Defragmentation of care in complex patients with ESKD improves clinical outcomes.

OBJECTIVES: Given the problematic fragmentation of care for patients with end-stage kidney disease (ESKD), a kidney care organization and an integrated health system within a large accountable care organization partnered to best utilize their individual capabilities to collaborate around their shared patients in a coordinated care approach. Ultimately, the goal of the program is to allow care teams to achieve the triple aim of improving the patient experience, improving clinical outcomes, and reducing the total cost of health care. STUDY DESIGN: This is a retrospective examination of the first year of the Shared Patient Care Coordination (SPCC) program. METHODS: The analysis consisted of 2 parts. First, rates of hospitalizations and emergency department visits were compared between the SPCC patients and other patients of the integrated health system who had ESKD but did not participate in SPCC. Second, rates of clinical indicators-central venous catheter (CVC) use, home dialysis, advance care planning, and missed dialysis treatments-were benchmarked vs normative data taken by bootstrap sampling of the kidney care organization's patient population. RESULTS: Overall, dialysis patients participating in the SPCC program had a 15% lower rate of hospital admissions than those not participating ( P = .02). Additionally, the bootstrap analysis showed that by the second year, dialysis patients in the program had favorable rates (above the 95th percentile) of CVC use, dialysis treatment absenteeism, and completion of advance care plans. CONCLUSIONS: Enhanced and structured communication between dialysis providers and patient care teams provides a unique opportunity to coordinate patient-centered care and improve patient outcomes.

Post-hospitalization remote monitoring for patients with heart failure or chronic obstructive pulmonary disease in an accountable care organization.

BACKGROUND: Post-hospitalization remote patient monitoring (RPM) has potential to improve health outcomes for high-risk patients with chronic medical conditions. The purpose of this study is to determine the extent to which RPM for patients with congestive heart failure (CHF) and chronic obstructive pulmonary disease (COPD) is associated with reductions in post-hospitalization mortality, hospital readmission, and ED visits within an Accountable Care Organization (ACO). METHODS: Nonrandomized prospective study of patients in an ACO offered enrollment in RPM upon hospital discharge between February 2021 and December 2021. RPM comprised of vital sign monitoring equipment (blood pressure monitor, scale, pulse oximeter), tablet device with symptom tracking software and educational material, and nurse-provided oversight and triage. Expected enrollment was for at least 30-days of monitoring, and outcomes were followed for 6 months following enrollment. The co-primary outcomes were (a) the composite of death, hospital admission, or emergency care visit within 180 days of eligibility, and (b) time to occurrence of this composite. Secondary outcomes were each component individually, the composite of death or hospital admission, and outpatient office visits. Adjusted analyses involved doubly robust estimation to address confounding by indication. RESULTS: Of 361 patients offered remote monitoring (251 with CHF and 110 with COPD), 140 elected to enroll (106 with CHF and 34 with COPD). The median duration of RPM-enrollment was 54 days (IQR 34-85). Neither the 6-month frequency of the co-primary composite outcome (59% vs 66%, FDR p-value = 0.47) nor the time to this composite (median 29 vs 38 days, FDR p-value = 0.60) differed between the groups, but 6-month mortality was lower in the RPM group (6.4% vs 17%, FDR p-value = 0.02). After adjustment for confounders, RPM enrollment was associated with nonsignificantly decreased odds for the composite outcome (adjusted OR [aOR] 0.68, 99% CI 0.25-1.34, FDR p-value 0.30) and lower 6-month mortality (aOR 0.41, 99% CI 0.00-0.86, FDR p-value 0.20). CONCLUSIONS: RPM enrollment may be associated with improved health outcomes, including 6-month mortality, for selected patient populations.

Developing a Framework for the Design and Deployment of Virtual Reality (VR) in Clinical Education.

