Sentinel Surveillance System Implementation and Evaluation for SARS-CoV-2 Genomic Data, Washington, USA, 2020-2021.

Genomic data provides useful information for public health practice, particularly when combined with epidemiologic data. However, sampling bias is a concern because inferences from nonrandom data can be misleading. In March 2021, the Washington State Department of Health, USA, partnered with submitting and sequencing laboratories to establish sentinel surveillance for SARS-CoV-2 genomic data. We analyzed available genomic and epidemiologic data during presentinel and sentinel periods to assess representativeness and timeliness of availability. Genomic data during the presentinel period was largely unrepresentative of all COVID-19 cases. Data available during the sentinel period improved representativeness for age, death from COVID-19, outbreak association, long-term care facility-affiliated status, and geographic coverage; timeliness of data availability and captured viral diversity also improved. Hospitalized cases were underrepresented, indicating a need to increase inpatient sampling. Our analysis emphasizes the need to understand and quantify sampling bias in phylogenetic studies and continue evaluation and improvement of public health surveillance systems.

Phenotypic abnormalities strongly reflect genotype in patients with unexplained cytopenias.

BACKGROUND: In patients with unexplained cytopenias, abnormal karyotyping studies can be found with inconclusive light microscopic findings. Multidimensional flow cytometry (FCM) can identify myelomonocytic cells with aberrant phenotypes often not seen by standard morphology. METHODS: In 431 patients presenting with unexplained cytopenia(s) FCM results were compared to abnormal karyotyping and FISH results recognized as associated with myelodysplastic syndrome (MDS) in the 2008 WHO classification, to assess the degree of and types of phenotypic abnormalities observed using a previously reported flow cytometric scoring system (FCSS). Fluorescence activated cell sorting was also used to identify subpopulations of abnormal maturing myelomonocytic cells that carry the genotypic abnormality. RESULTS: For marrows with complex (three or more karyotypic abnormalities), two abnormalities, isolated chromosome seven anomalies, del(5q) or del(13q), 100% of cases were positive when using a FCSS cutoff of ≥ 2. Trisomy 8, del(20 q), and minus Y had flow scores ≥ 2 in 72, 60, and 18%, respectively, but in some cases the flow score was high, indicating myeloid dysplasia. Most patients (16/22) with high myeloid progenitor cells (MyPC) (> 20%) also exhibited maturing myeloid cell abnormalities by FCM. Morphology was negative in the maturing myeloid cells in many cases with phenotypically abnormal myeloid cells. CONCLUSIONS: The high correlation between genotypic and phenotypic abnormalities suggests a possible increased utility of flow cytometry in the diagnosis of patients with unexplained cytopenias and may be useful in future clinical studies and in the classification by the WHO, using the FCSS rather than simple counting of flow cytometric abnormalities.

The kinetics of plasmin inhibition by aprotinin in vivo.

INTRODUCTION: The purpose of this study was to estimate, in patients undergoing cardiopulmonary bypass (CPB), the in vivo rates of tissue plasminogen activator (tPA) and plasminogen activator inhibitor 1 (PAI-1) secretion, plasmin generation, fibrin degradation, and plasmin inhibition by aprotinin versus antiplasmin. MATERIALS AND METHODS: Estimates of in vivo rates were based on measured levels of tPA, PAI-1, antiplasmin, plasmin-antiplasmin complex (PAP), total aprotinin, plasmin-aprotinin complex and D-dimer, combined with a computer model of each patient's vascular system that continuously accounted for secretion, clearance, hemodilution, blood loss and transfusion. Plasmin regulation was studied in nine control patients undergoing CPB without aprotinin versus six patients treated with aprotinin. RESULTS: In controls, plasmin-antiplasmin levels rose from a baseline of 3.0+/-0.9 to a peak of 8.1+/-2.7 nmol/L after CPB due to an average 44-fold rise in the plasmin generation rate. This rise in plasmin generation during CPB lead to increased fibrin degradation causing D-dimer levels to increase from a baseline of 1.2+/-0.6 to a peak of 9.7+/-4.4 nmol/L due to an average 74-fold rise in the D-dimer generation rate. During CPB in the aprotinin group, plasmin-antiplasmin levels dropped, plasmin-aprotinin complex levels rose, while D-dimer levels remained unchanged from baseline. Compared to controls, the aprotinin group showed similar rates of plasmin generation during CPB, but an 11-fold faster plasmin inhibition rate and a 10-fold lower D-dimer generation rate. CONCLUSIONS: The rise in plasmin generation and fibrin degradation that occurs during standard CPB is suppressed by the addition of aprotinin, which returns the patient to near baseline fibrin degradation rates during CPB.