Elizabeth Jordan Zudock

All Publications

• Using a 29-mRNA Host Response Classifier To Detect Bacterial Coinfections and Predict Outcomes in COVID-19 Patients Presenting to the Emergency Department. Microbiology spectrum Ram-Mohan, N., Rogers, A. J., Blish, C. A., Nadeau, K. C., Zudock, E. J., Kim, D., Quinn, J. V., Sun, L., Liesenfeld, O., Yang, S. 2022: e0230522

  Abstract

  Clinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial coinfection, and determining illness severity since current practices require separate workflows. Here, we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and bacterial coinfections and predicting clinical severity of COVID-19. A total of 161 patients with PCR-confirmed COVID-19 (52.2% female; median age, 50.0 years; 51% hospitalized; 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene blood RNA), and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter. The IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrollment, and the remaining patients oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial coinfection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e., Clostridioides difficile colitis (n = 1), urinary tract infection (n = 1), and clinically diagnosed bacterial infections (n = 3), for a specificity of 99.4%. Two of 101 (2.8%) patients in the IMX-SEV-3 "Low" severity classification and 7/60 (11.7%) in the "Moderate" severity classification died within 30 days of enrollment. IMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19 and bacterial coinfections and predicted patients' risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management, including more accurate treatment decisions and optimized resource utilization. IMPORTANCE We assay the utility of the single-test IMX-BVN-3/IMX-SEV-3 classifiers that require just 2.5 mL of patient blood in concurrently detecting viral and bacterial infections as well as predicting the severity and 30-day outcome from the infection. A point-of-care device, in development, will circumvent the need for blood culturing and drastically reduce the time needed to detect an infection. This will negate the need for empirical use of broad-spectrum antibiotics and allow for antibiotic use stewardship. Additionally, accurate classification of the severity of infection and the prediction of 30-day severe outcomes will allow for appropriate allocation of hospital resources.

  View details for DOI 10.1128/spectrum.02305-22

  View details for PubMedID 36250865

• Detection of bacterial co-infections and prediction of fatal outcomes in COVID-19 patients presenting to the emergency department using a 29 mRNA host response classifier. medRxiv : the preprint server for health sciences Ram-Mohan, N., Rogers, A. J., Blish, C. A., Nadeau, K. C., Zudock, E. J., Kim, D., Quinn, J. V., Sun, L., Liesenfeld, O., Stanford COVID-19 Biobank Study Group, Yang, S. 2022

  Abstract

  Objective: Clinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial co-infection, and determining illness severity since current practices require separate workflows. Here we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting SARS-CoV-2 infection, bacterial co-infections, and predicting clinical severity of COVID-19.Methods: 161 patients with PCR-confirmed COVID-19 (52.2% female, median age 50.0 years, 51% hospitalized, 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene Blood RNA) and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter.Results: The IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrolment and the remaining oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial co-infection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e. Clostridioides difficile colitis (n=1), urinary tract infection (n=1), and clinically diagnosed bacterial infections (n=3) for a specificity of 99.4%. 2/101 (2.8%) patients in the IMX-SEV-3 Low and 7/60 (11.7%) in the Moderate severity classifications died within thirty days of enrollment.Conclusions: IMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19, bacterial co-infections, and predicted patientsa risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management including more accurate treatment decisions and optimized resource utilization.

  View details for DOI 10.1101/2022.03.14.22272394

  View details for PubMedID 35313598

• SARS-CoV-2 RNAemia predicts clinical deterioration and extrapulmonary complications from COVID-19. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America Ram-Mohan, N. n., Kim, D. n., Zudock, E. J., Hashemi, M. M., Tjandra, K. C., Rogers, A. J., Blish, C. A., Nadeau, K. C., Newberry, J. A., Quinn, J. V., O'Hara, R. n., Ashley, E. n., Nguyen, H. n., Jiang, L. n., Hung, P. n., Blomkalns, A. L., Yang, S. n. 2021

  Abstract

  The determinants of COVID-19 disease severity and extrapulmonary complications (EPCs) are poorly understood. We characterized relationships between SARS-CoV-2 RNAemia and disease severity, clinical deterioration, and specific EPCs.We used quantitative (qPCR) and digital (dPCR) PCR to quantify SARS-CoV-2 RNA from plasma in 191 patients presenting to the Emergency Department (ED) with COVID-19. We recorded patient symptoms, laboratory markers, and clinical outcomes, with a focus on oxygen requirements over time. We collected longitudinal plasma samples from a subset of patients. We characterized the role of RNAemia in predicting clinical severity and EPCs using elastic net regression.23.0% (44/191) of SARS-CoV-2 positive patients had viral RNA detected in plasma by dPCR, compared to 1.4% (2/147) by qPCR. Most patients with serial measurements had undetectable RNAemia within 10 days of symptom onset, reached maximum clinical severity within 16 days, and symptom resolution within 33 days. Initially RNAaemic patients were more likely to manifest severe disease (OR 6.72 [95% CI, 2.45 - 19.79]), worsening of disease severity (OR 2.43 [95% CI, 1.07 - 5.38]), and EPCs (OR 2.81 [95% CI, 1.26 - 6.36]). RNA load correlated with maximum severity (r = 0.47 [95% CI, 0.20 - 0.67]).dPCR is more sensitive than qPCR for the detection of SARS-CoV-2 RNAemia, which is a robust predictor of eventual COVID-19 severity and oxygen requirements, as well as EPCs. Since many COVID-19 therapies are initiated on the basis of oxygen requirements, RNAemia on presentation might serve to direct early initiation of appropriate therapies for the patients most likely to deteriorate.

