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Article ; Online: Advances in noninvasive measurement of liver function and physiology: The HepQuant DuO test.

McRae, Michael P / Kittelson, John / Helmke, Steve M / Everson, Gregory T

Basic & clinical pharmacology & toxicology

2024 Volume 134, Issue 3, Page(s) 385–395

Abstract: Current noninvasive liver tests are surrogates for fibrosis and lack ability to directly measure liver function. HepQuant tests measure liver function and physiology through hepatic uptake of stable cholate isotopes. HepQuant SHUNT (V1.0) involves oral ... ...

Abstract	Current noninvasive liver tests are surrogates for fibrosis and lack ability to directly measure liver function. HepQuant tests measure liver function and physiology through hepatic uptake of stable cholate isotopes. HepQuant SHUNT (V1.0) involves oral and intravenous dosing and six blood samples over 90 min. We developed simplified test versions: SHUNT V2.0 (oral and intravenous dosing, two blood samples over 60 min) and DuO (oral dosing only, two blood samples over 60 min). The aim of this study was to evaluate equivalency of the simplified tests to the original SHUNT test. Data from three studies comprising 930 SHUNT tests were retrospectively analysed by each method. Equivalence was evaluated in terms of proportion of tests in which the difference between methods was less than any clinically meaningful difference and additionally by two one-sided t-test and bioequivalence methods. DuO and SHUNT V2.0 were equivalent to the original SHUNT test for Disease Severity Index, with >99% and >96% of tests falling within equivalence bounds. DuO and SHUNT V2.0 met equivalency criteria by two one-sided t-tests and bioequivalence. DuO and SHUNT V2.0 are easier to administer, are less invasive than the original SHUNT test and have potential to be more accepted by patients and providers.
MeSH term(s)	Humans ; Retrospective Studies ; Liver ; Liver Cirrhosis/diagnosis ; Liver Function Tests ; Therapeutic Equivalency
Language	English
Publishing date	2024-01-15
Publishing country	England
Document type	Journal Article
ZDB-ID	2134679-3
ISSN	1742-7843 ; 1742-7835
ISSN (online)	1742-7843
ISSN	1742-7835
DOI	10.1111/bcpt.13980
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Article ; Online: Within-individual reproducibility of a dual sample oral cholate challenge test (DuO) and simplified versions of the HepQuant SHUNT test.

McRae, Michael P / Kittelson, John / Helmke, Steve M / Everson, Gregory T

Clinical and translational science

2024 Volume 17, Issue 4, Page(s) e13786

Abstract: Current noninvasive liver tests measure fibrosis, inflammation, or steatosis and do not measure function. The HepQuant platform of noninvasive tests uniquely assesses both liver function and physiology through the hepatic uptake of stable isotopes of ... ...

Abstract	Current noninvasive liver tests measure fibrosis, inflammation, or steatosis and do not measure function. The HepQuant platform of noninvasive tests uniquely assesses both liver function and physiology through the hepatic uptake of stable isotopes of cholate. However, the prototypical HepQuant SHUNT test (SHUNT V1.0) is cumbersome to administer, requiring intravenous and oral administration of cholate and six peripheral venous blood samples over 90 min. To alleviate the burden of test administration, we explored whether an oral only (DuO) version, and other simplified versions, of the test could provide reproducible measurements of liver function. DuO requires only oral dosing and two blood samples over 60 min. The simplified SHUNT test versions were SHUNT V1.1 (oral and IV dosing but four blood samples) and SHUNT V2.0 (oral and IV dosing but only two blood samples over 60 min). In this paper, we describe the reproducibility of DuO and the simplified SHUNT tests relative to that of SHUNT V1.0; equivalency is described in a separate paper. Data from two studies comprising 236 SHUNT tests in 94 subjects were analyzed retrospectively by each method. All simplified methods were highly reproducible across test parameters with intraclass correlation coefficients >0.93 for test parameters Disease Severity Index (DSI) and Hepatic Reserve. DuO and SHUNT V2.0 improved reproducibility in measuring portal-systemic shunting (SHUNT%). These simplified tests, particularly DuO and SHUNT V2.0, are easier to administer and less invasive, thus, having the potential to be more widely accepted by care providers administering the test and by patients receiving the test.
MeSH term(s)	Humans ; Reproducibility of Results ; Retrospective Studies ; Liver Function Tests ; Liver ; Cholates
Chemical Substances	Cholates
Language	English
Publishing date	2024-04-01
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2433157-0
ISSN	1752-8062 ; 1752-8054
ISSN (online)	1752-8062
ISSN	1752-8054
DOI	10.1111/cts.13786
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Article ; Online: Smart Diagnostics: Combining Artificial Intelligence and In Vitro Diagnostics.

