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.

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.

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.

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.

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.

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.

Financial Implications of Early Hospital Discharge After AML-Like Induction Chemotherapy: A 4-Year Retrospective Analysis.

BACKGROUND: Early hospital discharge (EHD) after intensive acute myeloid leukemia (AML) induction chemotherapy has become routine at the University of Washington/Seattle Cancer Care Alliance over the past several years. We assessed the financial implications of EHD over the first 4 years after its broad adoption for patients with AML and other high-grade myeloid neoplasms undergoing AML-like induction chemotherapy. PATIENTS AND METHODS: We retrospectively compared charges between 189 patients with EHD who received all postinduction inpatient/outpatient care within our care system between August 2014 and July 2018 and 139 medically matched control patients who remained hospitalized for logistical reasons. Charges from the day of initial discharge (patients with EHD) or end of chemotherapy (control patients) until blood count recovery, additional chemotherapy or care transition, hospital discharge (for control patients only), an elapse of 42 days, or death were extracted from financial databases and separated into categories: facility/provider, emergency department, transfusions, laboratory, imaging, pharmacy, and miscellaneous. RESULTS: Combined charges averaged $4,157/day (range, $905-$13,119/day) for patients with EHD versus $9,248/day (range, $4,363-$48,522/day) for control patients (P<.001). The EHD cohort had lower mean facility/provider, transfusion, laboratory, and pharmacy charges but not imaging or miscellaneous charges. During readmissions, there was no statistically significant difference in daily inpatient charges between the EHD and control cohorts. After multivariable adjustment, average charges were $3,837/day lower for patients with EHD (P<.001). CONCLUSIONS: Together with previous data from our center showing that EHD is safe and associated with reduced healthcare resource utilization, this study further supports this care approach for AML and other high-grade myeloid neoplasms if infrastructure is available to enable close outpatient follow-up.

Sustainable hydropower in the 21st century.

Hydropower has been the leading source of renewable energy across the world, accounting for up to 71% of this supply as of 2016. This capacity was built up in North America and Europe between 1920 and 1970 when thousands of dams were built. Big dams stopped being built in developed nations, because the best sites for dams were already developed and environmental and social concerns made the costs unacceptable. Nowadays, more dams are being removed in North America and Europe than are being built. The hydropower industry moved to building dams in the developing world and since the 1970s, began to build even larger hydropower dams along the Mekong River Basin, the Amazon River Basin, and the Congo River Basin. The same problems are being repeated: disrupting river ecology, deforestation, losing aquatic and terrestrial biodiversity, releasing substantial greenhouse gases, displacing thousands of people, and altering people's livelihoods plus affecting the food systems, water quality, and agriculture near them. This paper studies the proliferation of large dams in developing countries and the importance of incorporating climate change into considerations of whether to build a dam along with some of the governance and compensation challenges. We also examine the overestimation of benefits and underestimation of costs along with changes that are needed to address the legitimate social and environmental concerns of people living in areas where dams are planned. Finally, we propose innovative solutions that can move hydropower toward sustainable practices together with solar, wind, and other renewable sources.

NIH funding longevity by gender.

Women have achieved parity with men among biomedical science degree holders but remain underrepresented in academic positions. The National Institutes of Health (NIH)-the world's largest public funder of biomedical research-receives less than one-third of its new grant applications from women. Correspondingly, women compose less than one-third of NIH research grantees, even though they are as successful as men in obtaining first-time grants. Our study examined women's and men's NIH funding trajectories over time (n = 34,770), exploring whether women remain funded at the same rate as men after receiving their first major research grants. A survival analysis demonstrated a slightly lower funding longevity for women. We next examined gender differences in application, review, and funding outcomes. Women individually held fewer grants, submitted fewer applications, and were less successful in renewing grants-factors that could lead to gender differences in funding longevity. Finally, two adjusted survival models that account for initial investigator characteristics or subsequent application behavior showed no gender differences, suggesting that the small observed longevity differences are affected by both sets of factors. Overall, given men's and women's generally comparable funding longevities, the data contradict the common assumption that women experience accelerated attrition compared with men across all career stages. Women's likelihood of sustaining NIH funding may be better than commonly perceived. This suggests a need to explore women's underrepresentation among initial NIH grantees, as well as their lower rates of new and renewal application submissions.

Modeling Immune Checkpoint Inhibitor Efficacy in Syngeneic Mouse Tumors in an Ex Vivo Immuno-Oncology Dynamic Environment.

The immune checkpoint blockade represents a revolution in cancer therapy, with the potential to increase survival for many patients for whom current treatments are not effective. However, response rates to current immune checkpoint inhibitors vary widely between patients and different types of cancer, and the mechanisms underlying these varied responses are poorly understood. Insights into the antitumor activities of checkpoint inhibitors are often obtained using syngeneic mouse models, which provide an in vivo preclinical basis for predicting efficacy in human clinical trials. Efforts to establish in vitro syngeneic mouse equivalents, which could increase throughput and permit real-time evaluation of lymphocyte infiltration and tumor killing, have been hampered by difficulties in recapitulating the tumor microenvironment in laboratory systems. Here, we describe a multiplex in vitro system that overcomes many of the deficiencies seen in current static histocultures, which we applied to the evaluation of checkpoint blockade in tumors derived from syngeneic mouse models. Our system enables both precision-controlled perfusion across biopsied tumor fragments and the introduction of checkpoint-inhibited tumor-infiltrating lymphocytes in a single experiment. Through real-time high-resolution confocal imaging and analytics, we demonstrated excellent correlations between in vivo syngeneic mouse and in vitro tumor biopsy responses to checkpoint inhibitors, suggesting the use of this platform for higher throughput evaluation of checkpoint efficacy as a tool for drug development.

