Effect of P2Y12 Inhibitors on Organ Support-Free Survival in Critically Ill Patients Hospitalized for COVID-19: A Randomized Clinical Trial.

Importance: Platelet activation is a potential therapeutic target in patients with COVID-19. Objective: To evaluate the effect of P2Y12 inhibition among critically ill patients hospitalized for COVID-19. Design, Setting, and Participants: This international, open-label, adaptive platform, 1:1 randomized clinical trial included critically ill (requiring intensive care-level support) patients hospitalized with COVID-19. Patients were enrolled between February 26, 2021, through June 22, 2022. Enrollment was discontinued on June 22, 2022, by the trial leadership in coordination with the study sponsor given a marked slowing of the enrollment rate of critically ill patients. Intervention: Participants were randomly assigned to receive a P2Y12 inhibitor or no P2Y12 inhibitor (usual care) for 14 days or until hospital discharge, whichever was sooner. Ticagrelor was the preferred P2Y12 inhibitor. Main Outcomes and Measures: The primary outcome was organ support-free days, evaluated on an ordinal scale that combined in-hospital death and, for participants who survived to hospital discharge, the number of days free of cardiovascular or respiratory organ support up to day 21 of the index hospitalization. The primary safety outcome was major bleeding, as defined by the International Society on Thrombosis and Hemostasis. Results: At the time of trial termination, 949 participants (median [IQR] age, 56 [46-65] years; 603 male [63.5%]) had been randomly assigned, 479 to the P2Y12 inhibitor group and 470 to usual care. In the P2Y12 inhibitor group, ticagrelor was used in 372 participants (78.8%) and clopidogrel in 100 participants (21.2%). The estimated adjusted odds ratio (AOR) for the effect of P2Y12 inhibitor on organ support-free days was 1.07 (95% credible interval, 0.85-1.33). The posterior probability of superiority (defined as an OR > 1.0) was 72.9%. Overall, 354 participants (74.5%) in the P2Y12 inhibitor group and 339 participants (72.4%) in the usual care group survived to hospital discharge (median AOR, 1.15; 95% credible interval, 0.84-1.55; posterior probability of superiority, 80.8%). Major bleeding occurred in 13 participants (2.7%) in the P2Y12 inhibitor group and 13 (2.8%) in the usual care group. The estimated mortality rate at 90 days for the P2Y12 inhibitor group was 25.5% and for the usual care group was 27.0% (adjusted hazard ratio, 0.96; 95% CI, 0.76-1.23; P = .77). Conclusions and Relevance: In this randomized clinical trial of critically ill participants hospitalized for COVID-19, treatment with a P2Y12 inhibitor did not improve the number of days alive and free of cardiovascular or respiratory organ support. The use of the P2Y12 inhibitor did not increase major bleeding compared with usual care. These data do not support routine use of a P2Y12 inhibitor in critically ill patients hospitalized for COVID-19. Trial Registration: ClinicalTrials.gov Identifier: NCT04505774.

Improving wastewater-based epidemiology performance through streamlined automation

Wastewater-based epidemiology (WBE) has enabled us to describe Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections in populations. However, implementation of wastewater monitoring of SARS-CoV-2 is limited due to the need for expert staff, expensive equipment, and prolonged processing times. As WBE increases in scope (beyond SARS-CoV-2) and scale (beyond developed regions), there is a need to make WBE processes simpler, cheaper, and faster. We developed an automated workflow based on a simplified method termed exclusion-based sample preparation (ESP). Our automated workflow takes 40 minutes from raw wastewater to purified RNA, which is several times faster than conventional WBE methods. The total assay cost per sample/replicate is $6.50 which includes consumables and reagents for concentration, extraction, and RT-qPCR quantification. The assay complexity is reduced significantly, as extraction and concentration steps are integrated and automated. The high recovery efficiency of the automated assay (84.5±25.4%) yielded an improved Limit of Detection (LoDAutomated=40 copies/mL) compared to the manual process (LoDManual=206 copies/mL), increasing analytical sensitivity. We validated the performance of the automated workflow by comparing it with the manual method using wastewater samples from several locations. The results from the two methods correlated strongly (r=0.953), while the automated method was shown to be more precise. In 83% of the samples, the automated method showed lower variation between replicates, which is likely due to higher technical errors in the manual process e.g., pipetting. Our automated wastewater workflow can support the expansion of WBE in the fight against Coronavirus Disease of 2019 (COVID-19) and other epidemics. Graphical

Improving wastewater-based epidemiology performance through streamlined automation.

