Cost-Effectiveness of Convalescent Plasma for COVID-19: A Cost-effectiveness Analysis of the CONCOR-1 Randomized Trial (preprint)

Background The CONvalescent Plasma for Hospitalized Adults With COVID-19 Respiratory Illness (CONCOR-1) trial was a multicenter randomized controlled trial assessing convalescent plasma in hospitalized COVID-19 patients. Though stopped early due to the lack of treatment benefit, the cost-effectiveness of convalescent plasma provides insight into its potential as an alternative treatment option in resource constrained settings.Methods Individual patient data on health outcomes and healthcare resource utilization from the CONCOR-1 trial were used to conduct the analysis from the Canadian public payer’s perspective with a time horizon of 30 days post-randomization. Baseline and 30-day EQ-5D-5L was measured to calculate quality-adjusted survival. All costs are presented in 2021 Canadian dollars. The base case assessed the EQ-5D-5L scores of patients reporting at both timepoints, and a utility score of 0 was assigned for patients who died within 30 days. Costs for all patients enrolled in the study were used. The sensitivity analysis utilizes EQ-5D-5L scores from the same population but only uses the costs from this population.Results 940 patients were randomized: 627 received CCP and 313 received standard care. The total costs were $28,716 (standard deviation, $25,380) and $24,258 ($22,939) for the convalescent plasma and standard care arms respectively. EQ-5D-5L scores were 0.61 both arms (p = 0.85) at baseline. At 30 days, EQ-5D-5L scores were 0.63 and 0.64 for patients in the convalescent plasma and standard care arms respectively (p = 0.46). The incremental cost was $4,458 and incremental quality-adjusted life day was − 0.078.Conclusion These results indicate that convalescent plasma was less effective and more costly than standard care in treating hospitalized patients with COVID-19. The sensitivity analysis yielded similar results to the base case analysis.

A Machine Learning Model Incorporating Laboratory Blood Tests Discriminates Between SARS-CoV-2 and Influenza Infections at Emergency Department Visit (preprint)

Introduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza virus are contagious respiratory pathogens with similar symptoms but require different treatment and management strategies. This study investigated whether laboratory blood tests can discriminate between SARS-CoV-2 and influenza infections at emergency department (ED) presentation. Methods 723 influenza A/B positive (2018/1/1 to 2020/3/15) and 1,281 SARS-CoV-2 positive (2020/3/11 to 2020/6/30) ED patients were retrospectively analyzed. Laboratory test results completed within 48 hours prior to reporting of virus RT-PCR results, as well as patient demographics were included to train and validate a random forest (RF) model. The dataset was randomly divided into training (2/3) and testing (1/3) sets with the same SARS-CoV-2/influenza ratio. The Shapley Additive Explanations technique was employed to visualize the impact of each laboratory test on the differentiation. Results The RF model incorporating results from 15 laboratory tests and demographic characteristics discriminated SARS-CoV-2 and influenza infections, with an area under the ROC curve value 0.90 in the independent testing set. The overall agreement with the RT-PCR results was 83% (95% CI: 80-86%). The test with the greatest impact on the differentiation was serum total calcium level. Further, the model achieved an AUC of 0.82 in a new dataset including 519 SARS-CoV-2 ED patients (2020/12/1 to 2021/2/28) and the previous 723 influenza positive patients. Serum calcium level remained the most impactful feature on the differentiation. Conclusion We identified characteristic laboratory test profiles differentiating SARS-CoV-2 and influenza infections, which may be useful for the preparedness of overlapping COVID-19 resurgence and future seasonal influenza.

