COVID-19-neutralizing antibodies predict disease severity and survival.

Coronavirus disease 2019 (COVID-19) exhibits variable symptom severity ranging from asymptomatic to life-threatening, yet the relationship between severity and the humoral immune response is poorly understood. We examined antibody responses in 113 COVID-19 patients and found that severe cases resulting in intubation or death exhibited increased inflammatory markers, lymphopenia, pro-inflammatory cytokines, and high anti-receptor binding domain (RBD) antibody levels. Although anti-RBD immunoglobulin G (IgG) levels generally correlated with neutralization titer, quantitation of neutralization potency revealed that high potency was a predictor of survival. In addition to neutralization of wild-type SARS-CoV-2, patient sera were also able to neutralize the recently emerged SARS-CoV-2 mutant D614G, suggesting cross-protection from reinfection by either strain. However, SARS-CoV-2 sera generally lacked cross-neutralization to a highly homologous pre-emergent bat coronavirus, WIV1-CoV, which has not yet crossed the species barrier. These results highlight the importance of neutralizing humoral immunity on disease progression and the need to develop broadly protective interventions to prevent future coronavirus pandemics.

Comparative Immunogenicity and Effectiveness of mRNA-1273, BNT162b2, and Ad26.COV2.S COVID-19 Vaccines.

BACKGROUND: Understanding immunogenicity and effectiveness of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines is critical to guide rational use. METHODS: We compared the immunogenicity of mRNA-1273, BNT-162b2, and Ad26.COV2.S in healthy ambulatory adults. We performed an inverse-variance meta-analysis of population-level effectiveness from public health reports in > 40 million individuals. RESULTS: A single dose of either mRNA vaccine yielded comparable antibody and neutralization titers to convalescent individuals. Ad26.COV2.S yielded lower antibody concentrations and frequently undetectable neutralization titers. Bulk and cytotoxic T-cell responses were higher in mRNA1273 and BNT162b2 than Ad26.COV2.S recipients. Regardless of vaccine, <50% of vaccinees demonstrated CD8+ T-cell responses. Antibody concentrations and neutralization titers increased comparably after the first dose of either vaccine, and further in recipients of a second dose. Prior infection was associated with high antibody concentrations and neutralization even after a single dose and regardless of vaccine. Neutralization of Beta, Gamma, and Delta strains were poorer regardless of vaccine. In meta-analysis, relative to mRNA1273 the effectiveness of BNT162b2 was lower against infection and hospitalization, and Ad26COV2.S was lower against infection, hospitalization, and death. CONCLUSIONS: Variation in the immunogenicity correlates with variable effectiveness of the 3 vaccines deployed in the United States.

Determining the Incidence of Asymptomatic SARS-CoV-2 Among Early Recipients of COVID-19 Vaccines (DISCOVER-COVID-19): A Prospective Cohort Study of Healthcare Workers Before, During and After Vaccination.

The impact of coronavirus disease 2019 vaccination on viral characteristics of breakthrough infections is unknown. In this prospective cohort study, incidence of severe acute respiratory syndrome coronavirus 2 infection decreased following vaccination. Although asymptomatic positive tests were observed following vaccination, the higher cycle thresholds, repeat negative tests, and inability to culture virus raise questions about their clinical significance.

COVID-19 Seroprevalence in ED Health Care Professionals Study: A Cross-Sectional Study.