Wastewater-based epidemiology (WBE) has enabled us to describe Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections in populations. However, implementation of wastewater monitoring of SARS-CoV-2 is limited due to the need for expert staff, expensive equipment, and prolonged processing times. As WBE increases in scope (beyond SARS-CoV-2) and scale (beyond developed regions), there is a need to make WBE processes simpler, cheaper, and faster. We developed an automated workflow based on a simplified method termed exclusion-based sample preparation (ESP). Our automated workflow takes 40 min from raw wastewater to purified RNA, which is several times faster than conventional WBE methods. The total assay cost per sample/replicate is $6.50 which includes consumables and reagents for concentration, extraction, and RT-qPCR quantification. The assay complexity is reduced significantly, as extraction and concentration steps are integrated and automated. The high recovery efficiency of the automated assay (84.5 ± 25.4%) yielded an improved Limit of Detection (LoDAutomated=40 copies/mL) compared to the manual process (LoDManual=206 copies/mL), increasing analytical sensitivity. We validated the performance of the automated workflow by comparing it with the manual method using wastewater samples from several locations. The results from the two methods correlated strongly (r = 0.953), while the automated method was shown to be more precise. In 83% of the samples, the automated method showed lower variation between replicates, which is likely due to higher technical errors in the manual process e.g., pipetting. Our automated wastewater workflow can support the expansion of WBE in the fight against Coronavirus Disease of 2019 (COVID-19) and other epidemics.

Stabilization of SARS-CoV-2 RNA in wastewater via rapid RNA extraction.

Wastewater-based Epidemiology (WBE) has contributed to surveillance of SARS-CoV-2 in communities across the world. Both symptomatic and asymptomatic patients with COVID-19 can shed the virus through the gastrointestinal tract, enabling the quantification of the virus in stool and ultimately in wastewater (WW). Unfortunately, instability of SARS-CoV-2 RNA in wastewater limits the utility of WBE programs, particularly in remote/rural regions where reliable cold storage and/or rapid shipping may be unavailable. This study examined whether rapid SARS-CoV-2 RNA extraction on the day of sample collection could minimize degradation. Importantly, the extraction technology used in these experiments, termed exclusion-based sample preparation (ESP), is lightweight, portable, and electricity-free, making it suitable for implementation in remote settings. We demonstrated that immediate RNA extraction followed by ambient storage significantly increased the RNA half-life compared to raw wastewater samples stored at both 4 °C or ambient temperature. Given that RNA degradation negatively impacts both the sensitivity and precision of WBE measurements, efforts must be made to mitigate degradation in order to maximize the potential impact of WBE on public health.

Wastewater Surveillance-"Messy" Science With Public Health Potential

Marginalized, rural, and resource-poor communities and their associated public health institutions stand to benefit from timely wastewater disease data that can inform local decision-making and the community members. The utility of wastewater analysis goes beyond infectious disease surveillance: scientists are testing wastewater for many biomarkers of public health importance, such as pharmaceutical metabolites11 and markers of exposure to air pollution.12 Wastewater surveillance isa particularly attractive public health tool for communities with limited access to clinical testing or health care. [...]there is an opportunity for community-engaged research to design wastewater analysis approaches that meet the needs of these communities. The Centers for Disease Control and Prevention has provided laboratory capacity grants to many states to enhance their wastewater surveillance programs.

Therapeutic Anticoagulation with Heparin in Noncritically Ill Patients with Covid-19.