The emerging cost-effective and powerful standalone VR hardware is an increasingly viable supplement to traditional clinical educational modalities. These traditional approaches are effective but can be limited by the cost of simulation infrastructure, the requirement to attend at fixed times and locations and instructor availability present challenges in meeting the needs of clinicians. One barrier facing educators looking to develop bespoke VR-based solutions is the lack of guidelines around their design, development, deployment, and evaluation. Our team has produced and deployed a number of VR-based educational applications. Through reflecting on findings from surveys, interviews, observation, we summarise a range of insights into the complexity and nuances of the clinical VR design and deployment in a framework that can inform and guide educators, clinicians and developers looking to create their own VR applications for use in healthcare.

Duvelisib for Critically Ill Patients With Coronavirus Disease 2019: An Investigator-Initiated, Randomized, Placebo-Controlled, Double-Blind Pilot Trial.

Background: Despite improvements in prevention and treatment, severe coronavirus disease 2019 (COVID-19) is associated with high mortality. Phosphoinositide 3-kinase (PI3K) pathways contribute to cytokine and cell-mediated lung inflammation. We conducted a randomized, placebo-controlled, double-blind pilot trial to determine the feasibility, safety, and preliminary activity of duvelisib, a PI3Kδγ inhibitor, for the treatment of COVID-19 critical illness. Methods: We enrolled adults aged ≥18 years with a primary diagnosis of COVID-19 with hypoxic respiratory failure, shock, and/or new cardiac disease, without improvement after at least 48 hours of corticosteroid. Participants received duvelisib (25 mg) or placebo for up to 10 days. Participants had daily semi-quantitative viral load measurements performed. Dose modifications were protocol driven due to adverse events (AEs) or logarithmic change in viral load. The primary endpoint was 28-day overall survival (OS). Secondary endpoints included hospital and intensive care unit length of stay, 60-day OS, and duration of critical care interventions. Safety endpoints included viral kinetics and AEs. Exploratory endpoints included serial cytokine measurements and cytometric analysis. Results: Fifteen patients were treated in the duvelisib cohort, and 13 in the placebo cohort. OS at 28 days was 67% (95% confidence interval [CI], 38%-88%) compared to 62% (95% CI, 32%-86%) for placebo (P = .544). Sixty-day OS was 60% versus 46%, respectively (hazard ratio, 0.66 [95% CI, .22-1.96]; P = .454). Other secondary outcomes were comparable. Duvelisib was associated with lower inflammatory cytokines. Conclusions: In this pilot study, duvelisib did not significantly improve 28-day OS compared to placebo for severe COVID-19. Duvelisib appeared safe in this critically ill population and was associated with reduction in cytokines implicated in COVID-19 and acute respiratory distress syndrome, supporting further investigation. Clinical Trials Registration: NCT04372602.

On the increasing competitiveness of UV/Cl to UV/H2O2 advanced oxidation as the organic carbon concentration increases.

UV/Cl and UV/H2O2 are advanced oxidation processes (AOPs) used for drinking water treatment and water reuse. This work explored the hypothesis that UV/Cl becomes more competitive to UV/H2O2 at neutral-to-high pH as the concentration of total organic carbon (TOC) increases. Lab experiments and kinetic modelling were used to compare initial pseudo first-order contaminant decay rate coefficients between the AOPs at various pH and TOC conditions. The relative effect of increasing TOC concentrations on UV/Cl vs. UV/H2O2 depended on the pH, contaminant, and organic matter reactivity towards radicals. For example, while the reaction rate coefficients during both AOPs generally decreased with increasing TOC, the UV/Cl reaction rate coefficients for the solely •OH-reactive sucralose decreased 41-138% less than the UV/H2O2 coefficients as the TOC concentration was increased from 0 to 5 mg-C L-1. However, UV/Cl was more affected than UV/H2O2 when targeting caffeine (a contaminant reactive to chlorine radicals). The data were used to define TOC-pH conditions for which either AOP would be more energy-efficient, under a set of standard conditions. The results suggest that UV/Cl may be competitive to UV/H2O2 under a wider range of treatment scenarios than has been conventionally thought based on tests in pure water.