More rapid, robust and sustainable antibody responses to mRNA COVID-19 vaccine in convalescent COVID-19 individuals (preprint)

Longitudinal studies are needed to evaluate the SARS-CoV-2 mRNA vaccine antibody response under "real-world" conditions. This longitudinal study investigated the quantity and quality of SARS-CoV-2 antibody response in 846 specimens from 350 subjects: comparing BNT162b2-vaccinated individuals (19 previously diagnosed with COVID-19 [RecoVax]; 49 never been diagnosed [NaiveVax]) to 122 hospitalized unvaccinated (HospNoVax) and 160 outpatient unvaccinated (OutPtNoVax) COVID-19 patients. NaiveVax experienced a delay in generating SARS-CoV-2 total antibody levels (TAb) and neutralizing antibodies (SNAb) after the 1st vaccine dose (D1), but a rapid increase in antibody levels was observed after the 2nd dose (D2). However, these never reached the robust levels observed in RecoVax. In fact, NaiveVax TAb and SNAb levels decreased 4-weeks post-D2 (p=0.003;p<0.001). For the most part, RecoVax TAb persisted throughout this study, after reaching maximal levels 2-weeks post-D2; but SNAb decreased significantly [~]6-months post-D1 (p=0.002). Although NaiveVax avidity lagged behind that of RecoVax for most of the follow-up periods, NaiveVax did reach similar avidity by [~]6-months post-D1. These data suggest that one vaccine dose elicits maximal antibody response in RecoVax and may be sufficient. Also, despite decreasing levels in TAb and SNAb overtime, long-term avidity maybe a measure worth evaluating and possibly correlating to vaccine efficacy.

SARS-CoV-2 Antibody Response in Patients Undergoing Kidney Transplantation (preprint)

Abstract The response of the immune system to COVID-19 in end stage kidney disease patients who undergo kidney transplantation has yet to be described. We report data on 72 patients who underwent SARS-CoV-2 antibody testing both before and after kidney transplantation and were followed for a median of 186 days (range 83, 277). Of the 25 patients with a positive antibody test at the time of transplant, 17 (68%) remained positive after transplantation. Patients were significantly more likely to have a persistently positive test if they reported a symptomatic COVID-19 infection prior to transplant (p=0.01). SARS-CoV-2 IgG index values were measured in a subset of kidney transplant recipients and compared to wait -listed dialysis patients. These assays demonstrated a more significant decline in IgG (58% versus 14% p = 0.008) in transplant recipients when compared to dialysis patients tested during the same time period. Additional analysis of the quality of the immune response measuring the binding of SARS-CoV-2 antibodies to the receptor-binding domain (RBD binding), the antibody neutralizing capability, and the antibody avidity demonstrated a more pronounced effect when comparing pre-transplant values to post-induction therapy/post transplant values. The attenuated IgG response seen in transplant patients compared to dialysis patients after induction therapy requires further study. These data have important implications for post-transplant management of vaccinated dialysis patients.

Convalescent plasma for hospitalized patients with COVID-19 and the effect of plasma antibodies: a randomized controlled, open-label trial (preprint)

The efficacy of convalescent plasma for COVID-19 is unclear. While most randomized controlled trials have shown negative results, uncontrolled studies have suggested that the antibody content may influence patient outcomes. We conducted an open-label, randomized controlled trial of convalescent plasma for adults with COVID-19 receiving oxygen within 12 days of respiratory symptom onset. Patients were allocated 2:1 to 500 mL of convalescent plasma or standard of care. The composite primary outcome was intubation or death by 30 days. The effect of convalescent plasma antibodies on the primary outcome was assessed by logistic regression. The trial was terminated at 78% of planned enrollment after meeting stopping criteria for futility. 940 patients were randomized and 921 patients were included in the intent-to-treat analysis. Intubation or death occurred in 199/614 (32.4%) in the convalescent plasma arm and 86/307 (28.0%) in the standard of care arm; relative risk (RR) 1.16 (95% confidence interval (CI) 0.94-1.43; p=0.18). Patients in the convalescent plasma arm had more serious adverse events (33.4% vs. 26.4%; RR=1.27, 95% CI 1.02-1.57, p=0.034). The antibody content significantly modulated the therapeutic effect of convalescent plasma. In multivariate analysis, each standard log increase in neutralization or antibody-dependent cellular cytotoxicity independently reduced the potential harmful effect of plasma (OR=0.74; 0.57-0.95 and OR=0.66; 0.50-0.87, respectively), while IgG against the full transmembrane Spike protein increased it (OR=1.53, 95% CI 1.14-2.05). Convalescent plasma did not reduce the risk of intubation or death at 30 days among hospitalized patients with COVID-19. Transfusion of convalescent plasma with unfavourable antibody profiles may be associated with worse clinical outcomes compared to standard care.

Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps (preprint)

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 115 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS), remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, evident as a function of varying viral load (high vs. low) during the course of infection and specific, transcriptional dysregulation in splicing isoforms, T cell receptor expression, and cellular expression states. In particular, cardiac and lung tissues revealed the largest degree of splicing isoform switching and cell expression state loss. Overall, these findings reveal a systemic disruption of cellular and transcriptional pathways from COVID-19 across all tissues, which can inform subsequent studies to combat the mortality of COVID-19, as well to better understand the molecular dynamics of lethal SARS-CoV-2 infection and other viruses.

Early introductions and community transmission of SARS-CoV-2 variant B.1.1.7 in the United States (preprint)

The emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a global public health concern because of its increased transmissibility. Over 2500 COVID-19 cases associated with this variant have been detected in the US since December 2020, but the extent of establishment is relatively unknown. Using travel, genomic, and diagnostic data, we highlight the primary ports of entry for B.1.1.7 in the US and locations of possible underreporting of B.1.1.7 cases. Furthermore, we found evidence for many independent B.1.1.7 establishments starting in early December 2020, followed by interstate spread by the end of the month. Finally, we project that B.1.1.7 will be the dominant lineage in many states by mid to late March. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response.

SARS-CoV-2 Viral Load Predicts Mortality in Patients with and Without Cancer Who are Hospitalized with Coronavirus Disease 2019 (preprint)

Patients with cancer may be at increased risk of severe coronavirus disease 2019 (COVID-19), but the role of viral load on this risk is unknown. We measured SARS-CoV-2 viral load using cycle threshold (CT) values from reverse transcription-polymerase chain reaction assays applied to nasopharyngeal swab specimens in 100 patients with cancer and 2914 without cancer admitted to three New York City hospitals. Overall, the in-hospital mortality rate was 39.5% among patients with a high viral load (CT<25), 25.6% among patients with a medium viral load (CT 25-30), and 15.7% among patients with a low viral load (CT>30; P<0.001). Similar findings were observed in patients with cancer (high, 45.0% mortality; medium, 29.2%; low, 13.9%; P=0.003). Patients with hematologic malignancies had higher median viral loads (CT=25.0) than patients without cancer (CT=29.2; P=0.0039). SARS-CoV-2 viral load results may offer vital prognostic information for patients with and without cancer who are hospitalied with COVID-19.Funding: This work was partially supported by the National Centerfor Advancing Translational Science [UL1 TR002384 to Julianne Imperato-McGinley] at the National Institutes of Health.Conflict of Interest: L.F.W. reports receiving consulting fees from Roche Molecular Systems, Inc. M.M.S. receives grant support from Amgen, Inc. All other authors report no potential conflicts of interest.Ethical Approval Statement: The study was approved by the Institutional Review Board (#20-03021681) at Weill Cornell Medicine with a waiver of informed consent

Routine laboratory blood tests predict SARS-CoV-2 infection using machine learning (preprint)

BackgroundAccurate diagnostic strategies to rapidly identify SARS-CoV-2 positive individuals for management of patient care and protection of health care personnel are urgently needed. The predominant diagnostic test is viral RNA detection by RT-PCR from nasopharyngeal swabs specimens, however the results are not promptly obtainable in all patient care locations. Routine laboratory testing, in contrast, is readily available with a turn-around time (TAT) usually within 1-2 hours. MethodWe developed a machine learning model incorporating patient demographic features (age, sex, race) with 27 routine laboratory tests to predict an individuals SARS-CoV-2 infection status. Laboratory test results obtained within two days before the release of SARS-CoV-2-RT-PCR result were used to train a gradient boosted decision tree (GBDT) model from 3,356 SARS-CoV-2 RT-PCR tested patients (1,402 positive and 1,954 negative) evaluated at a metropolitan hospital. ResultsThe model achieved an area under the receiver operating characteristic curve (AUC) of 0.854 (95% CI: 0.829-0.878). Application of this model to an independent patient dataset from a separate hospital resulted in a comparable AUC (0.838), validating the generalization of its use. Moreover, our model predicted initial SARS-CoV-2 RT-PCR positivity in 66% individuals whose RT-PCR result changed from negative to positive within two days. ConclusionThis model employing routine laboratory test results offers opportunities for early and rapid identification of high-risk SARS-CoV-2 infected patients before their RT-PCR results are available. It may play an important role in assisting the identification of SARS-COV-2 infected patients in areas where RT-PCR testing is not accessible due to financial or supply constraints.