McRae, Michael P / Rajsri, Kritika S / Alcorn, Timothy M / McDevitt, John T

Sensors (Basel, Switzerland)

2022 Volume 22, Issue 17

Abstract: We are beginning a new era ... ...

Abstract	We are beginning a new era of
MeSH term(s)	Artificial Intelligence ; Biosensing Techniques ; COVID-19/diagnosis ; COVID-19 Testing ; Humans ; Microfluidics ; Point-of-Care Systems
Language	English
Publishing date	2022-08-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s22176355
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Article ; Online: Compartmental model describing the physiological basis for the HepQuant SHUNT test.

McRae, Michael P / Helmke, Steve M / Burton, James R / Everson, Gregory T

Translational research : the journal of laboratory and clinical medicine

2022 Volume 252, Page(s) 53–63

Abstract: The HepQuant SHUNT test quantifies hepatic functional impairment from the simultaneous clearance of cholate from the systemic and portal circulations for the purpose of monitoring treatment effects or for predicting risk for clinical outcome. ... ...

Abstract	The HepQuant SHUNT test quantifies hepatic functional impairment from the simultaneous clearance of cholate from the systemic and portal circulations for the purpose of monitoring treatment effects or for predicting risk for clinical outcome. Compartmental models are defined by distribution volumes and transfer rates between volumes to estimate parameters not defined by noncompartmental analyses. Previously, a noncompartmental analysis method, called the minimal model (MM), demonstrated reproducible and reliable measures of liver function (Translational Research 2021). The aim of this study was to compare the reproducibility and reliability of a new physiologically based compartmental model (CM) vs the MM. Data were analyzed from 16 control, 16 nonalcoholic steatohepatitis (NASH), and 16 hepatitis C virus (HCV) subjects, each with 3 replicate tests conducted on 3 separate days. The CM describes transfer of cholates between systemic, portal, and liver compartments with assumptions from measured or literature-derived values and unknown parameters estimated by nonlinear least-squares regression. The CM was compared to the MM for 6 key indices of hepatic disease in terms of intraclass correlation coefficient (ICC) with a lower acceptable limit of 0.7. The CM correlated well with the MM for disease severity index (DSI) with R
MeSH term(s)	Humans ; Epidemiological Models ; Reproducibility of Results ; Liver ; Non-alcoholic Fatty Liver Disease ; Liver Function Tests ; Cholates
Chemical Substances	Cholates
Language	English
Publishing date	2022-08-07
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2246684-8
ISSN	1878-1810 ; 1532-6543 ; 1931-5244
ISSN (online)	1878-1810 ; 1532-6543
ISSN	1931-5244
DOI	10.1016/j.trsl.2022.08.002
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Article: Simultaneous Quantitative SARS-CoV-2 Antigen and Host Antibody Detection and Pre-Screening Strategy at the Point of Care.

Srinivasan Rajsri, Kritika / McRae, Michael P / Christodoulides, Nicolaos J / Dapkins, Isaac / Simmons, Glennon W / Matz, Hanover / Dooley, Helen / Fenyö, David / McDevitt, John T

Bioengineering (Basel, Switzerland)

2023 Volume 10, Issue 6

Abstract: As COVID-19 pandemic public health measures are easing globally, the emergence of new SARS-CoV-2 strains continue to present high risk for vulnerable populations. The antibody-mediated protection acquired from vaccination and/or infection is seen to wane ...

