An SGO commentary: U.S. News and World Report gynecologic oncology procedural ratings-Do they reflect high-quality care?

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Real-World Incidence of Breakthrough Coronavirus Disease 2019 Hospitalization After Vaccination vs Natural Infection in a Large, Local, Empaneled Primary Care Population Using Time-to-Event Analysis.

We followed 106 349 primary care patients for 22 385 3099 person-days across 21 calendar months and documented 69 breakthrough coronavirus disease 2019 (COVID-19) hospitalizations: 65/102,613 (0.06%) among those fully vaccinated, 3/11 047 (0.03%) among those previously infected, and 1/7,313 (0.01%) among those with both statuses. These data give providers real-world context regarding breakthrough COVID-19 hospitalization risk.

Impact of the Coronavirus Disease 2019 (COVID-19) Vaccine on Asymptomatic Infection Among Patients Undergoing Preprocedural COVID-19 Molecular Screening.

BACKGROUND: Several vaccines are now available under emergency use authorization in the United States and have demonstrated efficacy against symptomatic COVID-19. Vaccine impact on asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is largely unknown. METHODS: We conducted a retrospective cohort study of consecutive, asymptomatic adult patients (n = 39 156) within a large US healthcare system who underwent 48 333 preprocedural SARS-CoV-2 molecular screening tests between 17 December 2020 and 8 February 2021. The primary exposure of interest was vaccination with ≥1 dose of an mRNA COVID-19 vaccine. The primary outcome was relative risk (RR) of a positive SARS-CoV-2 molecular test among those asymptomatic persons who had received ≥1 dose of vaccine compared with persons who had not received vaccine during the same time period. RR was adjusted for age, sex, race/ethnicity, patient residence relative to the hospital (local vs nonlocal), healthcare system regions, and repeated screenings among patients using mixed-effects log-binomial regression. RESULTS: Positive molecular tests in asymptomatic individuals were reported in 42 (1.4%) of 3006 tests and 1436 (3.2%) of 45 327 tests performed on vaccinated and unvaccinated patients, respectively (RR, .44; 95% CI, .33-.60; P < .0001). Compared with unvaccinated patients, risk of asymptomatic SARS-CoV-2 infection was lower among those >10 days after the first dose (RR, .21; 95% CI, .12-.37; P < .0001) and >0 days after the second dose (RR, .20; 95% CI, .09-.44; P < .0001) in the adjusted analysis. CONCLUSIONS: COVID-19 vaccination with an mRNA-based vaccine showed a significant association with reduced risk of asymptomatic SARS-CoV-2 infection as measured during preprocedural molecular screening. Results of this study demonstrate the impact of the vaccines on reduction in asymptomatic infections supplementing the randomized trial results on symptomatic patients.

Coronavirus Disease 2019 Vaccine-Breakthrough Infections Requiring Hospitalization in Mayo Clinic Florida Through August 2021.

We characterized coronavirus disease 2019 (COVID-19) breakthrough cases admitted to a single center in Florida. With the emergence of delta variant, an increased number of hospitalizations was seen due to breakthrough infections. These patients were older and more likely to have comorbidities. Preventive measures should be maintained even after vaccination.

Low antispike antibody levels correlate with poor outcomes in COVID-19 breakthrough hospitalizations.

