Labor Market Returns to MBAs From Less‐Selective Universities: Evidence From a Field Experiment During COVID‐19

Master's degree enrollment and debt have increased substantially in recent years, raising important questions about the labor market value of these credentials. Using a field experiment featuring 9,480 job applications submitted during the early months of the COVID‐19 pandemic, I examine employers' responses to job candidates with a Master of Business Administration (MBA), which represents one‐quarter of all master's degrees in the United States. I focus on MBAs from three types of less‐selective institutions that collectively enroll the vast majority of master's students: for‐profit, online, and regional universities. Despite the substantial time and expense required for these degrees, job candidates with MBAs from all three types of institutions received positive responses from employers at the same rate as candidates who only had a bachelor's degree—even for positions that listed a preference for a master's degree. Additionally, applicants with names suggesting they were Black men received 30 percent fewer positive responses than otherwise equivalent applicants whose names suggested they were White men or women, providing further evidence of racial discrimination in hiring practices.

Labor market returns to MBAs from less‐selective universities: Evidence from a field experiment during COVID‐19

Master's degree enrollment and debt have increased substantially in recent years, raising important questions about the labor market value of these credentials. Using a field experiment featuring 9,480 job applications submitted during the early months of the COVID-19 pandemic, I examine employers' responses to job candidates with a Master of Business Administration (MBA), which represents one-quarter of all master's degrees in the United States. I focus on MBAs from three types of less-selective institutions that collectively enroll the vast majority of master's students: for-profit, online, and regional universities. Despite the substantial time and expense required for these degrees, job candidates with MBAs from all three types of institutions received positive responses from employers at the same rate as candidates who only had a bachelor's degree-even for positions that listed a preference for a master's degree. Additionally, applicants with names suggesting they were Black men received 30 percent fewer positive responses than otherwise equivalent applicants whose names suggested they were White men or women, providing further evidence of racial discrimination in hiring practices.

External validation of the 4C Mortality Score for hospitalised patients with COVID-19 in the RECOVER network.

OBJECTIVES: Estimating mortality risk in hospitalised SARS-CoV-2+ patients may help with choosing level of care and discussions with patients. The Coronavirus Clinical Characterisation Consortium Mortality Score (4C Score) is a promising COVID-19 mortality risk model. We examined the association of risk factors with 30-day mortality in hospitalised, full-code SARS-CoV-2+ patients and investigated the discrimination and calibration of the 4C Score. This was a retrospective cohort study of SARS-CoV-2+ hospitalised patients within the RECOVER (REgistry of suspected COVID-19 in EmeRgency care) network. SETTING: 99 emergency departments (EDs) across the USA. PARTICIPANTS: Patients ≥18 years old, positive for SARS-CoV-2 in the ED, and hospitalised. PRIMARY OUTCOME: Death within 30 days of the index visit. We performed logistic regression analysis, reporting multivariable risk ratios (MVRRs) and calculated the area under the ROC curve (AUROC) and mean prediction error for the original 4C Score and after dropping the C reactive protein (CRP) component. RESULTS: Of 6802 hospitalised patients with COVID-19, 1149 (16.9%) died within 30 days. The 30-day mortality was increased with age 80+ years (MVRR=5.79, 95% CI 4.23 to 7.34); male sex (MVRR=1.17, 1.05 to 1.28); and nursing home/assisted living facility residence (MVRR=1.29, 1.1 to 1.48). The 4C Score had comparable discrimination in the RECOVER dataset compared with the original 4C validation dataset (AUROC: RECOVER 0.786 (95% CI 0.773 to 0.799), 4C validation 0.763 (95% CI 0.757 to 0.769). Score-specific mortalities in our sample were lower than in the 4C validation sample (mean prediction error 6.0%). Dropping the CRP component from the 4C Score did not substantially affect discrimination and 4C risk estimates were now close (mean prediction error 0.7%). CONCLUSIONS: We independently validated 4C Score as predicting risk of 30-day mortality in hospitalised SARS-CoV-2+ patients. We recommend dropping the CRP component of the score and using our recalibrated mortality risk estimates.

Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments 2-22-2021.