INTRODUCTION: ED health care professionals are at the frontline of evaluation and management of patients with acute, and often undifferentiated, illness. During the initial phase of the SARS-CoV-2 outbreak, there were concerns that ED health care professionals may have been at increased risk of exposure to SARS-CoV-2 due to difficulty in early identification of patients. This study assessed the seroprevalence of SARS-CoV-2 antibodies among ED health care professionals without confirmed history of COVID-19 infection at a quaternary academic medical center. METHODS: This study used a cross-sectional design. An ED health care professional was deemed eligible if they had worked at least 4 shifts in the adult emergency department from April 1, 2020, through May 31, 2020, were asymptomatic on the day of blood draw, and were not known to have had prior documented COVID-19 infection. The study period was December 17, 2020, to January 27, 2021. Eligible participants completed a questionnaire and had a blood sample drawn. Samples were run on the Roche Cobas Elecsys Anti-SARS-CoV-2 antibody assay. RESULTS: Of 103 health care professionals (16 attending physicians, 4 emergency residents, 16 advanced practice professionals, and 67 full-time emergency nurses), only 3 (2.9%; exact 95% CI, 0.6%-8.3%) were seropositive for SARS-CoV-2 antibodies. DISCUSSION: At this quaternary academic medical center, among those who volunteered to take an antibody test, there was a low seroprevalence of SARS-CoV-2 antibodies among ED clinicians who were asymptomatic at the time of blood draw and not known to have had prior COVID-19 infection.

Presymptomatic Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 Among Residents and Staff at a Skilled Nursing Facility: Results of Real-time Polymerase Chain Reaction and Serologic Testing.

High rates of asymptomatic coronavirus disease 2019 infection suggest benefits to routine testing in congregate care settings. Screening was undertaken in a single nursing facility without a known case of coronavirus disease 2019, demonstrating an 85% prevalence among residents and 37% among staff. Serology was not helpful in identifying infections.

Clinical sensitivity and interpretation of PCR and serological COVID-19 diagnostics for patients presenting to the hospital.

The diagnosis of COVID-19 requires integration of clinical and laboratory data. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic assays play a central role in diagnosis and have fixed technical performance metrics. Interpretation becomes challenging because the clinical sensitivity changes as the virus clears and the immune response emerges. Our goal was to examine the clinical sensitivity of two most common SARS-CoV-2 diagnostic test modalities, polymerase chain reaction (PCR) and serology, over the disease course to provide insight into their clinical interpretation in patients presenting to the hospital. We conducted a single-center, retrospective study. To derive clinical sensitivity of PCR, we identified 209 PCR-positive SARS-CoV-2 patients with multiple PCR test results (624 total PCR tests) and calculated daily sensitivity from date of symptom onset or first positive test. Clinical sensitivity of PCR decreased with days post symptom onset with >90% clinical sensitivity during the first 5 days after symptom onset, 70%-71% from Days 9 to 11, and 30% at Day 21. To calculate daily clinical sensitivity by serology, we utilized 157 PCR-positive patients with a total of 197 specimens tested by enzyme-linked immunosorbent assay for IgM, IgG, and IgA anti-SARS-CoV-2 antibodies. In contrast to PCR, serological sensitivity increased with days post symptom onset with >50% of patients seropositive by at least one antibody isotype after Day 7, >80% after Day 12, and 100% by Day 21. Taken together, PCR and serology are complimentary modalities that require time-dependent interpretation. Superimposition of sensitivities over time indicate that serology can function as a reliable diagnostic aid indicating recent or prior infection.

Evaluation of Three Commercial SARS-CoV-2 Serologic Assays and Their Performance in Two-Test Algorithms.

Sensitive and specific severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serologic assays are needed to inform diagnostic, therapeutic, and public health decision-making. We evaluated three commercial serologic assays as stand-alone tests and as components of two-test algorithms. Two nucleocapsid antibody tests (Abbott IgG and Roche total antibody) and one spike protein antibody test (DiaSorin IgG) were included. We assessed sensitivity using 128 serum samples from symptomatic PCR-confirmed coronavirus disease 2019 (COVID-19)-infected patients and specificity using 1,204 samples submitted for routine serology prior to COVID-19's emergence, plus 64 pandemic-era samples from SARS-CoV-2 PCR-negative patients with respiratory symptoms. Assays were evaluated as stand-alone tests and as components of a two-test algorithm in which positive results obtained using one assay were verified using a second assay. The two nucleocapsid antibody tests were more sensitive than the spike protein antibody test overall (70% and 70% versus 57%; P ≤ 0.003), with pronounced differences observed using samples collected 7 to 14 days after symptom onset. All three assays were comparably sensitive (≥89%; P ≥ 0.13) using samples collected >14 days after symptom onset. Specificity was higher using the nucleocapsid antibody tests (99.3% and 99.7%) than using the spike protein antibody test (97.8%; P ≤ 0.002). When any two assays were paired in a two-test algorithm, the specificity was 99.9% (P < 0.0001 to 0.25 compared with the individual assays), and the positive predictive value (PPV) improved substantially, with a minimal effect on the negative predictive value (NPV). In conclusion, two nucleocapsid antibody tests outperformed a spike protein antibody test. Pairing two different serologic tests in a two-test algorithm improves the PPV, compared with the individual assays alone, while maintaining the NPV.