BACKGROUND: While COVID-19 immunization programs attempted to reach targeted rates, cases rose significantly since the emergence of the delta variant. This retrospective cohort study describes the correlation between antispike antibodies and outcomes of hospitalized, breakthrough cases during the delta variant surge. METHODS: All patients with positive SARS-CoV-2 polymerase chain reaction hospitalized at Mayo Clinic Florida from 19 June 2021 to 11 November 2021 were considered for analysis. Cases were analyzed by vaccination status. Breakthrough cases were then analyzed by low and high antibody titers against SARS-CoV-2 spike protein, with a cut-off value of ≥132 U/ml. Outcomes included hospital length of stay (LOS), need for intensive care unit (ICU), mechanical ventilation, and mortality. We used 1:1 nearest neighbor propensity score matching without replacement to assess for confounders. RESULTS: Among 627 hospitalized patients with COVID-19, vaccine breakthrough cases were older with more comorbidities compared to unvaccinated. After propensity score matching, the unvaccinated patients had higher mortality (27 [28.4%] vs. 12 [12.6%], p = 0.002) and LOS (7 [1.0-57.0] vs. 5 [1.0-31.0] days, p = 0.011). In breakthrough cases, low-titer patients were more likely to be solid organ transplant recipients (16 [34.0%] vs. 9 [12.3%], p = 0.006), with higher need for ICU care (24 [51.1%] vs. 22 [11.0%], p = 0.034), longer hospital LOS (median 6 vs. 5 days, p = 0.013), and higher mortality (10 [21.3%] vs. 5 [6.8%], p = 0.025) than high-titer patients. CONCLUSIONS: Hospitalized breakthrough cases were more likely to have underlying risk factors than unvaccinated patients. Low-spike antibody titers may serve as an indicator for poor prognosis in breakthrough cases admitted to the hospital.

Do diets with higher carbon footprints increase the risk of mortality? A population-based simulation study using self-selected diets from the USA.

OBJECTIVE: Are diets with a greater environmental impact less healthy? This is a key question for nutrition policy, but previous research does not provide a clear answer. To address this, our objective here was to test whether American diets with the highest carbon footprints predicted greater population-level mortality from diet-related chronic disease than those with the lowest. DESIGN: Baseline dietary recall data were combined with a database of greenhouse gases emitted in the production of foods to estimate a carbon footprint for each diet. Diets were ranked on their carbon footprints and those in the highest and lowest quintiles were studied here. Preventable Risk Integrated Model (PRIME), an epidemiological modelling software, was used to assess CVD and cancer mortality for a simulated dietary change from the highest to the lowest impact diets. The diet-mortality relationships used by PRIME came from published meta-analyses of randomised controlled trials and prospective cohort studies. SETTING: USA. PARTICIPANTS: Baseline diets came from adults (n 12 865) in the nationally representative 2005-2010 National Health and Nutrition Examination Survey. RESULTS: A simulated change at the population level from the highest to the lowest carbon footprint diets resulted in 23 739 (95 % CI 20 349, 27 065) fewer annual deaths from CVD and cancer. This represents a 1·83 % (95 % CI 1·57 %, 2·08 %) decrease in total deaths. About 95 % of deaths averted were from CVD. CONCLUSIONS: Diets with the highest carbon footprints were associated with a greater risk of mortality than the lowest, suggesting that dietary guidance could incorporate sustainability information to reinforce health messaging.

Associations between Hunter Type A/B Personality and Cardiovascular Risk Factors from Adolescence through Young Adulthood.

PURPOSE: Type A personality, characterized by action-oriented tendencies, has been linked to cardiovascular disease in middle-aged and elderly adults. Alternatively, limited research has tested whether personality type A/B and cardiovascular (CVD) risk are linked prior to adulthood. Therefore, we used the Hunter-Wolf A/B personality score to determine whether personality type A/B is associated with traditional CVD risk factors during adolescence, and more importantly if personality type, or its individual type A components, are associated with cardiovascular risk through young adulthood. This study is the first to assess personality type A/B on a continuous spectrum with regard to its relationship with cardiovascular disease risk, as well as the first to examine this association in a biracial, adolescent population. METHODS: Subjects (3396) from the Bogalusa Heart Study were surveyed from 1984 to 1986, and multivariable regression was used to test adjusted, cross-sectional associations between personality type A/B, as determined by Hunter-Wolf A/B personality questionnaire, and CVD risk factors during adolescence. To test whether associations existed longitudinally, subjects were followed through 2007, and general estimating equation (GEE) models were used to examine the associations of personality type A/B with CVD risk factors, as well as with Framingham risk score as a global score of CVD risk. The component traits of type A personality (leadership, hard-driving, eagerness-energy, and impatience-aggression) were tested individually to determine their independent, longitudinal associations with global CVD risk. RESULTS: Baseline mean (SD) age was 15.9(5.2). Mean( SD) Hunter-Wolf score in was 96.9 (11.6). After adjustment, more type A Hunter-Wolf scores were cross-sectionally associated with lower alcohol consumption (p = 0.03), female gender (p < 0.0001), and black race (p < 0.0001) in adolescence. After follow-up (median = 11 years), personality type A/B as the continuous Hunter-Wolf score was non-linearly associated with young adult BMI (p = 0.01), fasting blood glucose (p < 0.01), and Framingham score (p = 0.05). Of the type A components, leadership and hard-driving were non-linearly associated with Framingham risk at follow-up (both p < 0.0001). CONCLUSIONS: Adolescent personality type A is associated with female gender and black race. Generally, type A children have higher CVD risk during young adulthood, though this relationship is non-linear. Additionally, adolescents exhibiting strong leadership-oriented personality traits have worse cardiovascular risk profiles in early adulthood, whereas hard-driving adolescent personalities are protective of young adult CVD risk. Our results warrant consideration of personality as a continuous, non-categorical, trait in studies of cardiovascular disease.