Advanced Care Planning for Hospitalized Patients Following Clinician Notification of Patient Mortality by a Machine Learning Algorithm.

Importance: Goal-concordant care is an ongoing challenge in hospital settings. Identification of high mortality risk within 30 days may call attention to the need to have serious illness conversations, including the documentation of patient goals of care. Objective: To examine goals of care discussions (GOCDs) in a community hospital setting with patients identified as having a high risk of mortality by a machine learning mortality prediction algorithm. Design, Setting, and Participants: This cohort study took place at community hospitals within 1 health care system. Participants included adult patients with a high risk of 30-day mortality who were admitted to 1 of 4 hospitals between January 2 and July 15, 2021. Patient encounters of inpatients in the intervention hospital where physicians were notified of the computed high risk mortality score were compared with patient encounters of inpatients in 3 community hospitals without the intervention (ie, matched control). Intervention: Physicians of patients with a high risk of mortality within 30 days received notification and were encouraged to arrange for GOCDs. Main Outcomes and Measures: The primary outcome was the percentage change of documented GOCDs prior to discharge. Propensity-score matching was completed on a preintervention and postintervention period using age, sex, race, COVID-19 status, and machine learning-predicted mortality risk scores. A difference-in-difference analysis validated the results. Results: Overall, 537 patients were included in this study with 201 in the preintervention period (94 in the intervention group; 104 in the control group) and 336 patients in the postintervention period. The intervention and control groups included 168 patients per group and were well-balanced in age (mean [SD], 79.3 [9.60] vs 79.6 [9.21] years; standardized mean difference [SMD], 0.03), sex (female, 85 [51%] vs 85 [51%]; SMD, 0), race (White patients, 145 [86%] vs 144 [86%]; SMD 0.006), and Charlson comorbidities (median [range], 8.00 [2.00-15.0] vs 9.00 [2.00 to 19.0]; SMD, 0.34). Patients in the intervention group from preintervention to postintervention period were associated with being 5 times more likely to have documented GOCDs (OR, 5.11 [95% CI, 1.93 to 13.42]; P = .001) by discharge compared with matched controls, and GOCD occurred significantly earlier in the hospitalization in the intervention patients as compared with matched controls (median, 4 [95% CI, 3 to 6] days vs 16 [95% CI, 15 to not applicable] days; P < .001). Similar findings were observed for Black patient and White patient subgroups. Conclusions and Relevance: In this cohort study, patients whose physicians had knowledge of high-risk predictions from machine learning mortality algorithms were associated with being 5 times more likely to have documented GOCDs than matched controls. Additional external validation is needed to determine if similar interventions would be helpful at other institutions.

Thiol Reactome: A Nontargeted Strategy to Precisely Identify Thiol Reactive Drinking Water Disinfection Byproducts.

The precise identification of predominant toxic disinfection byproducts (DBPs) from disinfected water is a longstanding challenge. We propose a new acellular analytical strategy, the 'Thiol Reactome', to identify thiol-reactive DBPs by employing a thiol probe and nontargeted mass spectrometry (MS) analysis. Disinfected/oxidized water samples had reduced cellular oxidative stress responses of 46 ± 23% in Nrf2 reporter cells when preincubated with glutathione (GSH). This supports thiol-reactive DBPs as the predominant drivers of oxidative stress. This method was benchmarked using seven classes of DBPs including haloacetonitriles, which preferentially reacted with GSH via substitution or addition depending on the number of halogens present. The method was then applied to chemically disinfected/oxidized waters, and 181 tentative DBP-GSH reaction products were detected. The formulas of 24 high abundance DBP-GSH adducts were predicted, among which nitrogenous-DBPs (11) and unsaturated carbonyls (4) were the predominant compound classes. Two major unsaturated carbonyl-GSH adducts, GSH-acrolein and GSH-acrylic acid, were confirmed by their authentic standards. These two adducts were unexpectedly formed from larger native DBPs when reacting with GSH. This study demonstrated the "Thiol Reactome" as an effective acellular assay to precisely identify and broadly capture toxic DBPs from water mixtures.