Randomised controlled trial of simulation-based education for mechanical cardiopulmonary resuscitation training.

INTRODUCTION: Mechanical cardiopulmonary resuscitation (M-CPR) is increasingly used in the management of cardiac arrest. There are no previously reported randomised studies investigating M-CPR training. This study of newly trained M-CPR providers hypothesised that a brief simulation-based intervention after 4 months would improve M-CPR performance at 6 months. METHODS: This study used a simulated 'in situ' cardiac arrest model. The M-CPR device used was a proprietary Lund University Cardiac Assist System 3 machine (Physio Control, Redmond, Washington, USA). Standardised baseline training was provided to all participants. Following training, baseline performance was assessed. The primary outcome measure was the time taken to initiate M-CPR and the secondary outcome was performance against a checklist of errors. Participants were then randomised to intervention group (simulation training) or control group (routine clinical use of M-CPR). After 6 months the outcome measures were reassessed. Comparative statistical tests used an intention-to-treat analysis. RESULTS: 112 participants were enrolled. The intervention group (n=60) and control group (n=52) had similar demographic characteristics. At the 6-month assessment, median time to M-CPR initiation was 27.0 s (IQR 22.0-31.0) in the intervention group and 31.0 s (IQR 25.6-46.0) in the control group (p=0.003). The intervention group demonstrated fewer errors compared with controls at 6 months (p<0.001) CONCLUSION: In this randomised study of approaches to M-CPR training, providers receiving additional simulation-based training had higher retention levels of M-CPR skills. Therefore, when resuscitation skills are newly learnt, provision follow-up training should be an important consideration.

Molecular and Kinetic Models for High-Rate Thermal Degradation of Polyethylene.

Thermal degradation of polyethylene is studied under the extremely high rate temperature ramps expected in laser-driven and X-ray ablation experiments-from 1010 to 1014 K/s in isochoric, condensed phases. The molecular evolution and macroscopic state variables are extracted as a function of density from reactive molecular dynamics simulations using the ReaxFF potential. The enthalpy, dissociation onset temperature, bond evolution, and observed cross-linking are shown to be rate dependent. These results are used to parametrize a kinetic rate model for the decomposition and coalescence of hydrocarbons as a function of temperature, temperature ramp rate, and density. The results are contrasted to first-order random-scission macrokinetic models often assumed for pyrolysis of linear polyethylene under ambient conditions.

Using meta-quality to assess the utility of volunteered geographic information for science.

BACKGROUND: Volunteered geographic information (VGI) has strong potential to be increasingly valuable to scientists in collaboration with non-scientists. The abundance of mobile phones and other wireless forms of communication open up significant opportunities for the public to get involved in scientific research. As these devices and activities become more abundant, questions of uncertainty and error in volunteer data are emerging as critical components for using volunteer-sourced spatial data. METHODS: Here we present a methodology for using VGI and assessing its sensitivity to three types of error. More specifically, this study evaluates the reliability of data from volunteers based on their historical patterns. The specific context is a case study in surveillance of tsetse flies, a health concern for being the primary vector of African Trypanosomiasis. RESULTS: Reliability, as measured by a reputation score, determines the threshold for accepting the volunteered data for inclusion in a tsetse presence/absence model. Higher reputation scores are successful in identifying areas of higher modeled tsetse prevalence. A dynamic threshold is needed but the quality of VGI will improve as more data are collected and the errors in identifying reliable participants will decrease. CONCLUSIONS: This system allows for two-way communication between researchers and the public, and a way to evaluate the reliability of VGI. Boosting the public's ability to participate in such work can improve disease surveillance and promote citizen science. In the absence of active surveillance, VGI can provide valuable spatial information given that the data are reliable.

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.

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.

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.

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.

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.

Protecting the Amazon with protected areas.

This article addresses climate-tipping points in the Amazon Basin resulting from deforestation. It applies a regional climate model to assess whether the system of protected areas in Brazil is able to avoid such tipping points, with massive conversion to semiarid vegetation, particularly along the south and southeastern margins of the basin. The regional climate model produces spatially distributed annual rainfall under a variety of external forcing conditions, assuming that all land outside protected areas is deforested. It translates these results into dry season impacts on resident ecosystems and shows that Amazonian dry ecosystems in the southern and southeastern basin do not desiccate appreciably and that extensive areas experience an increase in precipitation. Nor do the moist forests dry out to an excessive amount. Evidently, Brazilian environmental policy has created a sustainable core of protected areas in the Amazon that buffers against potential climate-tipping points and protects the drier ecosystems of the basin. Thus, all efforts should be made to manage them effectively.