Ethnoracial Disparities in SARS-CoV-2 Seroprevalence in a Large Cohort of Individuals in Central North Carolina from April to December 2020.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths around the world within the past 2 years. Transmission within the United States has been heterogeneously distributed by geography and social factors with little data from North Carolina. Here, we describe results from a weekly cross-sectional study of 12,471 unique hospital remnant samples from 19 April to 26 December 2020 collected by four clinical sites within the University of North Carolina Health system, with a majority of samples from urban, outpatient populations in central North Carolina. We employed a Bayesian inference model to calculate SARS-CoV-2 spike protein immunoglobulin prevalence estimates and conditional odds ratios for seropositivity. Furthermore, we analyzed a subset of these seropositive samples for neutralizing antibodies. We observed an increase in seroprevalence from 2.9 (95% confidence interval [CI], 1.8 to 4.5) to 12.8 (95% CI, 10.6 to 15.2) over the course of the study. Latinx individuals had the highest odds ratio of SARS-CoV-2 exposure at 6.56 (95% CI, 4.66 to 9.44). Our findings aid in quantifying the degree of asymmetric SARS-CoV-2 exposure by ethnoracial grouping. We also find that 49% of a subset of seropositive individuals had detectable neutralizing antibodies, which was skewed toward those with recent respiratory infection symptoms. IMPORTANCE PCR-confirmed SARS-CoV-2 cases underestimate true prevalence. Few robust community-level SARS-CoV-2 ethnoracial and overall prevalence estimates have been published for North Carolina in 2020. Mortality has been concentrated among ethnoracial minorities and may result from a high likelihood of SARS-CoV-2 exposure, which we observe was particularly high among Latinx individuals in North Carolina. Additionally, neutralizing antibody titers are a known correlate of protection. Our observation that development of SARS-CoV-2 neutralizing antibodies may be inconsistent and dependent on severity of symptoms makes vaccination a high priority despite prior exposure.

Disparities in SARS-CoV-2 seroprevalence among individuals presenting for care in central North Carolina over a six-month period.

Background: Robust community-level SARS-CoV-2 prevalence estimates have been difficult to obtain in the American South and outside of major metropolitan areas. Furthermore, though some previous studies have investigated the association of demographic factors such as race with SARS-CoV-2 exposure risk, fewer have correlated exposure risk to surrogates for socioeconomic status such as health insurance coverage. Methods: We used a highly specific serological assay utilizing the receptor binding domain of the SARS-CoV-2 spike-protein to identify SARS-CoV-2 antibodies in remnant blood samples collected by the University of North Carolina Health system. We estimated the prevalence of SARS-CoV-2 in this cohort with Bayesian regression, as well as the association of critical demographic factors with higher prevalence odds. Findings: Between April 21st and October 3rd of 2020, a total of 9,624 unique samples were collected from clinical sites in central NC and we observed a seroprevalence increase from 2·9 (1·7, 4·3) to 9·1 (7·2, 11·1) over the study period. Individuals who identified as Latinx were associated with the highest odds ratio of SARS-CoV-2 exposure at 7·77 overall (5·20, 12·10). Increased odds were also observed among Black individuals and individuals without public or private health insurance. Interpretation: Our data suggests that for this care-accessing cohort, SARS-CoV-2 seroprevalence was significantly higher than cumulative total cases reported for the study geographical area six months into the COVID-19 pandemic in North Carolina. The increased odds of seropositivity by ethnoracial grouping as well as health insurance highlights the urgent and ongoing need to address underlying health and social disparities in these populations.

The analytical change in plasma creatinine that constitutes a biologic/physiologic change.

PURPOSE: Accurate and precise measurements of creatinine are necessary to evaluate changes in kidney function related to a decreased glomerular filtration rate (GFR). When serial measurements of creatinine are monitored in an individual, it is useful to know what magnitude of an analytical change in creatinine indicates a true physiologic/biologic change in plasma creatinine that might warrant clinical intervention. METHODS: We compared results between three different methods for creatinine using large chemistry analyzers, two based on alkaline picrate (AP1 and AP2), and one based on dry-slide enzymatic conversion (ENZ). On each of three different segments or days of the study spaced 1-2months apart, we selected 10 different plasma samples having creatinine concentrations ranging from about 0.5mg/dL to 4.5mg/dL (44 to 400µmol/L). Each sample was analyzed in triplicate on each of two same-model analyzers at each institution, then from this data we determined the precision of each model of analyzer. The within-instrument precision of each analyzer was evaluated from the differences between the triplicate results on each sample by each analyzer (mean and SD of the differences). The between-instrument precision was evaluated as the differences between results on the same sample (1, 2, 3, etc.) analyzed on different analyzers of the same model (A and B). This between-analyzer precision data was used to determine both the range and mean±2SD of the differences that could be used to indicate that greater changes in creatinine concentrations would represent a biologic change. RESULTS: The within-instrument precision was best for the ENZ method in comparison to the two alkaline picrate rate methods. The between-instrument precision of the 90 consecutive measurements (30 samples×triplicate analyses) between the same-model analyzers were (mean and SD of differences in mg/dL): -0.018 and 0.029 (ENZ); 0.016 and 0.11 (AP1), and -0.058 and 0.071 (AP2). CONCLUSIONS: While all three of the creatinine methods studied had good precision, the ENZ method had the best precision, such that a change of 0.07mg/dL (6µmol/L) in serial creatinine concentrations up to 1.5mg/dL on a patient could indicate a biologic change had occurred. For the alkaline picrate methods, a measured change of creatinine of 0.23mg/dL for AP1 or 0.11mg/dL for AP2 would indicate that a physiologic change in serum/plasma creatinine has occurred. While a definite biologic change may simply represent daily variations, detecting a biologic change in creatinine more rapidly could impact the ability of creatinine to detect early and clinically significant changes in renal function.

Predicting neonatal respiratory morbidity by lamellar body count and gestational age.

AIMS: To develop a predictive model for assessing the risk of developing neonatal respiratory morbidity using lamellar body counts (LBCs) and gestational age (GA) to provide a more patient-specific assessment. METHODS: Retrospective cohort study of patients' ≥32 weeks' gestation who received amniocentesis with LBC analysis over a 9-year period. Respiratory morbidity was defined as respiratory distress syndrome, transient tachypnea of the newborn or oxygen requirement for >24 h. Logistic regression analyses were used to predict the absolute risk and odds of respiratory morbidity as a function of GA and lamellar body count. RESULTS: Two hundred and sixty-seven mother-infant pairs included in the analysis with 32 cases (12.0%) of respiratory morbidity. When compared to those without respiratory morbidity, neonates with respiratory morbidity had amniocentesis performed at an earlier median GA, had lower mean birthweight and had lower median LBC (P<0.01). The GA specific absolute risks and odds ratios for the presence of respiratory morbidity were calculated. The predicted absolute risks of neonatal respiratory morbidity ranged from 38% at 32 weeks to 6% at 40 weeks when LBC were 35,000/µL. CONCLUSION: GA specific predicted risk of neonatal respiratory morbidity using LBC provides a statistical model, which can aid clinicians in individually counseling patients regarding the absolute risk of their neonate developing respiratory morbidity.