Missed opportunities in hospital quality measurement during the COVID-19 pandemic: a retrospective investigation of US hospitals' CMS Star Ratings and 30-day mortality during the early pandemic.

OBJECTIVES: In the USA and UK, pandemic-era outcome data have been excluded from hospital rankings and pay-for-performance programmes. We assessed the relationship between US hospitals' pre-pandemic Centers for Medicare and Medicaid Services (CMS) Overall Hospital Star ratings and early pandemic 30-day mortality among both patients with COVID and non-COVID to understand whether pre-existing structures, processes and outcomes related to quality enabled greater pandemic resiliency. DESIGN AND DATA SOURCE: A retrospective, claim-based data study using the 100% Inpatient Standard Analytic File and Medicare Beneficiary Summary File including all US Medicare Fee-for-Service inpatient encounters from 1 April 2020 to 30 November 2020 linked with the CMS Hospital Star Ratings using six-digit CMS provider IDs. OUTCOME MEASURE: The outcome was risk-adjusted 30-day mortality. We used multivariate logistic regression adjusting for age, sex, Elixhauser mortality index, US Census Region, month, hospital-specific January 2020 CMS Star rating (1-5 stars), COVID diagnosis (U07.1) and COVID diagnosis×CMS Star Rating interaction. RESULTS: We included 4 473 390 Medicare encounters from 2533 hospitals, with 92 896 (28.2%) mortalities among COVID-19 encounters and 387 029 (9.3%) mortalities among non-COVID encounters. There was significantly greater odds of mortality as CMS Star Ratings decreased, with 18% (95% CI 15% to 22%; p<0.0001), 33% (95% CI 30% to 37%; p<0.0001), 38% (95% CI 34% to 42%; p<0.0001) and 60% (95% CI 55% to 66%; p<0.0001), greater odds of COVID mortality comparing 4-star, 3-star, 2-star and 1-star hospitals (respectively) to 5-star hospitals. Among non-COVID encounters, there were 17% (95% CI 16% to 19%; p<0.0001), 24% (95% CI 23% to 26%; p<0.0001), 32% (95% CI 30% to 33%; p<0.0001) and 40% (95% CI 38% to 42%; p<0.0001) greater odds of mortality at 4-star, 3-star, 2-star and 1-star hospitals (respectively) as compared with 5-star hospitals. CONCLUSION: Our results support a need to further understand how quality outcomes were maintained during the pandemic. Valuable insights can be gained by including the reporting of risk-adjusted pandemic era hospital quality outcomes for high and low performing hospitals.

A Simple Risk Adjustment for Hospital-Level Nulliparous, Term, Singleton, Vertex, Cesarean Delivery Rates and Its Implications for Public Reporting.

