Commutability and Uncertainty of Blood Hemoglobin A1c Testing Materials.

BACKGROUND: Hemoglobin A1C (HbA1C) is used to evaluate glycemic control over a three-month period. Blood matrix-based HbA1C materials are needed for quality control and evaluation of HbA1C measurements. This study investigated the commutability of blood materials (BMs) and aimed to upgrade BMs for HbA1C testing for use as proficiency test (PT) material. METHODS: We measured BMs from a DM blood donor (n = 1), an in vitro glycation procedure (n = 3), and from commercial sources (n = 2) for HbA1C in parallel with fresh unprocessed BMs (n = 3) and clinical blood samples (n = 25). Two NGSP-certified methods, including a turbidimetric and an enzymatic immunoassay, were used for HbA1C determinations. Commutability as investigated according to CLSI EP14-Ed4 guidelines. RESULTS: The commutable BMs exhibited a mean paired difference of 0% to 9% when compared to reference methods, whereas the non-commutable BMs represented a mean paired difference of 3% to 11%. Fresh, unprocessed BMs with a low HbA1C of 6.0% were more commutable than BMs with a high HbA1C. The values of HbA1C in BMs (mean and uncertainty following ISO Guide 35 for RM production) were applied to upgrade the PT material to be used as a reference material. The relative uncertainty of BM-Ndm-1 and BM-Gcb-3 were 1 and 0.4%, respectively. CONCLUSIONS: The commutability of hemoglobin in BMs is dependent on the preparation process. Blood materials with a high HbA1C content are usually less commutable versus materials with low HbA1C content when prepared by the same process. Our study showed BMs can be successfully used as quality control or PT materials.

Point of care blood glucose devices in the hospital setting.

Dysglycemia is common among hospitalized patients. Accurate point-of-care (POC) glucose monitoring is necessary for the safe administration of insulin. Unfortunately, POC glucose meters are not all created equal. Interfering factors such as abnormal hematocrit, abnormal oxygen tension, and oxidizing/reducing substances can lead to inaccurate glucose measurements and result in inappropriate insulin dosing. The introduction of autocorrecting glucose meters has changed the POC testing landscape. Autocorrecting glucose meters provide more accurate measurements and have been associated with improved glycemic control in hospitalized patients. Continuous glucose monitoring has also created interest in using these platforms in at-risk inpatient populations. Future glucose monitoring technologies such as artificial intelligence/machine learning, wearable smart devices, and closed-loop insulin management systems are poised to transform glycemic management. The goal of this review is to provide an overview of glucose monitoring technology, summarize the clinical impact of glucose monitoring accuracy, and highlight emerging and future POC glucose monitoring technologies.

Machine learning and artificial intelligence for the diagnosis of infectious diseases in immunocompromised patients.

PURPOSE OF REVIEW: Immunocompromised patients are at high risk for infection. During the coronavirus disease (COVID-19) pandemic, immunocompromised patients exhibited increased odds of intensive care unit admission and death. Early pathogen identification is essential to mitigating infection related risk in immunocompromised patients. Artificial intelligence (AI) and machine learning (ML) have tremendous appeal to address unmet diagnostic needs. These AI/ML tools often rely on the wealth of data found in healthcare to enhance our ability to identify clinically significant patterns of disease. To this end, our review provides an overview of the current AI/ML landscape as it applies to infectious disease testing with emphasis on immunocompromised patients. RECENT FINDINGS: Examples include AI/ML for predicting sepsis in high risk burn patients. Likewise, ML is utilized to analyze complex host-response proteomic data to predict respiratory infections including COVID-19. These same approaches have also been applied for pathogen identification of bacteria, viruses, and hard to detect fungal microbes. Future uses of AI/ML may include integration of predictive analytics in point-of-care (POC) testing and data fusion applications. SUMMARY: Immunocompromised patients are at high risk for infections. AI/ML is transforming infectious disease testing and has great potential to address challenges encountered in the immune compromised population.

Evaluation of pharmacist guided intervention using procalcitonin and respiratory virus testing.

