypertension. STUDY DESIGN: Infants were included who underwent PFTs at 34-38 weeks postmenstrual age (PMA) as part of our pulmonary hypertension screening guidelines for infants born at ≤1500 g requiring respiratory support at ≥34 weeks PMA. One pediatric cardiologist reviewed and estimated right ventricular or pulmonary arterial pressure and defined pulmonary hypertension as an estimated pulmonary arterial pressure or right ventricular pressure greater than one-half the systemic pressure. Rrs and Crs were measured with the single breath occlusion technique and functional residual capacity with the nitrogen washout method according to standardized criteria. RESULTS: Twelve VLBW infants with pulmonary hypertension and 39 without pulmonary hypertension were studied. Those with pulmonary hypertension had significantly lower birth weight and a trend toward a lower gestational age. There were no other demographic differences between the groups. The infants with pulmonary hypertension had significantly higher Rrs (119 vs 78 cmH2O/L/s; adjusted P = .012) and significantly lower Crs/kg (0.71 vs 0.92 mL/cmH2O/kg; P = .04). CONCLUSIONS: In this pilot study of VLBW infants screened for pulmonary hypertension at 34-38 weeks PMA, those with pulmonary hypertension had significantly increased Rrs and decreased Crs compared with those without pulmonary hypertension. Additional studies are needed to further phenotype infants with evolving BPD and pulmonary hypertension.

Delineating the Ligand-Receptor Interactions That Lead to Biased Signaling at the µ-Opioid Receptor.

Biased agonists, which selectively stimulate certain signaling pathways controlled by a G protein-coupled receptor (GPCR), hold great promise as drugs that maximize efficacy while minimizing dangerous side effects. Biased agonists of the µ-opioid receptor (µOR) are of particular interest as a means to achieve analgesia through G protein signaling without dose-limiting side effects such as respiratory depression and constipation. Rational structure-based design of biased agonists remains highly challenging, however, because the ligand-mediated interactions that are key to activation of each signaling pathway remain unclear. We identify several compounds for which the R- and S-enantiomers have distinct bias profiles at the µOR. These compounds serve as excellent comparative tools to study bias because the identical physicochemical properties of enantiomer pairs ensure that differences in bias profiles are due to differences in interactions with the µOR binding pocket. Atomic-level simulations of compounds at µOR indicate that R- and S-enantiomers adopt different poses that form distinct interactions with the binding pocket. A handful of specific interactions with highly conserved binding pocket residues appear to be responsible for substantial differences in arrestin recruitment between enantiomers. Our results offer guidance for rational design of biased agonists at µOR and possibly at related GPCRs.

Implementation of a patient-collected audio recording audit & feedback quality improvement program to prevent contextual error: stakeholder perspective.

BACKGROUND: Using patient audio recordings of medical visits to provide clinicians with feedback on their attention to patient life context in care planning can improve health care delivery and outcomes, and reduce costs. However, such an initiative can raise concerns across stakeholders about surveillance, intrusiveness and merit. This study examined the perspectives of patients, physicians and other clinical staff, and facility leaders over 3 years at six sites during the implementation of a patient-collected audio quality improvement program designed to improve patient-centered care in a non-threatening manner and with minimal effort required of patients and clinicians. METHODS: Patients were invited during the first and third year to complete exit surveys when they returned their audio recorders following visits, and clinicians to complete surveys annually. Clinicians were invited to participate in focus groups in the first and third years. Facility leaders were interviewed individually during the last 6 months of the study. RESULTS: There were a total of 12 focus groups with 89 participants, and 30 leadership interviews. Two hundred fourteen clinicians and 800 patients completed surveys. In a qualitative analysis of focus group data employing NVivo, clinicians initially expressed concerns that the program could be disruptive and/or burdensome, but these diminished with program exposure and were substantially replaced by an appreciation for the value of low stakes constructive feedback. They were also significantly more confident in the value of the intervention in the final year (p = .008), more likely to agree that leadership supports continuous improvement of patient care and gives feedback on outcomes (p = .02), and at a time that is convenient (p = .04). Patients who volunteered sometimes expressed concerns they were "spying" on their doctors, but most saw it as an opportunity to improve care. Leaders were supportive of the program but not yet prepared to commit to funding it exclusively with facility resources. CONCLUSIONS: A patient-collected audio program can be implemented when it is perceived as safe, not disruptive or burdensome, and as contributing to better health care.

The Use of Point of Care Ultrasound in Hand Surgery.

Point of care ultrasound (POCUS) is the use of ultrasound (US) imaging technology by non-sonographer, non-radiologist treating clinicians. Handheld US systems are increasing in popularity and becoming widely available and easily accessible to hand surgeons in clinical practice. Adapting POCUS into the repertoire of the hand surgeon can aid in the diagnosis of many common hand surgery presentations and shorten operative times. In this review, we outline the potential uses and advantages of incorporating POCUS into hand surgery practice incuding its use in emergencies such as trauma, infections, and foreign body localization, as well as elective presentations such as nerve compression, procedural guidance, and anesthesia. Finally, this review outlines the training and curriculum development required to ensure safe implementation of POCUS into a hand surgery practice.

Being present: Examining the efficacy of an Internet Mantram Program on RN-delivered patient-centered care.

BACKGROUND: The COVID-19 pandemic highlighted nurses' compassionate presence during stressful conditions. Strategies to reduce workplace stress are needed. PURPOSE: The purpose of this study was to evaluate a stress reduction strategy, an Internet-based Mantram Repetition Program (MRP), for nurses caring for hospitalized Veterans. METHODS: A one group pre-/post-test design was used to assess change in nurses' perceived outcomes after participating in the MRP. A post-test-only design was used to assess hospitalized Veterans' perceptions of nursing presence and satisfaction with care. Qualitative interviews were used to supplement quantitative data. FINDINGS: Patients perceived high levels of presence and satisfaction with care. Post MRP, nurses perceived increased mindfulness, compassion satisfaction, spiritual well-being, and nursing presence. Increased mindfulness was associated with greater compassion satisfaction and less burnout. DISCUSSION: For nurses working on the front lines of patient care, the potential for experiencing stress and burnout is a reality. Participating in a MRP could lessen these effects and facilitate nursing presence.