BACKGROUND: The Joint Commission uses nulliparous, term, singleton, vertex, cesarean delivery (NTSV-CD) rates to assess hospitals' perinatal care quality through the Cesarean Birth measurement (PC-02). However, these rates are not risk-adjusted for maternal health factors, putting this measure at odds with the risk adjustment paradigm of most publicly reported hospital quality measures. Here, the authors tested whether risk adjustment for readily documented maternal risk factors affected hospital-level NTSV-CD rates in a large health system. METHODS: Included were all consecutive NTSV pregnancies from January 2019 to April 2023 across 10 hospitals in one health system. Logistic regression, adjusting for age, obesity, diabetes, and hypertensive disorders. was used to calculate hospital-level risk-adjusted NTSV-CD rates by multiplying observed vs. expected ratios for each hospital by the systemwide unadjusted NTSV-CD rate. The authors calculated intrahospital risk differences between unadjusted and risk-adjusted rates and calculated the percentage of hospitals qualifying for different reporting status after risk adjustment using the 30% Joint Commission reporting threshold rate. RESULTS: Of 23,866 pregnancies, 6,550 (27.4%) had cesarean deliveries. Across 10 hospitals, the number of deliveries ranged from 393 to 7,671, with unadjusted NTSV-CD rates ranging from 21.0% to 30.5%. Risk-adjusted NTSV-CD rates ranged from 21.5% to 30.4%, with absolute intrahospital differences in risk-adjusted vs. unadjusted rates ranging from -1.33% (indicating lower rate after risk adjustment) to 3.37% (indicating higher rate after risk adjustment). Three of 10 (30.0%) hospitals qualified for different reporting statuses after risk adjustment. CONCLUSION: Risk adjustment for age, obesity, diabetes, and hypertensive disorders is feasible and resulted in meaningful changes in hospital-level NTSV-CD rates with potentially impactful consequences for hospitals near The Joint Commission reporting threshold.

Exploring COVID-19 census burdens by US hospital characteristics: Implications of quality reporting at rural and critical access hospitals.

PURPOSE: By assessing longitudinal associations between COVID-19 census burdens and hospital characteristics, such as bed size and critical access status, we can explore whether pandemic-era hospital quality benchmarking requires risk-adjustment or stratification for hospital-level characteristics. METHODS: We used hospital-level data from the US Department of Health and Human Services including weekly total hospital and COVID-19 censuses from August 2020 to August 2023 and the 2021 American Hospital Association survey. We calculated weekly percentages of total adult hospital beds containing COVID-19 patients. We then calculated the number of weeks each hospital spent at Extreme (≥20% of beds occupied by COVID-19 patients), High (10%-19%), Moderate (5%-9%), and Low (<5%) COVID-19 stress. We assessed longitudinal hospital-level COVID-19 stress, stratified by 15 hospital characteristics including joint commission accreditation, bed size, teaching status, critical access hospital status, and core-based statistical area (CBSA) rurality. FINDINGS: Among n = 2582 US hospitals, the median(IQR) weekly percentage of hospital capacity occupied by COVID-19 patients was 6.7%(3.6%-13.0%). 80,268/213,383 (38%) hospital-weeks experienced Low COVID-19 census stress, 28% Moderate stress, 22% High stress, and 12% Extreme stress. COVID-19 census burdens were similar across most hospital characteristics, but were significantly greater for critical access hospitals. CONCLUSIONS: US hospitals experienced similar COVID-19 census burdens across multiple institutional characteristics. Evidence-based inclusion of pandemic-era outcomes in hospital quality reporting may not require significant hospital-level risk-adjustment or stratification, with the exception of rural or critical access hospitals, which experienced differentially greater COVID-19 census burdens and may merit hospital-level risk-adjustment considerations.

Risk of Transfusion in Isolated Coronary Artery Bypass Graft: Models developed from the STS Database.

