Timing of embolic phenomena after hydrogen peroxide exposure - a systematic review.

INTRODUCTION: Hydrogen peroxide ingestions cause significant morbidity and mortality due to oxygen gas emboli and are treatable with hyperbaric oxygen therapy. Recommendations for observation are based on small case series. OBJECTIVES: The aim of this systematic review is to define the time of onset of embolic phenomena after hydrogen peroxide exposure and to describe the proportion of patients who received hyperbaric oxygen therapy. METHODS: Cases from a systematic literature search were combined with those from a prior study that used data derived from the American Association of Poison Control Centers National Poison Data System. Air-gas emboli were defined as embolic phenomena (stroke, myocardial infarction, obstructive shock) potentially reversed with hyperbaric oxygen therapy. Simple counts, mean, and interquartile range were used for description and comparisons. RESULTS: A total of 766 records were identified in the literature search. Three-hundred and eighty-three duplicate records were identified and removed. Of the 383 remaining records, 156 met inclusion criteria; 88 were excluded based on predetermined criteria yielding 68 records with 85 unique cases. Forty-one cases were extracted from the 2017 National Poison Data System study resulting in a total of 126 cases for analysis. Case descriptions: We analyzed these 126 cases and documented 213 discrete clinical events, excluding deaths. There were 108 high-concentration exposures, 10 low-concentration exposures, and 8 were unknown. Thirty-five cases were intentional ingestions but not for self-harm, and 84 were unintentional or accidental. Only 4 cases were for self-harm, and there were 23 pediatric cases. There were 99 air-gas emboli reported in 78 patients. Time to onset: The time to onset of air-gas embolic was documented in 70/78. Time to symptom onset ranged from immediate to 72 h after hydrogen peroxide exposure. Over 90% of embolic symptoms occurred within 10 h of ingestion. Hyperbaric oxygen therapy: A total of 54/126 cases received hyperbaric oxygen therapy. Of those 54 cases, 31 had primary portal venous gas while the remaining 23 had air-gas emboli. Of the 23 air-gas emboli cases treated with hyperbaric oxygen therapy, 13 made full recoveries while 10 had residual symptoms or died. Mean time from air-gas emboli symptom onset to hyperbaric oxygen therapy in the full recovery group was 9 h compared to 18.2 h in the partial recovery/death group. Portal venous gas: There were 63 total reported cases of portal venous gas. Forty-nine of these cases were primary portal venous gas, 13 were secondary findings in patients with air-gas emboli and one case was secondary to non-air-gas emboli symptoms. Twenty-seven of 49 patients with portal venous gas (55%) as the primary finding had gastrointestinal bleeding. Thirty of the 63 cases received hyperbaric oxygen therapy for portal venous gas without any documented air-gas emboli. Deaths: Seventeen deaths occurred in the combined cohort. Of these, 13 were associated with high-concentration exposures. All deaths with reported time to symptom onset had symptoms within 1 h of exposure. CONCLUSION: This review of hydrogen peroxide exposure cases suggests that clinically significant embolic phenomena occur within 10 h of exposure, although delayed air-gas emboli do happen and should considered when deciding duration of observation. It remains equivocal whether hyperbaric oxygen therapy is beneficial in cases of primary portal venous gas without systemic involvement.

Developing a shared sepsis data infrastructure: a systematic review and concept map to FHIR.

The development of a shared data infrastructure across health systems could improve research, clinical care, and health policy across a spectrum of diseases, including sepsis. Awareness of the potential value of such infrastructure has been heightened by COVID-19, as the lack of a real-time, interoperable data network impaired disease identification, mitigation, and eradication. The Sepsis on FHIR collaboration establishes a dynamic, federated, and interoperable system of sepsis data from 55 hospitals using 2 distinct inpatient electronic health record systems. Here we report on phase 1, a systematic review to identify clinical variables required to define sepsis and its subtypes to produce a concept mapping of elements onto Fast Healthcare Interoperability Resources (FHIR). Relevant papers described consensus sepsis definitions, provided criteria for sepsis, severe sepsis, septic shock, or detailed sepsis subtypes. Studies not written in English, published prior to 1970, or "grey" literature were prospectively excluded. We analyzed 55 manuscripts yielding 151 unique clinical variables. We then mapped variables to their corresponding US Core FHIR resources and specific code values. This work establishes the framework to develop a flexible infrastructure for sharing sepsis data, highlighting how FHIR could enable the extension of this approach to other important conditions relevant to public health.

Selection for constrained peptides that bind to a single target protein.