Applying Lean methodologies reduces ED laboratory turnaround times.

BACKGROUND: Increasing the value of health care delivery is a national priority, and providers face growing pressure to reduce cost while improving quality. Ample opportunity exists to increase efficiency and quality simultaneously through the application of systems engineering science. OBJECTIVE: We examined the hypothesis that Lean-based reorganization of laboratory process flow would improve laboratory turnaround times (TAT) and reduce waste in the system. METHODS: This study was a prospective, before-after analysis of laboratory process improvement in a teaching hospital emergency department (ED). The intervention included a reorganization of laboratory sample flow based in systems engineering science and Lean methodologies, with no additional resources. The primary outcome was the median TAT from sample collection to result for 6 tests previously performed in an ED kiosk. RESULTS: After the intervention, median laboratory TAT decreased across most tests. The greatest decreases were found in "reflex tests" performed after an initial screening test: troponin T TAT was reduced by 33 minutes (86 to 53 minutes; 99% confidence interval, 30-35 minutes) and urine sedimentation TAT by 88 minutes (117 to 29 minutes; 99% confidence interval, 87-90 minutes). In addition, troponin I TAT was reduced by 12 minutes, urinalysis by 9 minutes, and urine human chorionic gonadotropin by 10 minutes. Microbiology rapid testing TAT, a "control," did not change. CONCLUSIONS: In this study, Lean-based reorganization of laboratory process flow significantly increased process efficiency. Broader application of systems engineering science might further improve health care quality and capacity while reducing waste and cost.

Clinical decision support to improve CBC and differential ordering.

OBJECTIVES: Complete blood count and differential (CBC diff) is a common laboratory test that may be overused or misordered, particularly in an inpatient setting. We assessed the ability of a clinical decision support (CDS) alert to decrease unnecessary orders for CBC diff and analyzed its impact in the laboratory. METHODS: We designed 3 CDS alerts to provide guidance to providers ordering CBC diff on inpatients at frequencies of daily, greater than once daily, or as needed. RESULTS: The 3 alerts were highly effective in reducing orders for CBC diff at the frequencies targeted by the alert. Overall, test volume for CBC diff decreased by 32% (mean of 5257 tests per month) after implementation of the alerts, with a corresponding decrease of 22% in manual differentials performed (mean of 898 per month). Turnaround time for manual differentials decreased by a mean of 41.5 minutes, with a mean decrease of up to 90 minutes during peak morning hours. CONCLUSIONS: The 3 CDS alerts successfully decreased inpatient orders for CBC diff and improved the quality of patient care by decreasing turnaround time for manual differentials.

Using machine learning to develop smart reflex testing protocols.

OBJECTIVE: Reflex testing protocols allow clinical laboratories to perform second line diagnostic tests on existing specimens based on the results of initially ordered tests. Reflex testing can support optimal clinical laboratory test ordering and diagnosis. In current clinical practice, reflex testing typically relies on simple "if-then" rules; however, this limits the opportunities for reflex testing since most test ordering decisions involve more complexity than traditional rule-based approaches would allow. Here, using the analyte ferritin as an example, we propose an alternative machine learning-based approach to "smart" reflex testing. METHODS: Using deidentified patient data, we developed a machine learning model to predict whether a patient getting CBC testing will also have ferritin testing ordered. We evaluate applications of this model to reflex testing by assessing its performance in comparison to possible rule-based approaches. RESULTS: Our underlying machine learning models performed moderately well in predicting ferritin test ordering (AUC=0.731 in reference to actual ordering) and demonstrated promising potential to underlie key clinical applications. In contrast, none of the many traditionally framed, rule-based, hypothetical reflex protocols we evaluated offered sufficient agreement with actual ordering to be clinically feasible. Using chart review, we further demonstrated that the strategic deployment of our model could avoid important ferritin test ordering errors. CONCLUSIONS: Machine learning may provide a foundation for new types of reflex testing with enhanced benefits for clinical diagnosis.