BACKGROUND: Perioperative blood transfusion is associated with adverse outcomes and higher costs following coronary artery bypass graft surgery (CABG). We developed risk assessments for patients' probability of perioperative transfusion and the expected transfusion volume, to improve clinical management and resource use. METHODS: Among 1,266,545 consecutive (2008-2016) isolated-CABG operations in STS's Adult Cardiac Surgery Database, 657,821 (51.9%) received perioperative blood transfusions (red blood cell [RBC], fresh frozen plasma [FFP], cryoprecipitate, and/or platelets). We developed "full" models to predict perioperative transfusion of any blood product, and of RBC, FFP, or platelets. Using least absolute shrinkage and selection operator model selection, we built a rapid risk score based on 5 variables (age, body surface area, sex, preoperative hematocrit and use of intra-aortic balloon pump). RESULTS: Full model C-statistics were 0.785, 0.815, 0.707, and 0.699 for any blood product, RBC, FFP, and platelets. Rapid risk assessments' C-statistics were 0.752, 0.785, 0.670, and 0.661 for any blood product, RBC, FFP, and platelets. The observed versus expected risk plots showed strong calibration for full models and risk assessment tools; absolute differences between observed and expected risks of transfusion were <10.8% in each percentile of expected risk. Risk-assessments' predicted probabilities of transfusion were strongly and non-linearly associated (p<.0001) with total units transfused. CONCLUSIONS: These robust and well-calibrated risk assessment tools for perioperative transfusion in CABG can inform surgeons regarding patients' risks and number of RBC, FFP, and platelets units they can expect to need. This can aid in optimizing outcomes and increasing efficient use of blood products.

Hospital quality reporting in the pandemic era: to what extent did hospitals' COVID-19 census burdens impact 30-day mortality among non-COVID Medicare beneficiaries?

OBJECTIVES: Highly visible hospital quality reporting stakeholders in the USA such as the US News & World Report (USNWR) and the Centers for Medicare & Medicaid Services (CMS) play an important health systems role via their transparent public reporting of hospital outcomes and performance. However, during the pandemic, many such quality measurement stakeholders and pay-for-performance programmes in the USA and Europe have eschewed the traditional risk adjustment paradigm, instead choosing to pre-emptively exclude months or years of pandemic era performance data due largely to hospitals' perceived COVID-19 burdens. These data exclusions may lead patients to draw misleading conclusions about where to seek care, while also masking genuine improvements or deteriorations in hospital quality that may have occurred during the pandemic. Here, we assessed to what extent hospitals' COVID-19 burdens (proportion of hospitalised patients with COVID-19) were associated with their non-COVID 30-day mortality rates from March through November 2020 to inform whether inclusion of pandemic-era data may still be appropriate. DESIGN: This was a retrospective cohort study using the 100% CMS Inpatient Standard Analytic File and Master Beneficiary Summary File to include all US Medicare inpatient encounters with admission dates from 1 April 2020 through 30 November 2020, excluding COVID-19 encounters. Using linear regression, we modelled the association between hospitals' COVID-19 proportions and observed/expected (O/E) ratios, testing whether the relationship was non-linear. We calculated alternative hospital O/E ratios after selective pandemic data exclusions mirroring the USNWR data exclusion methodology. SETTING AND PARTICIPANTS: We analysed 4 182 226 consecutive Medicare inpatient encounters from across 2601 US hospitals. RESULTS: The association between hospital COVID-19 proportion and non-COVID O/E 30-day mortality was statistically significant (p<0.0001), but weakly correlated (r2=0.06). The median (IQR) pairwise relative difference in hospital O/E ratios comparing the alternative analysis with the original analysis was +3.7% (-2.5%, +6.7%), with 1908/2571 (74.2%) of hospitals having relative differences within ±10%. CONCLUSIONS: For non-COVID patient outcomes such as mortality, evidence-based inclusion of pandemic-era data is methodologically plausible and must be explored rather than exclusion of months or years of relevant patient outcomes data.

A Simple and Interpretable Mortality-Based Value Metric for Condition- or Procedure-Specific Hospital Performance Reporting.