Rapid implementation of SARS-CoV-2 emergency use authorization RT-PCR testing and experience at an academic medical institution (preprint)

An epidemic caused by an outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China in December 2019 has since rapidly spread internationally, requiring urgent response from the clinical diagnostics community. We present a detailed overview of the clinical validation and implementation of the first laboratory-developed real-time reverse-transcription-PCR (rRT-PCR) test offered in the NewYork-Presbyterian Hospital system following the emergency use authority (EUA) guidance issued by the US Food and Drug Administration. Validation was performed on nasopharyngeal and sputum specimens (n=124) using newly designed dual-target rRT-PCR (altona RealStar SARS-CoV-2 Reagent) for detecting of SARS-CoV-2 in upper respiratory and lower respiratory tract specimens, including bronchoalveolar lavage and tracheal aspirates. Accuracy testing demonstrated excellent assay agreement between expected and observed values. The limit of detection (LOD) was 2.7 and 23.0 gene copies/reaction for nasopharyngeal and sputum specimens, respectively. Retrospective analysis of 1,694 tests from 1,571 patients revealed increased positivity in older patients and males compared to females, and an increasing positivity rate from approximately 20% at the start of testing to 50% at the end of testing three weeks later. Our findings demonstrate that the assay accurately and sensitively identifies SARS-CoV-2 in multiple specimen types in the clinical setting and summarizes clinical data from early in the epidemic in New York City.

Clinical Performance of SARS-CoV-2 Molecular Testing (preprint)

Molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the gold standard for diagnosis of coronavirus disease 2019 (COVID-19), but the test clinical performance is poorly understood. From 3/10/2020-5/1/2020 NewYork-Presbyterian laboratories performed 27,377 SARS-CoV-2 molecular assays from 22,338 patients. Repeat testing was performed in 3,432 patients, of which 2,413 had negative and 1,019 had positive first day results. Repeat-tested patients were more likely to be older, male, African-American or Hispanic, and to have severe disease. Among the patients with initially negative results, 18.6% became positive upon repeat-testing. Only 58.1% of any-time positive patients had a result of "detected" on the first test. The clinical sensitivity of COVID-19 molecular assays is estimated between 66.2 % and 95.6%, depending on the unknown number of false negative results in single-tested patients. Conversion to a negative result is unlikely to occur before 15 to 20 days after initial testing or 20-30 days after the onset of symptoms, with 50% conversion occurring at 28 days after initial testing. Forty-nine initially-positive patients converted to negative and then back to positive in subsequent days. Conversion from first day negative to positive results increased linearly with each day of testing, reaching 25% probability in 20 days. In summary, our study provides estimates of the clinical performance of SARS-CoV-2 molecular assays and suggests time frames for appropriate repeat testing, namely 15 to 20 days after a positive test and the same or next 2 days after a negative test in a patient with high suspicion for COVID-19.

Host, Viral, and Environmental Transcriptome Profiles of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) (preprint)

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused thousands of deaths worldwide, including >18,000 in New York City (NYC) alone. The sudden emergence of this pandemic has highlighted a pressing clinical need for rapid, scalable diagnostics that can detect infection, interrogate strain evolution, and identify novel patient biomarkers. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs, plus a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, bacterial, and viral profiling. We applied both technologies across 857 SARS-CoV-2 clinical specimens and 86 NYC subway samples, providing a broad molecular portrait of the COVID-19 NYC outbreak. Our results define new features of SARS-CoV-2 evolution, nominate a novel, NYC-enriched viral subclade, reveal specific host responses in interferon, ACE, hematological, and olfaction pathways, and examine risks associated with use of ACE inhibitors and angiotensin receptor blockers. Together, these findings have immediate applications to SARS-CoV-2 diagnostics, public health, and new therapeutic targets.