Abstract	As COVID-19 pandemic public health measures are easing globally, the emergence of new SARS-CoV-2 strains continue to present high risk for vulnerable populations. The antibody-mediated protection acquired from vaccination and/or infection is seen to wane over time and the immunocompromised populations can no longer expect benefit from monoclonal antibody prophylaxis. Hence, there is a need to monitor new variants and its effect on vaccine performance. In this context, surveillance of new SARS-CoV-2 infections and serology testing are gaining consensus for use as screening methods, especially for at-risk groups. Here, we described an improved COVID-19 screening strategy, comprising predictive algorithms and concurrent, rapid, accurate, and quantitative SARS-CoV-2 antigen and host antibody testing strategy, at point of care (POC). We conducted a retrospective analysis of 2553 pre- and asymptomatic patients who were tested for SARS-CoV-2 by RT-PCR. The pre-screening model had an AUC (CI) of 0.76 (0.73-0.78). Despite being the default method for screening, body temperature had lower AUC (0.52 [0.49-0.55]) compared to case incidence rate (0.65 [0.62-0.68]). POC assays for SARS-CoV-2 nucleocapsid protein (NP) and spike (S) receptor binding domain (RBD) IgG antibody showed promising preliminary results, demonstrating a convenient, rapid (<20 min), quantitative, and sensitive (ng/mL) antigen/antibody assay. This integrated pre-screening model and simultaneous antigen/antibody approach may significantly improve accuracy of COVID-19 infection and host immunity screening, helping address unmet needs for monitoring vaccine effectiveness and severe disease surveillance.
Language	English
Publishing date	2023-06-01
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2746191-9
ISSN	2306-5354
ISSN	2306-5354
DOI	10.3390/bioengineering10060670
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Article ; Online: Multidisciplinary quality improvement programme for older patients admitted to a vascular surgery ward

Mudge, Alison M / McRae, Prue / Donovan, Peter J / Reade, Michael C

Internal medicine journal

2020 Volume 50, Issue 6, Page(s) 741–748

Abstract: ... 68-1.00), P = 0.04). There was a trend to less delirium (18 (14.6%) vs 24 (21.4%), P = 0.17) and ... functional decline (18 (14.6%) vs 27 (24.3%), P = 0.06), with greatest reductions in the urgently admitted ... subgroup. Administrative data showed reduced median LOS (5.2 days vs 6 days, P = 0.03) and greater ...

Abstract	Background: Older vascular surgical patients are at high risk of hospital-associated complications and prolonged stays. Aims: To implement a multidisciplinary co-management model for older vascular patients and evaluate impact on length of stay (LOS), delirium incidence, functional decline, medical complications and discharge destination. Methods: Prospective pre-post evaluation of a quality improvement intervention, enrolling pre-intervention (August 2012-January 2013) and post-intervention cohort (September 2013-March 2014). Participants were consenting patients aged 65 years and over admitted to the vascular surgical ward of a metropolitan teaching hospital for at least 3 days. Intervention was physician-led co-management plus a multidisciplinary improvement programme targeting delirium and functional decline. Primary outcomes were LOS, delirium and functional decline. Secondary outcomes were medical complications and discharge destination. Process measures included documented consultation patterns. Administrative data were also compared for all patients aged 65 and older for 12 months pre- and post-intervention. Results: We enrolled 112 participants pre-intervention and 123 participants post-intervention. LOS was reduced post-intervention (geometric mean 7.6 days vs 9.3 days; ratio of geometric means 0.82 (95% confidence interval CI0.68-1.00), P = 0.04). There was a trend to less delirium (18 (14.6%) vs 24 (21.4%), P = 0.17) and functional decline (18 (14.6%) vs 27 (24.3%), P = 0.06), with greatest reductions in the urgently admitted subgroup. Administrative data showed reduced median LOS (5.2 days vs 6 days, P = 0.03) and greater discharge home (72% vs 50%, P < 0.01). Conclusions: Physician-led co-management plus a multidisciplinary improvement programme may reduce LOS and improve functional outcomes in older vascular surgical patients.
MeSH term(s)	Aged ; Delirium/epidemiology ; Delirium/prevention & control ; Hospitalization ; Humans ; Length of Stay ; Prospective Studies ; Quality Improvement
Language	English
Publishing date	2020-06-15
Publishing country	Australia
Document type	Journal Article
ZDB-ID	2045436-3
ISSN	1445-5994 ; 1444-0903
ISSN (online)	1445-5994
ISSN	1444-0903
DOI	10.1111/imj.14400
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Article: Predictive modeling of morbidity and mortality in COVID-19 hospitalized patients and its clinical implications.