Mid-regional proadrenomedullin (MR-proADM), C-reactive protein (CRP) and other biomarkers in the early identification of disease progression in patients with COVID-19 in the acute NHS setting.

AIMS: There is a lack of biomarkers validated for assessing clinical deterioration in patients with COVID-19 on presentation to secondary or tertiary care. This evaluation looked at the potential clinical application of C reactive protein (CRP), procalcitonin, mid-regional proadrenomedullin (MR-proADM) and white cell count to support prediction of clinical outcomes. METHODS: 135 patients presenting to Hampshire Hospitals NHS Foundation Trust between April and June 2020 confirmed to have COVID-19 via reverse-transcription-qPCR were included. Biomarkers from within 24 hours of presentation were used to predict disease progression by Cox regression and area under the receiver operating characteristic curves. The endpoints assessed were 30-day all-cause mortality, intubation and ventilation, critical care admission and non-invasive ventilation (NIV) use. RESULTS: Elevated MR-proADM was shown to have the greatest ability to predict 30-day mortality adjusting for age, cardiovascular disease, renal disease and neurological disease. A significant association was also noted between raised MR-proADM and CRP concentrations and the requirement for critical care admission and NIV. CONCLUSIONS: The measurement of MR-proADM and CRP in patients with confirmed COVID-19 infection on admission shows significant potential to support clinicians in identifying those at increased risk of disease progression and need for higher level care, subsequently enabling prompt escalation in clinical interventions.

Virtual Reality-Based Interventions for Treating Depression in the Context of COVID-19 Pandemic: Inducing the Proficit in Positive Emotions as a Key Concept of Recovery and a Path Back to Normality.

BACKGROUND: During the COVID-19 pandemic as much as 40% of the global population reported deterioration in depressive mood, whereas 26% experienced increased need for emotional support. At the same time, the availability of on-site psychiatric care declined drastically because of the COVID-19 preventive social restriction measures. To address this shortfall, telepsychiatry assumes a greater role in mental health care services. Among various on-line treatment modalities, immersive virtual reality (VR) environments provide an important resource for adjusting the emotional state in people living with depression. Therefore, we reviewed the literature on VR-based interventions for depression treatment during the COVID-19 pandemic. SUBJECTS AND METHODS: We searched the PubMed and Scopus databases, as well as the Internet, for full-length articles published during the period of 2020-2022 citing a set of following key words: "virtual reality", "depression", "COVID-19", as well as their terminological synonyms and word combinations. The inclusion criteria were: 1) the primary or secondary study objectives included the treatment of depressive states or symptoms; 2) the immersive VR intervention used a head-mounted display (HMD); 3) the article presented clinical study results and/or case reports 4) the study was urged by or took place during the COVID-19-associated lockdown period. RESULTS: Overall, 904 records were retrieved using the search strategy. Remarkably, only three studies and one case report satisfied all the inclusion criteria elaborated for the review. These studies included 155 participants: representatives of healthy population (n=40), a case report of a patient with major depressive disorder (n=1), patients with cognitive impairments (n=25), and COVID-19 patients who had survived from ICU treatment (n=89). The described interventions used immersive VR scenarios, in combination with other treatment techniques, and targeted depression. The most robust effect, which the VR-based approach had demonstrated, was an immediate post-intervention improvement in mood and the reduction of depressive symptoms in healthy population. However, studies showed no significant findings in relation to both short-term effectiveness in treatment of depression and primary prevention of depressive symptoms. Also, safety issues were identified, such as: three participants developed mild adverse events (e.g., headache, "giddiness", and VR misuse behavior), and three cases of discomfort related to wearing a VR device were registered. CONCLUSIONS: There has been a lack of appropriately designed clinical trials of the VR-based interventions for depression since the onset of the COVID-19 pandemic. Moreover, all these studies had substantial limitations due to the imprecise study design, small sample size, and minor safety issues, that did not allow us making meaningful judgments and conclude regarding the efficacy of VR in the treatment of depression, taking into account those investigations we have retrieved upon the inclusion criteria of our particularistic review design. This may call for randomized, prospective studies of the short-term and long-lasting effect of VR modalities in managing negative affectivity (sadness, anxiety, anhedonia, self-guilt, ignorance) and inducing positive affectivity (feeling of happiness, joy, motivation, self-confidence, viability) in patients suffering from clinical depression.