INTRODUCTION: Acute respiratory infections make up a sizable percentage of emergency department (ED) visits and many result in antibiotics being prescribed. Procalcitonin (PCT) has been found to reduce antibiotic use in both outpatient and critical care settings, yet remains underused in the ED. This study aimed to evaluate whether point of care molecular influenza and Respiratory Syncytial Virus (RSV) testing, PCT, and a pharmacist driven educational intervention in aggregate optimizes antibiotic and antiviral prescribing in the ED setting. METHODS: A randomized trial of the Cobas Liat Flu/RSV Assay, procalcitonin, and the use of pharmacist-led education in patients 0-50 years of age being seen in the ED for Influenza Like Illness (ILI) or acute respiratory illness. The study enrolled 200 ED patients between March 2018 and April 2022. RESULTS: There was little difference in antibiotic or antiviral prescribing between the intervention and control groups in this study (39%-32% = 7.0%, 95% CI: -6.2, 20.2, P = 0.30). However, a post-hoc analysis of the use of procalcitonin showed results were used as indicated in the ED (P = 0.001). CONCLUSION: PCT can be used in both adult and pediatric populations to help guide the decision of whether to treat with antibiotics in the ED setting. Pharmacist guided education may not be a driving factor.

Clinical Performance of the Point-of-Care cobas Liat for Detection of SARS-CoV-2 in 20 Minutes: a Multicenter Study.

Highly accurate testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at the point of care (POC) is an unmet diagnostic need in emergency care and time-sensitive outpatient care settings. Reverse transcription-PCR (RT-PCR) technology is the gold standard for SARS-CoV-2 diagnostics. We performed a multisite U.S. study comparing the clinical performance of the first U.S. Food and Drug Administration (FDA)-authorized POC RT-PCR for detection of SARS-CoV-2 in 20 min, the cobas Liat SARS-CoV-2 and influenza A/B nucleic acid test, to the most widely used RT-PCR laboratory test, the cobas 68/8800 SARS-CoV-2 test. Clinical nasopharyngeal swab specimens from 444 patients with 357 evaluable specimens at five U.S. clinical laboratories were enrolled from 21 September 2020 to 23 October 2020. The overall agreement between the Liat and 68/8800 systems for SARS-CoV-2 diagnostics was 98.6% (352/357). Using Liat, positive percent agreement for SARS-CoV-2 was 100% (162/162) and the negative percent agreement was 97.4% (190/195). The Liat is an RT-PCR POC test that provides highly accurate SARS-CoV-2 results in 20 min with performance equivalent to that of high-throughput laboratory molecular testing. Rapid RT-PCR testing at the POC can enable more timely infection control and individual care decisions for coronavirus disease 2019.

Evolving Applications of Artificial Intelligence and Machine Learning in Infectious Diseases Testing.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are poised to transform infectious disease testing. Uniquely, infectious disease testing is technologically diverse spaces in laboratory medicine, where multiple platforms and approaches may be required to support clinical decision-making. Despite advances in laboratory informatics, the vast array of infectious disease data is constrained by human analytical limitations. Machine learning can exploit multiple data streams, including but not limited to laboratory information and overcome human limitations to provide physicians with predictive and actionable results. As a quickly evolving area of computer science, laboratory professionals should become aware of AI/ML applications for infectious disease testing as more platforms are become commercially available. CONTENT: In this review we: (a) define both AI/ML, (b) provide an overview of common ML approaches used in laboratory medicine, (c) describe the current AI/ML landscape as it relates infectious disease testing, and (d) discuss the future evolution AI/ML for infectious disease testing in both laboratory and point-of-care applications. SUMMARY: The review provides an important educational overview of AI/ML technique in the context of infectious disease testing. This includes supervised ML approaches, which are frequently used in laboratory medicine applications including infectious diseases, such as COVID-19, sepsis, hepatitis, malaria, meningitis, Lyme disease, and tuberculosis. We also apply the concept of "data fusion" describing the future of laboratory testing where multiple data streams are integrated by AI/ML to provide actionable clinical knowledge.

ED syphilis and gonorrhea/chlamydia cotesting practices before and after the implementation of an electronic health record-based alert.