Wang, Joshua M / Liu, Wenke / Chen, Xiaoshan / McRae, Michael P / McDevitt, John T / Fenyö, David

medRxiv : the preprint server for health sciences

2021

Abstract: Clinical activity of 3740 de-identified COVID-19 positive patients treated at NYU Langone Health (NYULH) were collected between January and August 2020. XGBoost model trained on clinical data from the final 24 hours excelled at predicting mortality (AUC= ... ...

Abstract	Clinical activity of 3740 de-identified COVID-19 positive patients treated at NYU Langone Health (NYULH) were collected between January and August 2020. XGBoost model trained on clinical data from the final 24 hours excelled at predicting mortality (AUC=0.92, specificity=86% and sensitivity=85%). Respiration rate was the most important feature, followed by SpO2 and age 75+. Performance of this model to predict the deceased outcome extended 5 days prior with AUC=0.81, specificity=70%, sensitivity=75%. When only using clinical data from the first 24 hours, AUCs of 0.79, 0.80, and 0.77 were obtained for deceased, ventilated, or ICU admitted, respectively. Although respiration rate and SpO2 levels offered the highest feature importance, other canonical markers including diabetic history, age and temperature offered minimal gain. When lab values were incorporated, prediction of mortality benefited the most from blood urea nitrogen (BUN) and lactate dehydrogenase (LDH). Features predictive of morbidity included LDH, calcium, glucose, and C-reactive protein (CRP). Together this work summarizes efforts to systematically examine the importance of a wide range of features across different endpoint outcomes and at different hospitalization time points.
Language	English
Publishing date	2021-03-29
Publishing country	United States
Document type	Preprint
DOI	10.1101/2020.12.02.20235879
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Article ; Online: Predictive Modeling of Morbidity and Mortality in Patients Hospitalized With COVID-19 and its Clinical Implications: Algorithm Development and Interpretation.

Wang, Joshua M / Liu, Wenke / Chen, Xiaoshan / McRae, Michael P / McDevitt, John T / Fenyö, David

Journal of medical Internet research

2021 Volume 23, Issue 7, Page(s) e29514

Abstract: Background: The COVID-19 pandemic began in early 2021 and placed significant strains on health care systems worldwide. There remains a compelling need to analyze factors that are predictive for patients at elevated risk of morbidity and mortality.: ... ...

Abstract	Background: The COVID-19 pandemic began in early 2021 and placed significant strains on health care systems worldwide. There remains a compelling need to analyze factors that are predictive for patients at elevated risk of morbidity and mortality. Objective: The goal of this retrospective study of patients who tested positive with COVID-19 and were treated at NYU (New York University) Langone Health was to identify clinical markers predictive of disease severity in order to assist in clinical decision triage and to provide additional biological insights into disease progression. Methods: The clinical activity of 3740 patients at NYU Langone Hospital was obtained between January and August 2020; patient data were deidentified. Models were trained on clinical data during different parts of their hospital stay to predict three clinical outcomes: deceased, ventilated, or admitted to the intensive care unit (ICU). Results: The XGBoost (eXtreme Gradient Boosting) model that was trained on clinical data from the final 24 hours excelled at predicting mortality (area under the curve [AUC]=0.92; specificity=86%; and sensitivity=85%). Respiration rate was the most important feature, followed by SpO Conclusions: Together, this work summarizes efforts to systematically examine the importance of a wide range of features across different endpoint outcomes and at different hospitalization time points.
MeSH term(s)	Adolescent ; Adult ; Aged ; Algorithms ; Area Under Curve ; COVID-19/diagnosis ; COVID-19/mortality ; Child ; Child, Preschool ; Diabetes Mellitus ; Female ; Hospitalization ; Hospitals ; Humans ; Infant ; Infant, Newborn ; Intensive Care Units ; Male ; Middle Aged ; Morbidity ; New York City/epidemiology ; Pandemics ; Retrospective Studies ; SARS-CoV-2 ; Triage ; Young Adult
Language	English
Publishing date	2021-07-09
Publishing country	Canada
Document type	Journal Article
ZDB-ID	2028830-X
ISSN	1438-8871 ; 1439-4456
ISSN (online)	1438-8871
ISSN	1439-4456
DOI	10.2196/29514
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Article: Sensors that Learn: The Evolution from Taste Fingerprints to Patterns of Early Disease Detection.