Identification of COVID-19 patients at risk of hospital admission and mortality: a European multicentre retrospective analysis of mid-regional pro-adrenomedullin.

BACKGROUND: Mid-Regional pro-Adrenomedullin (MR-proADM) is an inflammatory biomarker that improves the prognostic assessment of patients with sepsis, septic shock and organ failure. Previous studies of MR-proADM have primarily focussed on bacterial infections. A limited number of small and monocentric studies have examined MR-proADM as a prognostic factor in patients infected with SARS-CoV-2, however there is need for multicenter validation. An evaluation of its utility in predicting need for hospitalisation in viral infections was also performed. METHODS: An observational retrospective analysis of 1861 patients, with SARS-CoV-2 confirmed by RT-qPCR, from 10 hospitals across Europe was performed. Biomarkers, taken upon presentation to Emergency Departments (ED), clinical scores, patient demographics and outcomes were collected. Multiclass random forest classifier models were generated as well as calculation of area under the curve analysis. The primary endpoint was hospital admission with and without death. RESULTS: Patients suitable for safe discharge from Emergency Departments could be identified through an MR-proADM value of ≤ 1.02 nmol/L in combination with a CRP (C-Reactive Protein) of ≤ 20.2 mg/L and age ≤ 64, or in combination with a SOFA (Sequential Organ Failure Assessment) score < 2 if MR-proADM was ≤ 0.83 nmol/L regardless of age. Those at an increased risk of mortality could be identified upon presentation to secondary care with an MR-proADM value of > 0.85 nmol/L, in combination with a SOFA score ≥ 2 and LDH > 720 U/L, or in combination with a CRP > 29.26 mg/L and age ≤ 64, when MR-proADM was > 1.02 nmol/L. CONCLUSIONS: This international study suggests that for patients presenting to the ED with confirmed SARS-CoV-2 infection, MR-proADM in combination with age and CRP or with the patient's SOFA score could identify patients at low risk where outpatient treatment may be safe.

Designing Virtual Reality-Based Conversational Agents to Train Clinicians in Verbal De-escalation Skills: Exploratory Usability Study.

BACKGROUND: Violence and aggression are significant workplace challenges faced by clinicians worldwide. Traditional methods of training consist of "on-the-job learning" and role-play simulations. Although both approaches can result in improved skill levels, they are not without limitation. Interactive simulations using virtual reality (VR) can complement traditional training processes as a cost-effective, engaging, easily accessible, and flexible training tool. OBJECTIVE: In this exploratory study, we aimed to determine the feasibility of and barriers to verbal engagement with a virtual agent in the context of the Code Black VR application. Code Black VR is a new interactive VR-based verbal de-escalation trainer that we developed based on the Clinical Training Through VR Design Framework. METHODS: In total, 28 participants with varying clinical expertise from 4 local hospitals enrolled in the Western Sydney Local Health District Clinical Initiative Nurse program and Transition to Emergency Nursing Programs and participated in 1 of 5 workshops. They completed multiple playthroughs of the Code Black VR verbal de-escalation trainer application and verbally interacted with a virtual agent. We documented observations and poststudy reflection notes. After the playthroughs, the users completed the System Usability Scale and provided written comments on their experience. A thematic analysis was conducted on the results. Data were also obtained through the application itself, which also recorded the total interactions and successfully completed interactions. RESULTS: The Code Black VR verbal de-escalation training application was well received. The findings reinforced the factors in the existing design framework and identified 3 new factors-motion sickness, perceived value, and privacy-to be considered for future application development. CONCLUSIONS: Verbal interaction with a virtual agent is feasible for training staff in verbal de-escalation skills. It is an effective medium to supplement clinician training in verbal de-escalation skills. We provide broader design considerations to guide further developments in this area.