BACKGROUND: The prevalence of syphilis is increasing in many countries, including the USA. The ED is often used by underserved populations, making it an important setting to test and treat patients who are not evaluated in outpatient clinical settings. We aimed to assess the utility of an ED-based syphilis and gonorrhoea/chlamydia cotesting protocol by comparing testing practices before and after its implementation. METHODS: We implemented an electronic health record (EHR) alert that prompted clinicians to order syphilis testing in patients undergoing gonorrhoea/chlamydia testing. We performed a retrospective cohort analysis that compared outcomes between the preimplementation period (January-November 2018) and the postimplementation period (January-November 2019). Patients were tested for Treponema pallidum antibody (TPA) using a multiplex flow immunoassay (MFI), and positive results were confirmed by rapid plasma reagin (RPR). The primary implementation outcome was the number of syphilis tests/month, and the primary clinical outcome was the number of syphilis diagnoses/month (defined as positive TPA MFI and RPR). We performed an interrupted time-series analysis to evaluate the effect of implementing the alert over time. RESULTS: Four-hundred and ninety-four and 1106 unique patients were tested for syphilis in the preimplementation and postimplementation periods, respectively. Syphilis testing increased by 55.6 tests/month (95% CI 45.9 to 65.3, p<0.001) following alert implementation. Patients tested in the postimplementation period who were tested using the alert were much younger (difference: 14 years (95% CI 12 to 15)) and were more likely to be female (difference: 15% (95% CI 8 to 21)) and African-American (difference: 11% (95% CI 5 to 17)) than patients tested by clinician-initiated testing. Presumptive syphilis diagnoses increased from 3.4 diagnoses/month to 7.9 diagnoses/month (difference, 4.5 (95% CI 2.2 to 6.9), p<0.001). CONCLUSIONS: Our study demonstrates that use of a targeted EHR alert testing protocol can increase syphilis testing and diagnosis and may reduce clinician bias in testing.

Investigating Transfusion-related Sepsis Using Culture-Independent Metagenomic Sequencing.

BACKGROUND: Transfusion-related sepsis remains an important hospital infection control challenge. Investigation of septic transfusion events is often restricted by the limitations of bacterial culture in terms of time requirements and low yield in the setting of prior antibiotic administration. METHODS: In 3 gram-negative septic transfusion cases, we performed metagenomic next-generation sequencing (mNGS) of direct clinical blood specimens in addition to standard culture-based approaches utilized for infection control investigations. Pathogen detection leveraged IDSeq, a new open-access microbial bioinformatics portal. Phylogenetic analysis was performed to assess microbial genetic relatedness and understand transmission events. RESULTS: mNGS of direct clinical blood specimens afforded precision detection of pathogens responsible for each case of transfusion-related sepsis and enabled discovery of a novel Acinetobacter species in a platelet product that had become contaminated despite photochemical pathogen reduction. In each case, longitudinal assessment of pathogen burden elucidated the temporal sequence of events associated with each transfusion-transmitted infection. We found that informative data could be obtained from culture-independent mNGS of residual platelet products and leftover blood specimens that were either unsuitable or unavailable for culture or that failed to grow due to prior antibiotic administration. We additionally developed methods to enhance accuracy for detecting transfusion-associated pathogens that share taxonomic similarity to contaminants commonly found in mNGS library preparations. CONCLUSIONS: Culture-independent mNGS of blood products afforded rapid and precise assessment of pathogen identity, abundance, and genetic relatedness. Together, these challenging cases demonstrated the potential for metagenomics to advance existing methods for investigating transfusion-transmitted infections.

Relationship of Cerebrospinal Fluid Vitamin B12 Status Markers With Parkinson's Disease Progression.

BACKGROUND: Using blood specimens from untreated early Parkinson's disease (PD) patients from the DATATOP trial, we found that subjects in the low serum vitamin B12 tertile experienced greater annualized change in ambulatory capacity score, whereas those with moderately elevated (>15 µmol/L) total homocysteine had greater annualized declines in the Mini-Mental State Exam. METHODS: In this this study we sought to determine whether levels of cerebrospinal fluid (CSF) B12 markers were also associated with progression of PD. RESULTS: The annualized change in the UPDRS "walking" item, a component of the ambulatory capacity score, was worse in the low B12 tertile. No association with change in the Mini-Mental State Exam was seen for those 7% with the highest baseline CSF total homocysteine. CONCLUSIONS: In these untreated early-PD subjects, low CSF B12 predicted greater worsening of the UPDRS "walking" item, whereas CSF total homocysteine was not associated with progression of cognitive impairment. These findings extend and partially support our findings in serum. © 2020 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Prospective study of serum and ionized magnesium pharmacokinetics in the treatment of children with severe acute asthma.