Objective: To develop a simple, interpretable value metric (VM) to assess the value of care of hospitals for specific procedures or conditions by operationalizing the value equation: Value = Quality/Cost. Patients and Methods: The present study was conducted on a retrospective cohort from 2015 to 2018 drawn from the 100% US sample of Medicare inpatient claims. The final cohort comprised 637,341 consecutive inpatient encounters with a cancer-related Medicare Severity-Diagnosis Related Grouping and 13,307 consecutive inpatient encounters with the International Classification of Diseases, Ninth Revision or International Classification of Diseases, Tenth Revision procedure code for partial or total gastrectomy. Claims-based demographic and clinical variables were used for risk adjustment, including age, sex, year, dual eligibility, reason for Medicare entitlement, and binary indicators for each of the Elixhauser comorbidities used in the Elixhauser mortality index. Risk-adjusted 30-day mortality and risk-adjusted encounter-specific costs were combined to form the VM, which was calculated as follows: number needed to treat = 1/(Mortalitynational - Mortalityhospital), and VM = number needed to treat × risk-adjusted cost per encounter. Results: Among hospitals with better-than-average 30-day cancer mortality rates, the cost to prevent 1 excess 30-day mortality for an inpatient cancer encounter ranged from $71,000 (best value) to $1.4 billion (worst value), with a median value of $543,000. Among hospitals with better-than-average 30-day gastrectomy mortality rates, the cost to prevent 1 excess 30-day mortality for an inpatient gastrectomy encounter ranged from $710,000 (best value) to $95 million (worst value), with a median value of $1.8 million. Conclusion: This simple VM may have utility for interpretable reporting of hospitals' value of care for specific conditions or procedures. We found substantial inter- and intrahospital variation in value when defined as the costs of preventing 1 excess cancer or gastrectomy mortality compared with the national average, implying that hospitals with similar quality of care may differ widely in the value of that care.

A Multisite Assessment of Inpatient Safety Event Rates During the Coronavirus Disease 2019 Pandemic.

To date, there has been a notable lack of peer-reviewed or publicly available data documenting rates of hospital quality outcomes and patient safety events during the coronavirus disease 2019 pandemic era. The dearth of evidence is perhaps related to the US health care system triaging resources toward patient care and away from reporting and research and also reflects that data used in publicly reported hospital quality rankings and ratings typically lag 2-5 years. At our institution, a learning health system assessment is underway to evaluate how patient safety was affected by the pandemic. Here we share and discuss early findings, noting the limitations of self-reported safety event reporting, and suggest the need for further widespread investigations at other US hospitals. During the 2-year study period from January 1, 2020, through December 31, 2021 across 3 large US academic medical centers at our institution, we documented an overall rate of 25.8 safety events per 1000 inpatient days. The rate of events meeting "harm" criteria was 12.4 per 1000 inpatient days, the rate of nonharm events was 11.1 per 1000 inpatient days, and the fall rate was 2.3 per 1000 inpatient days. This descriptive exploratory analysis suggests that patient safety event rates at our institution did not increase over the course of the pandemic. However, increasing health care worker absences were nonlinearly and strongly associated with patient safety event rates, which raises questions regarding the mechanisms by which patient safety event rates may be affected by staff absences during pandemic peaks.

Real-world performance of SARS-Cov-2 serology tests in the United States, 2020.

BACKGROUND: Real-world performance of COVID-19 diagnostic tests under Emergency Use Authorization (EUA) must be assessed. We describe overall trends in the performance of serology tests in the context of real-world implementation. METHODS: Six health systems estimated the odds of seropositivity and positive percent agreement (PPA) of serology test among people with confirmed SARS-CoV-2 infection by molecular test. In each dataset, we present the odds ratio and PPA, overall and by key clinical, demographic, and practice parameters. RESULTS: A total of 15,615 people were observed to have at least one serology test 14-90 days after a positive molecular test for SARS-CoV-2. We observed higher PPA in Hispanic (PPA range: 79-96%) compared to non-Hispanic (60-89%) patients; in those presenting with at least one COVID-19 related symptom (69-93%) as compared to no such symptoms (63-91%); and in inpatient (70-97%) and emergency department (93-99%) compared to outpatient (63-92%) settings across datasets. PPA was highest in those with diabetes (75-94%) and kidney disease (83-95%); and lowest in those with auto-immune conditions or who are immunocompromised (56-93%). The odds ratios (OR) for seropositivity were higher in Hispanics compared to non-Hispanics (OR range: 2.59-3.86), patients with diabetes (1.49-1.56), and obesity (1.63-2.23); and lower in those with immunocompromised or autoimmune conditions (0.25-0.70), as compared to those without those comorbidities. In a subset of three datasets with robust information on serology test name, seven tests were used, two of which were used in multiple settings and met the EUA requirement of PPA ≥87%. Tests performed similarly across datasets. CONCLUSION: Although the EUA requirement was not consistently met, more investigation is needed to understand how serology and molecular tests are used, including indication and protocol fidelity. Improved data interoperability of test and clinical/demographic data are needed to enable rapid assessment of the real-world performance of in vitro diagnostic tests.