Christodoulides, Nicolaos / McRae, Michael P / Simmons, Glennon W / Modak, Sayli S / McDevitt, John T

Micromachines

2019 Volume 10, Issue 4

Abstract: The McDevitt group has sustained efforts to develop a programmable sensing platform that offers advanced, multiplexed/multiclass chem-/bio-detection capabilities. This scalable chip-based platform has been optimized to service real-world biological ... ...

Abstract	The McDevitt group has sustained efforts to develop a programmable sensing platform that offers advanced, multiplexed/multiclass chem-/bio-detection capabilities. This scalable chip-based platform has been optimized to service real-world biological specimens and validated for analytical performance. Fashioned as a sensor that learns, the platform can host new content for the application at hand. Identification of biomarker-based fingerprints from complex mixtures has a direct linkage to e-nose and e-tongue research. Recently, we have moved to the point of big data acquisition alongside the linkage to machine learning and artificial intelligence. Here, exciting opportunities are afforded by multiparameter sensing that mimics the sense of taste, overcoming the limitations of salty, sweet, sour, bitter, and glutamate sensing and moving into fingerprints of health and wellness. This article summarizes developments related to the electronic taste chip system evolving into a platform that digitizes biology and affords clinical decision support tools. A dynamic body of literature and key review articles that have contributed to the shaping of these activities are also highlighted. This fully integrated sensor promises more rapid transition of biomarker panels into wide-spread clinical practice yielding valuable new insights into health diagnostics, benefiting early disease detection.
Language	English
Publishing date	2019-04-16
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2620864-7
ISSN	2072-666X
ISSN	2072-666X
DOI	10.3390/mi10040251
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Article ; Online: Simultaneous Quantitative SARS-CoV-2 Antigen and Host Antibody Detection and Pre-Screening Strategy at the Point of Care

Kritika Srinivasan Rajsri / Michael P. McRae / Nicolaos J. Christodoulides / Isaac Dapkins / Glennon W. Simmons / Hanover Matz / Helen Dooley / David Fenyö / John T. McDevitt

Bioengineering, Vol 10, Iss 670, p

2023 Volume 670

Abstract	As COVID-19 pandemic public health measures are easing globally, the emergence of new SARS-CoV-2 strains continue to present high risk for vulnerable populations. The antibody-mediated protection acquired from vaccination and/or infection is seen to wane over time and the immunocompromised populations can no longer expect benefit from monoclonal antibody prophylaxis. Hence, there is a need to monitor new variants and its effect on vaccine performance. In this context, surveillance of new SARS-CoV-2 infections and serology testing are gaining consensus for use as screening methods, especially for at-risk groups. Here, we described an improved COVID-19 screening strategy, comprising predictive algorithms and concurrent, rapid, accurate, and quantitative SARS-CoV-2 antigen and host antibody testing strategy, at point of care (POC). We conducted a retrospective analysis of 2553 pre- and asymptomatic patients who were tested for SARS-CoV-2 by RT-PCR. The pre-screening model had an AUC (CI) of 0.76 (0.73–0.78). Despite being the default method for screening, body temperature had lower AUC (0.52 [0.49–0.55]) compared to case incidence rate (0.65 [0.62–0.68]). POC assays for SARS-CoV-2 nucleocapsid protein (NP) and spike (S) receptor binding domain (RBD) IgG antibody showed promising preliminary results, demonstrating a convenient, rapid (<20 min), quantitative, and sensitive (ng/mL) antigen/antibody assay. This integrated pre-screening model and simultaneous antigen/antibody approach may significantly improve accuracy of COVID-19 infection and host immunity screening, helping address unmet needs for monitoring vaccine effectiveness and severe disease surveillance.
Keywords	artificial intelligence ; COVID-19 ; clinical decision making ; lab-on-a-chip ; nucleocapsid antigen ; spike RBD IgG ; Technology ; T ; Biology (General) ; QH301-705.5
Subject code	570
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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