OBJECTIVES: Accurate and reliable criteria to rapidly estimate the probability of infection with the novel coronavirus-2 that causes the severe acute respiratory syndrome (SARS-CoV-2) and associated disease (COVID-19) remain an urgent unmet need, especially in emergency care. The objective was to derive and validate a clinical prediction score for SARS-CoV-2 infection that uses simple criteria widely available at the point of care. METHODS: Data came from the registry data from the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER network) comprising 116 hospitals from 25 states in the US. Clinical variables and 30-day outcomes were abstracted from medical records of 19,850 emergency department (ED) patients tested for SARS-CoV-2. The criterion standard for diagnosis of SARS-CoV-2 required a positive molecular test from a swabbed sample or positive antibody testing within 30 days. The prediction score was derived from a 50% random sample (n = 9,925) using unadjusted analysis of 107 candidate variables as a screening step, followed by stepwise forward logistic regression on 72 variables. RESULTS: Multivariable regression yielded a 13-variable score, which was simplified to a 13-point score: +1 point each for age>50 years, measured temperature>37.5°C, oxygen saturation<95%, Black race, Hispanic or Latino ethnicity, household contact with known or suspected COVID-19, patient reported history of dry cough, anosmia/dysgeusia, myalgias or fever; and -1 point each for White race, no direct contact with infected person, or smoking. In the validation sample (n = 9,975), the probability from logistic regression score produced an area under the receiver operating characteristic curve of 0.80 (95% CI: 0.79-0.81), and this level of accuracy was retained across patients enrolled from the early spring to summer of 2020. In the simplified score, a score of zero produced a sensitivity of 95.6% (94.8-96.3%), specificity of 20.0% (19.0-21.0%), negative likelihood ratio of 0.22 (0.19-0.26). Increasing points on the simplified score predicted higher probability of infection (e.g., >75% probability with +5 or more points). CONCLUSION: Criteria that are available at the point of care can accurately predict the probability of SARS-CoV-2 infection. These criteria could assist with decisions about isolation and testing at high throughput checkpoints.

Multicenter Study of Outcomes Among Persons With HIV Who Presented to US Emergency Departments With Suspected SARS-CoV-2.

BACKGROUND: There is a need to characterize patients with HIV with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SETTING: Multicenter registry of patients from 116 emergency departments in 27 US states. METHODS: Planned secondary analysis of patients with suspected SARS-CoV-2, with (n = 415) and without (n = 25,306) HIV. Descriptive statistics were used to compare patient information and clinical characteristics by SARS-CoV-2 and HIV status. Unadjusted and multivariable models were used to explore factors associated with death, intubation, and hospital length of stay. Kaplan-Meier curves were used to estimate survival by SARS-CoV-2 and HIV infection status. RESULTS: Patients with both SARS-CoV-2 and HIV and patients with SARS-CoV-2 but without HIV had similar admission rates (62.7% versus 58.6%, P = 0.24), hospitalization characteristics [eg, rates of admission to the intensive care unit from the emergency department (5.0% versus 6.3%, P = 0.45) and intubation (10% versus 13.3%, P = 0.17)], and rates of death (13.9% versus 15.1%, P = 0.65). They also had a similar cumulative risk of death (log-rank P = 0.72). However, patients with both HIV and SARS-CoV-2 infections compared with patients with HIV but without SAR-CoV-2 had worsened outcomes, including increased mortality (13.9% versus 5.1%, P < 0.01, log-rank P < 0.0001) and their deaths occurred sooner (median 11.5 versus 34 days, P < 0.01). CONCLUSIONS: Among emergency department patients with HIV, clinical outcomes associated with SARS-CoV-2 infection are not worse when compared with patients without HIV, but SARS-CoV-2 infection increased the risk of death in patients with HIV.

Evaluation of Three Commercial and Two Non-Commercial Immunoassays for the Detection of Prior Infection to SARS-CoV-2.

BACKGROUND: Serological testing provides a record of prior infection with SARS-CoV-2, but assay performance requires independent assessment. METHODS: We evaluated 3 commercial (Roche Diagnostics pan-IG, and Epitope Diagnostics IgM and IgG) and 2 non-commercial (Simoa and Ragon/MGH IgG) immunoassays against 1083 unique samples that included 251 PCR-positive and 832 prepandemic samples. RESULTS: The Roche assay registered the highest specificity 99.6% (3/832 false positives), the Ragon/MGH assay 99.5% (4/832), the primary Simoa assay model 99.0% (8/832), and the Epitope IgG and IgM 99.0% (8/830) and 99.5% (4/830), respectively. Overall sensitivities for the Simoa, Roche pan-IG, Epitope IgG, Ragon/MGH IgG, and Epitope IgM were 92.0%, 82.9%, 82.5%, 64.5% and 47.0%, respectively. The Simoa immunoassay demonstrated the highest sensitivity among samples stratified by days postsymptom onset (PSO), <8 days PSO (57.69%) 8-14 days PSO (93.51%), 15-21 days PSO (100%), and > 21 days PSO (95.18%). CONCLUSIONS: All assays demonstrated high to very high specificities while sensitivities were variable across assays.