PURPOSE: Intravenous (IV) magnesium sulfate (MgSO4) is clinically useful as adjunct therapy in treating acute asthma exacerbations. Despite its clinical utility, the disposition of magnesium in children is poorly described. The purpose of this study is to describe the pharmacokinetics (PK) of ionized and total serum magnesium following IV MgSO4 administration in children with severe acute asthma. METHODS: Thirty-two children receiving 50 mg/kg IV MgSO4 for acute asthma exacerbations at Primary Children's Hospital in Salt Lake City, UT, were prospectively enrolled in the study. Blood samples were collected before, as well as 30 min and 2 h after each child's IV MgSO4 dose, and used to determine total serum and ionized magnesium concentrations. The collected data were analyzed using population PK techniques using NONMEM® software. RESULTS: Total serum magnesium concentrations were used to externally validate our previously published model constructed with retrospective data (median prediction error 10.3%, median absolute prediction error 18.1%). The mean (%CV) observed endogenous ionized magnesium concentration was calculated to be 6.0 mg/L (12%), approximately one third of the same value for endogenous total serum magnesium (17.6 mg/L (22%)) in this dataset. Weight was a significant predictor of both clearance and volume in a population PK model describing ionized magnesium concentrations. No adverse events were observed in this pediatric cohort. CONCLUSIONS: This prospective study supports and extends our previous PK analysis of total serum magnesium concentrations. Ionized and total serum magnesium followed similar PK profiles following IV MgSO4 administration in children. A single bolus infusion of IV MgSO4 was safe in this small sample of children receiving it for acute asthma.

Clinical Impact of Accurate Point-of-Care Glucose Monitoring for Tight Glycemic Control in Severely Burned Children.

OBJECTIVES: The goal of this study was to retrospectively evaluate the clinical impact of an accurate autocorrecting blood glucose monitoring system in children with severe burns. Blood glucose monitoring system accuracy is essential for providing appropriate intensive insulin therapy and achieving tight glycemic control in critically ill patients. Unfortunately, few comparison studies have been performed to evaluate the clinical impact of accurate blood glucose monitoring system monitoring in the high-risk pediatric burn population. DESIGN: Retrospective analysis of an electronic health record system. SETTING: Pediatric burn ICU at an academic medical center. PATIENTS: Children (aged < 18 yr) with severe burns (≥ 20% total body surface area) receiving intensive insulin therapy guided by either a noncorrecting (blood glucose monitoring system-1) or an autocorrecting blood glucose monitoring system (blood glucose monitoring system-2). MEASUREMENTS AND MAIN RESULTS: Patient demographics, insulin rates, and blood glucose monitoring system measurements were collected. The frequency of hypoglycemia and glycemic variability was compared between the two blood glucose monitoring system groups. A total of 122 patient charts from 2001 to 2014 were reviewed. Sixty-three patients received intensive insulin therapy using blood glucose monitoring system-1 and 59 via blood glucose monitoring system-2. Patient demographics were similar between the two groups. Mean insulin infusion rates (5.1 ± 3.8 U/hr; n = 535 paired measurements vs 2.4 ± 1.3 U/hr; n = 511 paired measurements; p < 0.001), glycemic variability, and frequency of hypoglycemic events (90 vs 12; p < 0.001) were significantly higher in blood glucose monitoring system-1-treated patients. Compared with laboratory measurements, blood glucose monitoring system-2 yielded the most accurate results (mean ± SD bias: -1.7 ± 6.9 mg/dL [-0.09 ± 0.4 mmol/L] vs 7.4 ± 13.5 mg/dL [0.4 ± 0.7 mmol/L]). Blood glucose monitoring system-2 patients achieve glycemic control more quickly (5.7 ± 4.3 vs 13.1 ± 6.9 hr; p< 0.001) and stayed within the target glycemic control range longer compared with blood glucose monitoring system-1 patients (85.2% ± 13.9% vs 57.9% ± 29.1%; p < 0.001). CONCLUSIONS: Accurate autocorrecting blood glucose monitoring system optimizes intensive insulin therapy, improves tight glycemic control, and reduces the risk of hypoglycemia and glycemic variability. The use of an autocorrecting blood glucose monitoring system for intensive insulin therapy may improve glycemic control in severely burned children.