BACKGROUND: Thrombosis and inflammation may contribute to the risk of death and complications among patients with coronavirus disease 2019 (Covid-19). We hypothesized that therapeutic-dose anticoagulation may improve outcomes in noncritically ill patients who are hospitalized with Covid-19. METHODS: In this open-label, adaptive, multiplatform, controlled trial, we randomly assigned patients who were hospitalized with Covid-19 and who were not critically ill (which was defined as an absence of critical care-level organ support at enrollment) to receive pragmatically defined regimens of either therapeutic-dose anticoagulation with heparin or usual-care pharmacologic thromboprophylaxis. The primary outcome was organ support-free days, evaluated on an ordinal scale that combined in-hospital death (assigned a value of -1) and the number of days free of cardiovascular or respiratory organ support up to day 21 among patients who survived to hospital discharge. This outcome was evaluated with the use of a Bayesian statistical model for all patients and according to the baseline d-dimer level. RESULTS: The trial was stopped when prespecified criteria for the superiority of therapeutic-dose anticoagulation were met. Among 2219 patients in the final analysis, the probability that therapeutic-dose anticoagulation increased organ support-free days as compared with usual-care thromboprophylaxis was 98.6% (adjusted odds ratio, 1.27; 95% credible interval, 1.03 to 1.58). The adjusted absolute between-group difference in survival until hospital discharge without organ support favoring therapeutic-dose anticoagulation was 4.0 percentage points (95% credible interval, 0.5 to 7.2). The final probability of the superiority of therapeutic-dose anticoagulation over usual-care thromboprophylaxis was 97.3% in the high d-dimer cohort, 92.9% in the low d-dimer cohort, and 97.3% in the unknown d-dimer cohort. Major bleeding occurred in 1.9% of the patients receiving therapeutic-dose anticoagulation and in 0.9% of those receiving thromboprophylaxis. CONCLUSIONS: In noncritically ill patients with Covid-19, an initial strategy of therapeutic-dose anticoagulation with heparin increased the probability of survival to hospital discharge with reduced use of cardiovascular or respiratory organ support as compared with usual-care thromboprophylaxis. (ATTACC, ACTIV-4a, and REMAP-CAP ClinicalTrials.gov numbers, NCT04372589, NCT04505774, NCT04359277, and NCT02735707.).

Development and validation of a prognostic 40-day mortality risk model among hospitalized patients with COVID-19.

OBJECTIVES: The development of a prognostic mortality risk model for hospitalized COVID-19 patients may facilitate patient treatment planning, comparisons of therapeutic strategies, and public health preparations. METHODS: We retrospectively reviewed the electronic health records of patients hospitalized within a 13-hospital New Jersey USA network between March 1, 2020 and April 22, 2020 with positive polymerase chain reaction results for SARS-CoV-2, with follow-up through May 29, 2020. With death or hospital discharge by day 40 as the primary endpoint, we used univariate followed by stepwise multivariate proportional hazard models to develop a risk score on one-half the data set, validated on the remainder, and converted the risk score into a patient-level predictive probability of 40-day mortality based on the combined dataset. RESULTS: The study population consisted of 3123 hospitalized COVID-19 patients; median age 63 years; 60% were men; 42% had >3 coexisting conditions. 713 (23%) patients died within 40 days of hospitalization for COVID-19. From 22 potential candidate factors 6 were found to be independent predictors of mortality and were included in the risk score model: age, respiratory rate ≥25/minute upon hospital presentation, oxygenation <94% on hospital presentation, and pre-hospital comorbidities of hypertension, coronary artery disease, or chronic renal disease. The risk score was highly prognostic of mortality in a training set and confirmatory set yielding in the combined dataset a hazard ratio of 1.80 (95% CI, 1.72, 1.87) for one unit increases. Using observed mortality within 20 equally sized bins of risk scores, a predictive model for an individual's 40-day risk of mortality was generated as -14.258 + 13.460*RS + 1.585*(RS-2.524)^2-0.403*(RS-2.524)^3. An online calculator of this 40-day COVID-19 mortality risk score is available at www.HackensackMeridianHealth.org/CovidRS. CONCLUSIONS: A risk score using six variables is able to prognosticate mortality within 40-days of hospitalization for COVID-19. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT04347993.