  View details for DOI 10.1093/cid/ciab394

  View details for PubMedID 33949665

• SARS-CoV-2 RNAaemia predicts clinical deterioration and extrapulmonary complications from COVID-19. medRxiv : the preprint server for health sciences Ram-Mohan, N. n., Kim, D. n., Zudock, E. J., Hashemi, M. M., Tjandra, K. C., Rogers, A. J., Blish, C. A., Nadeau, K. C., Newberry, J. A., Quinn, J. V., O'Hara, R. n., Ashley, E. n., Nguyen, H. n., Jiang, L. n., Hung, P. n., Blomkalns, A. L., Yang, S. n. 2020

  Abstract

  The determinants of COVID-19 disease severity and extrapulmonary complications (EPCs) are poorly understood. We characterise the relationships between SARS-CoV-2 RNAaemia and disease severity, clinical deterioration, and specific EPCs.We used quantitative (qPCR) and digital (dPCR) PCR to quantify SARS-CoV-2 RNA from nasopharyngeal swabs and plasma in 191 patients presenting to the Emergency Department (ED) with COVID-19. We recorded patient symptoms, laboratory markers, and clinical outcomes, with a focus on oxygen requirements over time. We collected longitudinal plasma samples from a subset of patients. We characterised the role of RNAaemia in predicting clinical severity and EPCs using elastic net regression.23·0% (44/191) of SARS-CoV-2 positive patients had viral RNA detected in plasma by dPCR, compared to 1·4% (2/147) by qPCR. Most patients with serial measurements had undetectable RNAaemia 10 days after onset of symptoms, but took 16 days to reach maximum severity, and 33 days for symptoms to resolve. Initially RNAaemic patients were more likely to manifest severe disease (OR 6·72 [95% CI, 2·45 - 19·79]), worsening of disease severity (OR 2·43 [95% CI, 1·07 - 5·38]), and EPCs (OR 2·81 [95% CI, 1·26 - 6·36]). RNA load correlated with maximum severity ( r = 0·47 [95% CI, 0·20 - 0·67]).dPCR is more sensitive than qPCR for the detection of SARS-CoV-2 RNAaemia, which is a robust predictor of eventual COVID-19 severity and oxygen requirements, as well as EPCs. Since many COVID-19 therapies are initiated on the basis of oxygen requirements, RNAaemia on presentation might serve to direct early initiation of appropriate therapies for the patients most likely to deteriorate.NIH/NIAID (Grants R01A153133, R01AI137272, and 3U19AI057229 - 17W1 COVID SUPP #2) and a donation from Eva Grove.Evidence before this study: The varied clinical manifestations of COVID-19 have directed attention to the distribution of SARS-CoV-2 in the body. Although most concentrated and tested for in the nasopharynx, SARS-CoV-2 RNA has been found in blood, stool, and numerous tissues, raising questions about dissemination of viral RNA throughout the body, and the role of this process in disease severity and extrapulmonary complications. Recent studies have detected low levels of SARS-CoV-2 RNA in blood using either quantitative reverse transcriptase real-time PCR (qPCR) or droplet digital PCR (dPCR), and have associated RNAaemia with disease severity and biomarkers of dysregulated immune response.Added value of this study: We quantified SARS-CoV-2 RNA in the nasopharynx and plasma of patients presenting to the Emergency Department with COVID-19, and found an array-based dPCR platform to be markedly more sensitive than qPCR for detection of SARS-CoV-2 RNA, with a simplified workflow well-suited to clinical adoption. We collected serial plasma samples during patients' course of illness, and showed that SARS-CoV-2 RNAaemia peaks early, while clinical condition often continues to worsen. Our findings confirm the association between RNAaemia and disease severity, and additionally demonstrate a role for RNAaemia in predicting future deterioration and specific extrapulmonary complications.Implications of all the available evidence: Variation in SARS-CoV-2 RNAaemia may help explain disparities in disease severity and extrapulmonary complications from COVID-19. Testing for RNAaemia with dPCR early in the course of illness may help guide patient triage and management.

  View details for DOI 10.1101/2020.12.19.20248561

  View details for PubMedID 33398290

  View details for PubMedCentralID PMC7781329