Peptide secondary metabolites are common in nature and have diverse pharmacologically-relevant functions, from antibiotics to cross-kingdom signaling. Here, we present a method to design large libraries of modified peptides in Escherichia coli and screen them in vivo to identify those that bind to a single target-of-interest. Constrained peptide scaffolds were produced using modified enzymes gleaned from microbial RiPP (ribosomally synthesized and post-translationally modified peptide) pathways and diversified to build large libraries. The binding of a RiPP to a protein target leads to the intein-catalyzed release of an RNA polymerase σ factor, which drives the expression of selectable markers. As a proof-of-concept, a selection was performed for binding to the SARS-CoV-2 Spike receptor binding domain. A 1625 Da constrained peptide (AMK-1057) was found that binds with similar affinity (990 ± 5 nM) as an ACE2-derived peptide. This demonstrates a generalizable method to identify constrained peptides that adhere to a single protein target, as a step towards "molecular glues" for therapeutics and diagnostics.

Strengthening national capacities for pandemic preparedness: a cross-country analysis of COVID-19 cases and deaths.

The International Health Regulations-State Party Annual Reporting (IHR-SPAR) index and the Global Health Security Index (GHSI) have been developed to aid in strengthening national capacities for pandemic preparedness. We examined the relationship between country-level rankings on these two indices, along with two additional indices (the Universal Health Coverage Service Coverage Index and World Bank Worldwide Governance Indicator (n = 195)) and compared them to the country-level reported coronavirus disease (COVID-19) cases and deaths (Johns Hopkins University COVID-19 Dashboard) through 17 June 2020. Ordinary least squares regression models were used to compare weekly reported COVID-19 cases and death rates per million in the first 12 weeks of the pandemic between countries classified as low, middle and high ranking on each index while controlling for country socio-demographic information. Countries with higher GHSI and IHR-SPAR index scores experienced fewer reported COVID-19 cases and deaths but only for the first 8 weeks after the country's first case. For the GHSI, this association was further limited to countries with populations below 69.4 million. For both the GHSI and IHR-SPAR, countries with a higher sub-index score in human resources for pandemic preparedness reported fewer COVID-19 cases and deaths in the first 8 weeks after the country's first reported case. The Universal Health Coverage Service Coverage Index and Worldwide Governance Indicator country-level rankings were not associated with COVID-19 outcomes. The associations between GHSI and IHR-SPAR scores and COVID-19 outcomes observed in this study demonstrate that these two indices, although imperfect, may have value, especially in countries with a population under 69.4 million people for the GHSI. Preparedness indices may have value; however, they should continue to be evaluated as policy makers seek to better prepare for future global public health crises.

COVID-19 Impacts on the Trucking Industry

The primary objective of this research was to understand the immediate operational impacts that the COVID-19 pandemic had on trucking operations in the United States. The American Transportation Research Institute (ATRI) and the Owner-Operator Independent Driver Association (OOIDA) Foundation developed a collaborative research methodology for ascertaining pandemic effects on supply chains, trucking operations and truck drivers in particular. ATRI and OOIDA jointly developed a trucking industry survey that identified a range of operational and financial issues that were being impacted by the pandemic. The survey was designed to obtain the perspectives of multiple labor categories in trucking, from truck drivers to dispatchers to senior executives. The survey generated approximately 5,100 usable responses. Findings revealed that average trip lengths decreased during the pandemic, while truck travel speeds at the worst traffic chokepoints increased due to reduced congestion as motorists sheltered in place. Freight levels were also impacted, with certain sectors of the industry experiencing both dramatic decreases and increases in specific commodity volumes during the pandemic. The survey analysis also revealed that small fleets were not prepared for a significant impact on their operations. Nearly 80 percent of owner-operators and fleets with fewer than five power units reported that they did not have any disaster plan in place prior to COVID-19, whereas 70 percent of large fleets reported that they had business continuity plans in place. This lack of preplanning provides an opportunity for operational “best practices” research to inform disaster planning for small fleets going forward.

Lopinavir-ritonavir and hydroxychloroquine for critically ill patients with COVID-19: REMAP-CAP randomized controlled trial.