Development and Structure of an Accurate Machine Learning Algorithm to Predict Inpatient Mortality and Hospice Outcomes in the Coronavirus Disease 2019 Era.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has challenged the accuracy and racial biases present in traditional mortality scores. An accurate prognostic model that can be applied to hospitalized patients irrespective of race or COVID-19 status may benefit patient care. RESEARCH DESIGN: This cohort study utilized historical and ongoing electronic health record features to develop and validate a deep-learning model applied on the second day of admission predicting a composite outcome of in-hospital mortality, discharge to hospice, or death within 30 days of admission. Model features included patient demographics, diagnoses, procedures, inpatient medications, laboratory values, vital signs, and substance use history. Conventional performance metrics were assessed, and subgroup analysis was performed based on race, COVID-19 status, and intensive care unit admission. SUBJECTS: A total of 35,521 patients hospitalized between April 2020 and October 2020 at a single health care system including a tertiary academic referral center and 9 community hospitals. RESULTS: Of 35,521 patients, including 9831 non-White patients and 2020 COVID-19 patients, 2838 (8.0%) met the composite outcome. Patients who experienced the composite outcome were older (73 vs. 61 y old) with similar sex and race distributions between groups. The model achieved an area under the receiver operating characteristic curve of 0.89 (95% confidence interval: 0.88, 0.91) and an average positive predictive value of 0.46 (0.40, 0.52). Model performance did not differ significantly in White (0.89) and non-White (0.90) subgroups or when grouping by COVID-19 status and intensive care unit admission. CONCLUSION: A deep-learning model using large-volume, structured electronic health record data can effectively predict short-term mortality or hospice outcomes on the second day of admission in the general inpatient population without significant racial bias.

Reverse-Transcription Loop-Mediated Isothermal Amplification Has High Accuracy for Detecting Severe Acute Respiratory Syndrome Coronavirus 2 in Saliva and Nasopharyngeal/Oropharyngeal Swabs from Asymptomatic and Symptomatic Individuals.

Previous studies have described reverse-transcription loop-mediated isothermal amplification (RT-LAMP) for the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in nasopharyngeal/oropharyngeal swab and saliva samples. This multisite clinical evaluation describes the validation of an improved sample preparation method for extraction-free RT-LAMP and reports clinical performance of four RT-LAMP assay formats for SARS-CoV-2 detection. Direct RT-LAMP was performed on 559 swabs and 86,760 saliva samples and RNA RT-LAMP on extracted RNA from 12,619 swabs and 12,521 saliva samples from asymptomatic and symptomatic individuals across health care and community settings. For direct RT-LAMP, overall diagnostic sensitivity (DSe) was 70.35% (95% CI, 63.48%-76.60%) on swabs and 84.62% (95% CI, 79.50%-88.88%) on saliva, with diagnostic specificity of 100% (95% CI, 98.98%-100.00%) on swabs and 100% (95% CI, 99.72%-100.00%) on saliva, compared with quantitative RT-PCR (RT-qPCR); analyzing samples with RT-qPCR ORF1ab CT values of ≤25 and ≤33, DSe values were 100% (95% CI, 96.34%-100%) and 77.78% (95% CI, 70.99%-83.62%) for swabs, and 99.01% (95% CI, 94.61%-99.97%) and 87.61% (95% CI, 82.69%-91.54%) for saliva, respectively. For RNA RT-LAMP, overall DSe and diagnostic specificity were 96.06% (95% CI, 92.88%-98.12%) and 99.99% (95% CI, 99.95%-100%) for swabs, and 80.65% (95% CI, 73.54%-86.54%) and 99.99% (95% CI, 99.95%-100%) for saliva, respectively. These findings demonstrate that RT-LAMP is applicable to a variety of use cases, including frequent, interval-based direct RT-LAMP of saliva from asymptomatic individuals who may otherwise be missed using symptomatic testing alone.