Discrepancy between estimated glomerular filtration rate by creatinine versus cystatin C in different patient care settings.

OBJECTIVE: Estimated glomerular filtration rate (eGFR) calculated by cystatin C (cysC) has been recommended for broader adoption. This study assessed the discrepancy between eGFR calculated by cysC (eGFRcys) and creatinine (eGFRcr) in different patient care settings and explored potential contributing factors to such discrepancies. METHODS: This retrospective study included 2072 patients with paired cysC and creatinine results in different patient care settings. Delta eGFRcr-cys (eGFRcr - eGFRcys) was analyzed in relationship to patient care settings and the Elixhauser Comorbidity index. The 90-day survival in patients with different delta eGFR was assessed by Kaplan-Meier analysis, univariate and multivariate Cox proportional hazard models. In addition, discrepancy between eGFRcys and eGFRcr was analyzed in 50 ambulatory patients with systemic inflammation but normal kidney function. RESULTS: Inpatients had higher cysC (median 1.91 mg/L), lower eGFRcys (median 31 mL/min/1.73 m2), and larger delta eGFRcr-cys (median 18 mL/min/1.73 m2) than outpatients (cysC median 1.53 mg/L, p < 0.0001, eGFRcys median 41 mL/min/1.73 m2, p < 0.0001, delta eGFRcr-cys median 4 mL/min/1.73 m2, p < 0.0001). Higher Elixhauser Comorbidity index correlated with lower eGFRcys and larger delta eGFRcr-cys, with median delta eGFRcr-cys 11 and 6 mL/min/1.73 m2 in patients with a Comorbidity index > 15 and ≤ 15, respectively (p < 0.0001). Increased delta eGFRcr-cys was associated with worse 90-day survival. Patients with systemic inflammation but normal kidney function had lower eGFRcys (median 77.5 mL/min/1.73 m2) than eGFRcr (median 97 mL/min/1.73 m2, p < 0.001), with red blood cell abnormalities as associated factors. CONCLUSION: Inflammation and comorbidities are associated with decreased eGFRcys and large discrepancies between eGFRcr and eGFRcys independent of kidney function and are most apparent in inpatients. Creatinine-cysC combined eGFR reduces this discrepancy and should be broadly adopted.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine response in adults with predominantly antibody deficiency.

Background: Patients with predominantly antibody deficiency (PAD) have lower anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike antibody levels after initial 2-dose SARS-CoV-2 vaccination than healthy controls do; however, the anti-spike antibody responses and neutralization function in patients with PAD following subsequent immunizations remain understudied. Objective: We sought to characterize anti-spike antibody responses in adults with PAD over the course of 5 SARS-CoV-2 vaccine doses and identify diagnostic and immunophenotypic risk factors for low antibody response. Methods: We evaluated anti-spike antibody levels in 117 adult patients with PAD and 192 adult healthy controls following a maximum of 5 SARS-CoV-2 immunizations. We assessed neutralization of the SARS-CoV-2 wild-type strain and the Omicron BA.5 variant and analyzed infection outcomes. Results: The patients with PAD had significantly lower mean anti-spike antibody levels after 3 SARS-CoV-2 vaccine doses than the healthy controls did (1,439.1 vs 21,890.4 U/mL [P < .0001]). Adults with secondary PAD, severe primary PAD, and high-risk immunophenotypes had lower mean anti-spike antibody levels following vaccine doses 2, 3, and/or 4 but not following vaccine dose 5. Compared with patients with mild and moderate PAD, patients with severe PAD had a higher rate of increase in anti-spike antibody levels over 5 immunizations. A strong positive correlation was observed between anti-spike antibody levels and neutralization of both the SARS-CoV-2 wild-type strain and the Omicron BA.5 variant. Most infections were managed on an outpatient basis. Conclusions: In all of the patients with PAD, anti-spike antibody levels increased with successive SARS-CoV-2 immunizations and were correlated with neutralization of both the SARS-CoV-2 wild-type strain and the Omicron BA.5 variant. Secondary PAD, severe primary PAD, and high-risk immunophenotypes were correlated with lower mean anti-spike antibody levels following vaccine doses 2 through 4. Patients with severe PAD had the highest rate of increase in anti-spike antibody levels over 5 immunizations. These data suggest a clinical benefit to sequential SARS-CoV-2 immunizations, particularly among high-risk patients with PAD.