Identification of Gram-Negative Bacteria and Genetic Resistance Determinants from Positive Blood Culture Broths by Use of the Verigene Gram-Negative Blood Culture Multiplex Microarray-Based Molecular Assay.

Bloodstream infection is a serious condition associated with significant morbidity and mortality. The outcome of these infections can be positively affected by the early implementation of effective antibiotic therapy based on the identification of the infecting organism and genetic markers associated with antibiotic resistance. In this study, we evaluated the microarray-based Verigene Gram-negative blood culture (BC-GN) assay in the identification of 8 genus or species targets and 6 genetic resistance determinants in positive blood culture broths. A total of 1,847 blood cultures containing Gram-negative organisms were tested using the BC-GN assay. This comprised 729 prospective fresh, 781 prospective or retrospective frozen, and 337 simulated cultures representing 7 types of aerobic culture media. The results were compared to those with standard bacterial culture and biochemical identification with nucleic acid sequence confirmation of the resistance determinants. Among monomicrobial cultures, the positive percent agreement (PPA) of the BC-GN assay with the reference method was as follows; Escherichia coli, 100%; Klebsiella pneumoniae, 92.9%; Klebsiella oxytoca, 95.5%; Enterobacter spp., 99.3%; Pseudomonas aeruginosa, 98.9%; Proteus spp., 100%; Acinetobacter spp., 98.4%; and Citrobacter spp., 100%. All organism identification targets demonstrated >99.5% negative percent agreement (NPA) with the reference method. Of note, 25/26 cultures containing K. pneumoniae that were reported as not detected by the BC-GN assay were subsequently identified as Klebsiella variicola. The PPA for identification of resistance determinants was as follows; blaCTX-M, 98.9%; blaKPC, 100%; blaNDM, 96.2%; blaOXA, 94.3%; blaVIM, 100%; and blaIMP, 100%. All resistance determinant targets demonstrated >99.9% NPA. Among polymicrobial specimens, the BC-GN assay correctly identified at least one organism in 95.4% of the broths and correctly identified all organisms present in 54.5% of the broths. The sample-to-result processing and automated reading of the detection microarray results enables results within 2 h of culture positivity.

Whole blood neutrophil gelatinase-associated lipocalin predicts acute kidney injury in burn patients.

BACKGROUND: Early detection of acute kidney injury (AKI) in severely burn-injured patients can help alter treatment to prevent progression to acute failure and reduce the need for renal replacement therapy. We hypothesized that whole blood neutrophil gelatinase-associated lipocalin (NGAL) will be increased in severely burn-injured patients who develop AKI during acute resuscitation. MATERIALS AND METHODS: We performed a prospective observation study of adult burn patients with a 20% total body surface area (TBSA) burned or greater burn injury. Two-hour serial measurements of NGAL, serum creatinine (Cr), and hourly urine output (UO) were collected for 48 h after admission. Our primary goal was to correlate the risk of AKI in the first week after burn injury with serial NGAL levels in the first 48 h after admission. Our secondary goal was to determine if NGAL was an earlier independent predictor of AKI compared with Cr and UO. RESULTS: We enrolled 30 adult (age ≥ 18 y) burn patients with the mean ± standard deviation age of 40.9 ± 15.4 and mean TBSA of 46.4 ± 22.4. Fourteen patients developed AKI within the first 7 d after burn injury. There were no differences in age, TBSA, fluid administration, mean arterial pressure, UO, and Cr between AKI and no-AKI patients. NGAL was significantly increased as early as 4 h after injury (182.67 ± 83.3 versus 107.37 ± 46.15) in the AKI group. Controlling for age, TBSA, and inhalation injury, NGAL was a predictor of AKI at 4 h after injury (odds ratio, 1.02) and remained predictive of AKI for the period of more than the first 24 h after admission. UO and Cr were not predictive of AKI in the first 24 h after admission. CONCLUSIONS: Whole blood NGAL is markedly increased in burn patients who develop AKI in the first week after injury. In addition, NGAL is an early independent predictor of AKI during acute resuscitation for severe burn injury. UO and Cr are not predictive of AKI during this time period.