Predictive Radiation Oncology - A New NCI-DOE Scientific Space and Community.

With a widely attended virtual kickoff event on January 29, 2021, the National Cancer Institute (NCI) and the Department of Energy (DOE) launched a series of 4 interactive, interdisciplinary workshops-and a final concluding "World Café" on March 29, 2021-focused on advancing computational approaches for predictive oncology in the clinical and research domains of radiation oncology. These events reflect 3,870 human hours of virtual engagement with representation from 8 DOE national laboratories and the Frederick National Laboratory for Cancer Research (FNL), 4 research institutes, 5 cancer centers, 17 medical schools and teaching hospitals, 5 companies, 5 federal agencies, 3 research centers, and 27 universities. Here we summarize the workshops by first describing the background for the workshops. Participants identified twelve key questions-and collaborative parallel ideas-as the focus of work going forward to advance the field. These were then used to define short-term and longer-term "Blue Sky" goals. In addition, the group determined key success factors for predictive oncology in the context of radiation oncology, if not the future of all of medicine. These are: cross-discipline collaboration, targeted talent development, development of mechanistic mathematical and computational models and tools, and access to high-quality multiscale data that bridges mechanisms to phenotype. The workshop participants reported feeling energized and highly motivated to pursue next steps together to address the unmet needs in radiation oncology specifically and in cancer research generally and that NCI and DOE project goals align at the convergence of radiation therapy and advanced computing.

C-reactive protein-guided use of procalcitonin in COVID-19.

BACKGROUND: A low procalcitonin (PCT) concentration facilitates exclusion of bacterial co-infections in COVID-19, but high costs associated with PCT measurements preclude universal adoption. Changes in inflammatory markers, including C-reactive protein (CRP), can be concordant, and predicting low PCT concentrations may avoid costs of redundant tests and support more cost-effective deployment of this diagnostic biomarker. OBJECTIVES: To explore whether, in COVID-19, low PCT values could be predicted by the presence of low CRP concentrations. METHODS: Unselected cohort of 224 COVID-19 patients admitted to hospital that underwent daily PCT and CRP measurements as standard care. Both 0.25 ng/mL and 0.5 ng/mL were used as cut-offs for positive PCT test results. Geometric mean was used to define high and low CRP values at each timepoint assessed. RESULTS: Admission PCT was <0.25 ng/mL in 160/224 (71.4%), 0.25-0.5 ng/mL in 27 (12.0%) and >0.5 ng/mL in 37 (16.5%). Elevated PCT was associated with increased risk of death (P = 0.0004) and was more commonly associated with microbiological evidence of bacterial co-infection (P < 0.0001). For high CRP values, significant heterogeneity in PCT measurements was observed, with maximal positive predictive value of 50% even for a PCT cut-off of 0.25 ng/mL. In contrast, low CRP was strongly predictive of low PCT concentrations, particularly <0.5 ng/mL, with a negative predictive value of 97.6% at time of hospital admission and 100% 48 hours into hospital stay. CONCLUSIONS: CRP-guided PCT testing algorithms can reduce unnecessary PCT measurement and costs, supporting antimicrobial stewardship strategies in COVID-19.

The management of the shoulder skin microbiome (Cutibacterium acnes) in the context of shoulder surgery: a review of the current literature.