An initiative to improve the management of clinically significant test results in a large health care network.

BACKGROUND: The failure of providers to communicate and follow up clinically significant test results (CSTR) is an important threat to patient safety. The Massachusetts Coalition for the Prevention of Medical Errors has endorsed the creation of systems to ensure that results can be received and acknowledged. METHODS: In 2008 a task force was convened that represented clinicians, laboratories, radiology, patient safety, risk management, and information systems in a large health care network with the goals of providing recommendations and a road map for improvement in the management of CSTR and of implementing this improvement plan during the sub-force sequent five years. In drafting its charter, the task broadened the scope from "critical" results to "clinically significant" ones; clinically significant was defined as any result that requires further clinical action to avoid morbidity or mortality, regardless of the urgency of that action. RESULTS: The task force recommended four key areas for improvement--(1) standardization of policies and definitions, (2) robust identification of the patient's care team, (3) enhanced results management/tracking systems, and (4) centralized quality reporting and metrics. The task force faced many challenges in implementing these recommendations, including disagreements on definitions of CSTR and on who should have responsibility for CSTR, changes to established work flows, limitations of resources and of existing information systems, and definition of metrics. CONCLUSIONS: This large-scale effort to improve the communication and follow-up of CSTR in a health care network continues with ongoing work to address implementation challenges, refine policies, prepare for a new clinical information system platform, and identify new ways to measure the extent of this important safety problem.

Electronic Health Record Optimization for Artificial Intelligence.

Laboratory clinical decision support (CDS) typically relies on data from the electronic health record (EHR). The implementation of a sustainable, effective laboratory CDS program requires a commitment to standardization and harmonization of key EHR data elements that are the foundation of laboratory CDS. The direct use of artificial intelligence algorithms in CDS programs will be limited unless key elements of the EHR are structured. The identification, curation, maintenance, and preprocessing steps necessary to implement robust laboratory-based algorithms must account for the heterogeneity of data present in a typical EHR.

Using Machine Learning to Develop Smart Reflex Testing Protocols.

Objective: Reflex testing protocols allow clinical laboratories to perform second line diagnostic tests on existing specimens based on the results of initially ordered tests. Reflex testing can support optimal clinical laboratory test ordering and diagnosis. In current clinical practice, reflex testing typically relies on simple "if-then" rules; however, this limits their scope since most test ordering decisions involve more complexity than a simple rule will allow. Here, using the analyte ferritin as an example, we propose an alternative machine learning-based approach to "smart" reflex testing with a wider scope and greater impact than traditional rule-based approaches. Methods: Using patient data, we developed a machine learning model to predict whether a patient getting CBC testing will also have ferritin testing ordered, consider applications of this model to "smart" reflex testing, and evaluate the model by comparing its performance to possible rule-based approaches. Results: Our underlying machine learning models performed moderately well in predicting ferritin test ordering and demonstrated greater suitability to reflex testing than rule-based approaches. Using chart review, we demonstrate that our model may improve ferritin test ordering. Finally, as a secondary goal, we demonstrate that ferritin test results are missing not at random (MNAR), a finding with implications for unbiased imputation of missing test results. Conclusions: Machine learning may provide a foundation for new types of reflex testing with enhanced benefits for clinical diagnosis and laboratory utilization management.