PURPOSE: To study the efficacy of lopinavir-ritonavir and hydroxychloroquine in critically ill patients with coronavirus disease 2019 (COVID-19). METHODS: Critically ill adults with COVID-19 were randomized to receive lopinavir-ritonavir, hydroxychloroquine, combination therapy of lopinavir-ritonavir and hydroxychloroquine or no antiviral therapy (control). The primary endpoint was an ordinal scale of organ support-free days. Analyses used a Bayesian cumulative logistic model and expressed treatment effects as an adjusted odds ratio (OR) where an OR > 1 is favorable. RESULTS: We randomized 694 patients to receive lopinavir-ritonavir (n = 255), hydroxychloroquine (n = 50), combination therapy (n = 27) or control (n = 362). The median organ support-free days among patients in lopinavir-ritonavir, hydroxychloroquine, and combination therapy groups was 4 (- 1 to 15), 0 (- 1 to 9) and-1 (- 1 to 7), respectively, compared to 6 (- 1 to 16) in the control group with in-hospital mortality of 88/249 (35%), 17/49 (35%), 13/26 (50%), respectively, compared to 106/353 (30%) in the control group. The three interventions decreased organ support-free days compared to control (OR [95% credible interval]: 0.73 [0.55, 0.99], 0.57 [0.35, 0.83] 0.41 [0.24, 0.72]), yielding posterior probabilities that reached the threshold futility (≥ 99.0%), and high probabilities of harm (98.0%, 99.9% and > 99.9%, respectively). The three interventions reduced hospital survival compared with control (OR [95% CrI]: 0.65 [0.45, 0.95], 0.56 [0.30, 0.89], and 0.36 [0.17, 0.73]), yielding high probabilities of harm (98.5% and 99.4% and 99.8%, respectively). CONCLUSION: Among critically ill patients with COVID-19, lopinavir-ritonavir, hydroxychloroquine, or combination therapy worsened outcomes compared to no antiviral therapy.

Urgent Arthroplasty Interventions During the COVID-19 Pandemic: Operating Risks in Low-Prevalence Areas.

Background and objective Orthopaedic services have reorganised their delivery of care in response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. In this study, we aimed to share our operating experience during the coronavirus disease 2019 (COVID-19) pandemic and analyse its effect on urgent hip and knee arthroplasty. Our study involved a comparative analysis between a cohort of patients from 2019 (pre-COVID) and another from 2020. Methods Tha data relating to patients undergoing urgent operations requiring arthroplasty interventions such as for infection, periprosthetic fracture (PPF) and neck of femur fracture (NOF) between April and July of 2020 and 2019 were reviewed prospectively and retrospectively. Patients were categorised according to the Royal College of Surgeons (RCS) case prioritisation and the COVID-19 risk assessment. Data were collected on 30-day mortality, readmissions, reoperations, complications, length of hospital stay and theatre efficiency. This was analysed, matched and compared. Statistical analysis was performed on categorical variables including the time to the theatre as well as dual consultant operating. Results A total of 46 consecutive patients were included in the 2020 cohort with a mean age of 78 years (range: 58-108 years). The median length of stay was 6.5 days (range: 3-35 days) and the median time to theatre for NOF patients was 23.8 hours (range: 16.2-87.7 hours). There were six complications and two deaths; one of the deaths was COVID-19-related. A total of 56 patients were included from 2019 with a mean age of 74.6 years (range: 45-88 years). The median length of stay was five days (range: 1-18 days) and the median time to theatre for NOF patients was 40.8 hours (range: 18.9-167 hours). There were four complications and one death. Conclusion Based on our findings, it is safe to perform complex surgery in a region of low community prevalence of COVID-19, and the outcomes were comparable to those from a pre-COVID-19 cohort.

Value of dynamic clinical and biomarker data for mortality risk prediction in COVID-19: a multicentre retrospective cohort study.

OBJECTIVES: Being able to predict which patients with COVID-19 are going to deteriorate is important to help identify patients for clinical and research practice. Clinical prediction models play a critical role in this process, but current models are of limited value because they are typically restricted to baseline predictors and do not always use contemporary statistical methods. We sought to explore the benefits of incorporating dynamic changes in routinely measured biomarkers, non-linear effects and applying 'state-of-the-art' statistical methods in the development of a prognostic model to predict death in hospitalised patients with COVID-19. DESIGN: The data were analysed from admissions with COVID-19 to three hospital sites. Exploratory data analysis included a graphical approach to partial correlations. Dynamic biomarkers were considered up to 5 days following admission rather than depending solely on baseline or single time-point data. Marked departures from linear effects of covariates were identified by employing smoothing splines within a generalised additive modelling framework. SETTING: 3 secondary and tertiary level centres in Greater Manchester, the UK. PARTICIPANTS: 392 hospitalised patients with a diagnosis of COVID-19. RESULTS: 392 patients with a COVID-19 diagnosis were identified. Area under the receiver operating characteristic curve increased from 0.73 using admission data alone to 0.75 when also considering results of baseline blood samples and to 0.83 when considering dynamic values of routinely collected markers. There was clear non-linearity in the association of age with patient outcome. CONCLUSIONS: This study shows that clinical prediction models to predict death in hospitalised patients with COVID-19 can be improved by taking into account both non-linear effects in covariates such as age and dynamic changes in values of biomarkers.