BACKGROUND: This review aims to establish current knowledge of the shoulder skin microbiome and how to manage the bacteria that reside within it. METHODS: A review was undertaken of the current literature through OvidSP. All abstracts were reviewed by three independent researchers. RESULTS: Thirty-five studies met the inclusion criteria. With forward referencing an additional 14 were included. None commented on organisms specific to the shoulder microbiome other than Cutibacterium acnes. Therefore, this review is focussed on the current knowledge of C. acnes. DISCUSSION: C. acnes is a skin commensal within the pilo-sebaceous glands reported to be the primary pathogen in up to 86% of shoulder joint infections. Pre-operative culture of unprepared skin can be indicative of underlying joint infection in shoulder arthroplasty revision. Intra-articular biopsies may have a high false positive due to skin contamination. Correlating the number of positive samples and certain associated signs can give a greater than 90% probability of a true infection. Standard surgical skin preparation, peri-surgical intravenous antibiotics and oral pre-operative antibiotics do not reduce bacterial load within the skin. However, topical benzoyl peroxide and clindamycin have both demonstrated significantly reduced bacteria load. Phylogenetically there are six main types. Patients may have more than one phenotype present during infection.

Sample test array and recovery (STAR) platform at the National Ignition Facility.

We have developed the Sample Test Array and Recovery (STAR) platform for the National Ignition Facility (NIF) for studying the thermal and hydrodynamic responses of materials in extreme environments. The STAR platform expands the range of obtainable fluences and quadruples the rate that materials experiments can be conducted at the NIF. Example configurations are demonstrated for fluences spanning 0.56-34 J/cm2 with environmental isolation for post-shot material recovery and inspection and up to 1740 J/cm2 without isolation, with surface heating rates of up to 2 × 1014 K/s. An example experiment involving thermally driven shock and spallation of aluminum alloy 7075 is briefly discussed.

Deletion of AMPK minimizes graft-versus-host disease through an early impact on effector donor T cells.

Allogeneic hematopoietic stem cell transplantation is a viable treatment for multiple hematologic diseases, but its application is often limited by graft-versus-host disease (GVHD), where donor T cells attack host tissues in the skin, liver, and gastrointestinal tract. Here, we examined the role of the cellular energy sensor AMP kinase (AMPK) in alloreactive T cells during GVHD development. Early posttransplant, AMPK activity increased more than 15-fold in allogeneic T cells, and transplantation of T cells deficient in both AMPKα1 and AMPKα2 decreased GVHD severity in multiple disease models. Importantly, a lack of AMPK lessened GVHD without compromising antileukemia responses or impairing lymphopenia-driven immune reconstitution. Mechanistically, absence of AMPK decreased both CD4+ and CD8+ effector T cell numbers as early as day 3 posttransplant, while simultaneously increasing regulatory T cell (Treg) percentages. Improvements in GVHD resulted from cell-intrinsic perturbations in conventional effector T cells as depletion of donor Tregs had minimal impact on AMPK-related improvements. Together, these results highlight a specific role for AMPK in allogeneic effector T cells early posttransplant and suggest that AMPK inhibition may be an innovative approach to mitigate GVHD while preserving graft-versus-leukemia responses and maintaining robust immune reconstitution.

Manipulation of the unfolded protein response: A pharmacological strategy against coronavirus infection.

Coronavirus infection induces the unfolded protein response (UPR), a cellular signalling pathway composed of three branches, triggered by unfolded proteins in the endoplasmic reticulum (ER) due to high ER load. We have used RNA sequencing and ribosome profiling to investigate holistically the transcriptional and translational response to cellular infection by murine hepatitis virus (MHV), often used as a model for the Betacoronavirus genus to which the recently emerged SARS-CoV-2 also belongs. We found the UPR to be amongst the most significantly up-regulated pathways in response to MHV infection. To confirm and extend these observations, we show experimentally the induction of all three branches of the UPR in both MHV- and SARS-CoV-2-infected cells. Over-expression of the SARS-CoV-2 ORF8 or S proteins alone is itself sufficient to induce the UPR. Remarkably, pharmacological inhibition of the UPR greatly reduced the replication of both MHV and SARS-CoV-2, revealing the importance of this pathway for successful coronavirus replication. This was particularly striking when both IRE1α and ATF6 branches of the UPR were inhibited, reducing SARS-CoV-2 virion release (~1,000-fold). Together, these data highlight the UPR as a promising antiviral target to combat coronavirus infection.