Real-world utilization of SARS-CoV-2 serological testing in RNA positive patients across the United States.

BACKGROUND: As diagnostic tests for COVID-19 were broadly deployed under Emergency Use Authorization, there emerged a need to understand the real-world utilization and performance of serological testing across the United States. METHODS: Six health systems contributed electronic health records and/or claims data, jointly developed a master protocol, and used it to execute the analysis in parallel. We used descriptive statistics to examine demographic, clinical, and geographic characteristics of serology testing among patients with RNA positive for SARS-CoV-2. RESULTS: Across datasets, we observed 930,669 individuals with positive RNA for SARS-CoV-2. Of these, 35,806 (4%) were serotested within 90 days; 15% of which occurred <14 days from the RNA positive test. The proportion of people with a history of cardiovascular disease, obesity, chronic lung, or kidney disease; or presenting with shortness of breath or pneumonia appeared higher among those serotested compared to those who were not. Even in a population of people with active infection, race/ethnicity data were largely missing (>30%) in some datasets-limiting our ability to examine differences in serological testing by race. In datasets where race/ethnicity information was available, we observed a greater distribution of White individuals among those serotested; however, the time between RNA and serology tests appeared shorter in Black compared to White individuals. Test manufacturer data was available in half of the datasets contributing to the analysis. CONCLUSION: Our results inform the underlying context of serotesting during the first year of the COVID-19 pandemic and differences observed between claims and EHR data sources-a critical first step to understanding the real-world accuracy of serological tests. Incomplete reporting of race/ethnicity data and a limited ability to link test manufacturer data, lab results, and clinical data challenge the ability to assess the real-world performance of SARS-CoV-2 tests in different contexts and the overall U.S. response to current and future disease pandemics.

Association of Neutralizing Antispike Monoclonal Antibody Treatment With Coronavirus Disease 2019 Hospitalization and Assessment of the Monoclonal Antibody Screening Score.

Objective: To test the hypothesis that the Monoclonal Antibody Screening Score performs consistently better in identifying the need for monoclonal antibody infusion throughout each "wave" of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant predominance during the coronavirus disease 2019 (COVID-19) pandemic and that the infusion of contemporary monoclonal antibody treatments is associated with a lower risk of hospitalization. Patients and Methods: In this retrospective cohort study, we evaluated the efficacy of monoclonal antibody treatment compared with that of no monoclonal antibody treatment in symptomatic adults who tested positive for SARS-CoV-2 regardless of their risk factors for disease progression or vaccination status during different periods of SARS-CoV-2 variant predominance. The primary outcome was hospitalization within 28 days after COVID-19 diagnosis. The study was conducted on patients with a diagnosis of COVID-19 from November 19, 2020, through May 12, 2022. Results: Of the included 118,936 eligible patients, hospitalization within 28 days of COVID-19 diagnosis occurred in 2.52% (456/18,090) of patients who received monoclonal antibody treatment and 6.98% (7,037/100,846) of patients who did not. Treatment with monoclonal antibody therapies was associated with a lower risk of hospitalization when using stratified data analytics, propensity scoring, and regression and machine learning models with and without adjustments for putative confounding variables, such as advanced age and coexisting medical conditions (eg, relative risk, 0.15; 95% CI, 0.14-0.17). Conclusion: Among patients with mild to moderate COVID-19, including those who have been vaccinated, monoclonal antibody treatment was associated with a lower risk of hospital admission during each wave of the COVID-19 pandemic.