Not Carfentanil-A Case of Unexpected Xylazine Detection.

Historically, xylazine has been utilized in veterinary medicine for decades as an anesthetic and analgesic sedative to facilitate safe handling, diagnostic testing, and surgical procedures in large animals. Currently, xylazine is an emerging threat to human health. It has been detected in the illicit drug supply chain, often as an adulterant. It has been more commonly added to illicit substances, most notably fentanyl, by drugmakers to enhance drug effect. End users are often unaware of its presence. This is alarming given the large number of xylazine-involved overdose deaths while laboratory detections are deficient and reversal agents are absent. Herein, we present the first documented case of xylazine identified via gas chromatography-tandem mass spectrometry at University of California Davis Health despite a peculiarly mild clinical presentation. We hope to increase awareness of this potentially fatal adulterant that is often missed in evaluation and engender further opportunities to study this ongoing issue.

Plasma-derived extracellular vesicles (EVs) as biomarkers of sepsis in burn patients via label-free Raman spectroscopy.

Sepsis following burn trauma is a global complication with high mortality, with ∼60% of burn patient deaths resulting from infectious complications. Diagnosing sepsis is complicated by confounding clinical manifestations of the burn injury, and current biomarkers lack the sensitivity and specificity required for prompt treatment. There is a strong rationale to assess circulating extracellular vesicles (EVs) from patient liquid biopsy as sepsis biomarkers due to their release by pathogens from bacterial biofilms and roles in the subsequent immune response. This study applies Raman spectroscopy to patient plasma-derived EVs for rapid, sensitive, and specific detection of sepsis in burn patients, achieving 97.5% sensitivity and 90.0% specificity. Furthermore, spectral differences between septic and non-septic burn patient EVs could be traced to specific glycoconjugates of bacterial strains associated with sepsis morbidity. This work illustrates the potential application of EVs as biomarkers in clinical burn trauma care and establishes Raman analysis as a fast, label-free method to specifically identify features of bacterial EVs relevant to infection amongst the host background.

Correlation between locally versus centrally processed serum procalcitonin during emergency department research evaluation of febrile infants aged 0-60 days.

Introduction: Procalcitonin (PCT) is a useful biomarker in the initial evaluation of febrile infants for serious bacterial infections (SBIs). However, PCT is not always available locally and must at times be frozen and shipped to a reference laboratory for research studies. We sought to compare PCT measured locally versus centrally at a reference laboratory during a research study. Materials and methods: This was a secondary analysis of a multicenter study of febrile infants ≤60 days evaluated for SBIs from June 2016 to April 2019. A PCT cutoff value of 0.5 ng/mL was used to stratify infants at low-versus high-risk of SBIs. Statistical analyses consisted of Spearman's correlation, Bland-Altman difference plotting, Passing-Bablok regression, Deming regression, and Fisher's exact testing at the 0.5 ng/mL threshold. Results: 241 febrile infants had PCT levels measured both locally and at the reference laboratory. PCT levels measured locally on 5 different platforms and from the frozen research samples demonstrated strong Spearman's correlation (ρ = 0.83) and had similar mean PCT values with an average relative difference of 0.02%. Eleven infants with SBIs had PCT values < 0.5 ng/mL in both the clinical and research samples. Six other infants had differences in SBI prediction based on PCT values at the 0.5 ng/mL threshold between the clinical and research platforms. Conclusions: We found no significant differences in detection of febrile infants at high risk for SBI based on locally (on multiple platforms) versus centrally processed PCT. Testing at a central reference laboratory after freezing and shipping is an accurate and reliable alternative for research studies or when rapid turnaround is not required.

Plasma-derived Extracellular Vesicles (EVs) as Biomarkers of Sepsis in Burn Patients via Label-free Raman Spectroscopy.