Anti-Thrombotic Therapy to Ameliorate Complications of COVID-19 (ATTACC): Study design and methodology for an international, adaptive Bayesian randomized controlled trial.

BACKGROUND: Mortality from COVID-19 is high among hospitalized patients and effective therapeutics are lacking. Hypercoagulability, thrombosis and hyperinflammation occur in COVID-19 and may contribute to severe complications. Therapeutic anticoagulation may improve clinical outcomes through anti-thrombotic, anti-inflammatory and anti-viral mechanisms. Our primary objective is to evaluate whether therapeutic-dose anticoagulation with low-molecular-weight heparin or unfractionated heparin prevents mechanical ventilation and/or death in patients hospitalized with COVID-19 compared to usual care. METHODS: An international, open-label, adaptive randomized controlled trial. Using a Bayesian framework, the trial will declare results as soon as pre-specified posterior probabilities for superiority, futility, or harm are reached. The trial uses response-adaptive randomization to maximize the probability that patients will receive the more beneficial treatment approach, as treatment effect information accumulates within the trial. By leveraging a common data safety monitoring board and pooling data with a second similar international Bayesian adaptive trial (REMAP-COVID anticoagulation domain), treatment efficacy and safety will be evaluated as efficiently as possible. The primary outcome is an ordinal endpoint with three possible outcomes based on the worst status of each patient through day 30: no requirement for invasive mechanical ventilation, invasive mechanical ventilation or death. CONCLUSION: Using an adaptive trial design, the Anti-Thrombotic Therapy To Ameliorate Complications of COVID-19 trial will establish whether therapeutic anticoagulation can reduce mortality and/or avoid the need for mechanical ventilation in patients hospitalized with COVID-19. Leveraging existing networks to recruit sites will increase enrollment and mitigate enrollment risk in sites with declining COVID-19 cases.

Hydroxychloroquine and tocilizumab therapy in COVID-19 patients-An observational study.

Hydroxychloroquine has been touted as a potential COVID-19 treatment. Tocilizumab, an inhibitor of IL-6, has also been proposed as a treatment of critically ill patients. In this retrospective observational cohort study drawn from electronic health records we sought to describe the association between mortality and hydroxychloroquine or tocilizumab therapy among hospitalized COVID-19 patients. Patients were hospitalized at a 13-hospital network spanning New Jersey USA between March 1, 2020 and April 22, 2020 with positive polymerase chain reaction results for SARS-CoV-2. Follow up was through May 5, 2020. Among 2512 hospitalized patients with COVID-19 there have been 547 deaths (22%), 1539 (61%) discharges and 426 (17%) remain hospitalized. 1914 (76%) received at least one dose of hydroxychloroquine and 1473 (59%) received hydroxychloroquine with azithromycin. After adjusting for imbalances via propensity modeling, compared to receiving neither drug, there were no significant differences in associated mortality for patients receiving any hydroxychloroquine during the hospitalization (HR, 0.99 [95% CI, 0.80-1.22]), hydroxychloroquine alone (HR, 1.02 [95% CI, 0.83-1.27]), or hydroxychloroquine with azithromycin (HR, 0.98 [95% CI, 0.75-1.28]). The 30-day unadjusted mortality for patients receiving hydroxychloroquine alone, azithromycin alone, the combination or neither drug was 25%, 20%, 18%, and 20%, respectively. Among 547 evaluable ICU patients, including 134 receiving tocilizumab in the ICU, an exploratory analysis found a trend towards an improved survival association with tocilizumab treatment (adjusted HR, 0.76 [95% CI, 0.57-1.00]), with 30 day unadjusted mortality with and without tocilizumab of 46% versus 56%. This observational cohort study suggests hydroxychloroquine, either alone or in combination with azithromycin, was not associated with a survival benefit among hospitalized COVID-19 patients. Tocilizumab demonstrated a trend association towards reduced mortality among ICU patients. Our findings are limited to hospitalized patients and must be interpreted with caution while awaiting results of randomized trials. Trial Registration: Clinicaltrials.gov Identifier: NCT04347993.