Sepsis following burn trauma is a global complication with high mortality, with ~60% of burn patient deaths resulting from infectious complications. Sepsis diagnosis is complicated by confounding clinical manifestations of the burn injury, and current biomarkers markers lack the sensitivity and specificity required for prompt treatment. Circulating extracellular vesicles (EVs) from patient liquid biopsy as biomarkers of sepsis due to their release by pathogens from bacterial biofilms and roles in subsequent immune response. This study applies Raman spectroscopy to patient plasma derived EVs for rapid, sensitive, and specific detection of sepsis in burn patients, achieving 97.5% sensitivity and 90.0% specificity. Furthermore, spectral differences between septic and non-septic burn patient EVs could be traced to specific glycoconjugates of bacterial strains associated with sepsis morbidity. This work illustrates the potential application of EVs as biomarkers in clinical burn trauma care, and establishes Raman analysis as a fast, label-free method to specifically identify features of bacterial EVs relevant to infection amongst the host background.

Comparator Data Characteristics and Testing Procedures for the Clinical Performance Evaluation of Continuous Glucose Monitoring Systems.

Comparing the performance of different continuous glucose monitoring (CGM) systems is challenging due to the lack of comprehensive guidelines for clinical study design. In particular, the absence of concise requirements for the distribution of comparator (reference) blood glucose (BG) concentrations and their rate of change (RoC) that are used to evaluate CGM performance, impairs comparability. For this article, several experts in the field of CGM performance testing have collaborated to propose characteristics of the distribution of comparator measurements that should be collected during CGM performance testing. Specifically, it is proposed that at least 7.5% of comparator BG concentrations are <70 mg/dL (3.9 mmol/L) and >300 mg/dL (16.7 mmol/L), respectively, and that at least 7.5% of BG-RoC combinations indicate fast BG changes with impending hypo- or hyperglycemia, respectively. These proposed characteristics of the comparator data can facilitate the harmonization of testing conditions across different studies and CGM systems and ensure that the most relevant scenarios representing real-life situations are established during performance testing. In addition, a study protocol and testing procedure for the manipulation of glucose levels are suggested that enable the collection of comparator data with these characteristics. This work is an important step toward establishing a future standard for the performance evaluation of CGM systems.

Consensus Considerations and Good Practice Points for Use of Continuous Glucose Monitoring Systems in Hospital Settings.

Continuous glucose monitoring (CGM) systems provide frequent glucose measurements in interstitial fluid and have been used widely in ambulatory settings for diabetes management. During the coronavirus disease 2019 (COVID-19) pandemic, regulators in the U.S. and Canada temporarily allowed for CGM systems to be used in hospitals with the aim of reducing health care professional COVID-19 exposure and limiting use of personal protective equipment. As such, studies on hospital CGM system use have been possible. With improved sensor accuracy, there is increased interest in CGM usage for diabetes management in hospitals. Laboratorians and health care professionals must determine how to integrate CGM usage into practice. The aim of this consensus guidance document is to provide an update on the application of CGM systems in hospital, with insights and opinions from laboratory medicine, endocrinology, and nursing.

The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors.

INTRODUCTION: An error grid compares measured versus reference glucose concentrations to assign clinical risk values to observed errors. Widely used error grids for blood glucose monitors (BGMs) have limited value because they do not also reflect clinical accuracy of continuous glucose monitors (CGMs). METHODS: Diabetes Technology Society (DTS) convened 89 international experts in glucose monitoring to (1) smooth the borders of the Surveillance Error Grid (SEG) zones and create a user-friendly tool-the DTS Error Grid; (2) define five risk zones of clinical point accuracy (A-E) to be identical for BGMs and CGMs; (3) determine a relationship between DTS Error Grid percent in Zone A and mean absolute relative difference (MARD) from analyzing 22 BGM and nine CGM accuracy studies; and (4) create trend risk categories (1-5) for CGM trend accuracy. RESULTS: The DTS Error Grid for point accuracy contains five risk zones (A-E) with straight-line borders that can be applied to both BGM and CGM accuracy data. In a data set combining point accuracy data from 18 BGMs, 2.6% of total data pairs equally moved from Zones A to B and vice versa (SEG compared with DTS Error Grid). For every 1% increase in percent data in Zone A, the MARD decreased by approximately 0.33%. We also created a DTS Trend Accuracy Matrix with five trend risk categories (1-5) for CGM-reported trend indicators compared with reference trends calculated from reference glucose. CONCLUSION: The DTS Error Grid combines contemporary clinician input regarding clinical point accuracy for BGMs and CGMs. The DTS Trend Accuracy Matrix assesses accuracy of CGM trend indicators.