Nynke Wijbenga, Marjolein M Muller, Rogier A S Hoek, Bas J Mathot, Leonard Seghers, Joachim G J V Aerts, Brenda C M de Winter, Daniel Bos, Olivier C Manintveld, Merel E Hellemons
{"title":"Diagnostic accuracy of eNose 'breathprints' for therapeutic drug monitoring of Tacrolimus trough levels in lung transplantation.","authors":"Nynke Wijbenga, Marjolein M Muller, Rogier A S Hoek, Bas J Mathot, Leonard Seghers, Joachim G J V Aerts, Brenda C M de Winter, Daniel Bos, Olivier C Manintveld, Merel E Hellemons","doi":"10.1088/1752-7163/acf066","DOIUrl":null,"url":null,"abstract":"<p><p>In order to prevent long-term immunity-related complications after lung transplantation, close monitoring of immunosuppressant levels using therapeutic drug monitoring (TDM) is paramount. Novel electronic nose (eNose) technology may be a non-invasive alternative to the current invasive procedures for TDM. We investigated the diagnostic and categorization capacity of eNose breathprints for Tacrolimus trough blood plasma levels (TAC<sub>trough</sub>) in lung transplant recipients (LTRs). We performed eNose measurements in stable LTR attending the outpatient clinic. We evaluated (1) the correlation between eNose measurements and TAC<sub>trough</sub>, (2) the diagnostic capacity of eNose technology for TAC<sub>trough</sub>, and (3) the accuracy of eNose technology for categorization of TAC<sub>trough</sub>into three clinically relevant categories (low: <7<i>µ</i>g ml<sup>-1</sup>, medium: 7-10<i>µ</i>g ml<sup>-1</sup>, and high: >10<i>µ</i>g ml<sup>-1</sup>). A total of 186 measurements from 86 LTR were included. There was a weak but statistically significant correlation (<i>r</i>= 0.21,<i>p</i>= 0.004) between the eNose measurements and TAC<sub>trough</sub>. The root mean squared error of prediction for the diagnostic capacity was 3.186 in the training and 3.131 in the validation set. The accuracy of categorization ranged between 45%-63% for the training set and 52%-69% in the validation set. There is a weak correlation between eNose breathprints and TAC<sub>trough</sub>in LTR. However, the diagnostic as well as categorization capacity for TAC<sub>trough</sub>using eNose breathprints is too inaccurate to be applicable in TDM.</p>","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":"17 4","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of breath research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1088/1752-7163/acf066","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
In order to prevent long-term immunity-related complications after lung transplantation, close monitoring of immunosuppressant levels using therapeutic drug monitoring (TDM) is paramount. Novel electronic nose (eNose) technology may be a non-invasive alternative to the current invasive procedures for TDM. We investigated the diagnostic and categorization capacity of eNose breathprints for Tacrolimus trough blood plasma levels (TACtrough) in lung transplant recipients (LTRs). We performed eNose measurements in stable LTR attending the outpatient clinic. We evaluated (1) the correlation between eNose measurements and TACtrough, (2) the diagnostic capacity of eNose technology for TACtrough, and (3) the accuracy of eNose technology for categorization of TACtroughinto three clinically relevant categories (low: <7µg ml-1, medium: 7-10µg ml-1, and high: >10µg ml-1). A total of 186 measurements from 86 LTR were included. There was a weak but statistically significant correlation (r= 0.21,p= 0.004) between the eNose measurements and TACtrough. The root mean squared error of prediction for the diagnostic capacity was 3.186 in the training and 3.131 in the validation set. The accuracy of categorization ranged between 45%-63% for the training set and 52%-69% in the validation set. There is a weak correlation between eNose breathprints and TACtroughin LTR. However, the diagnostic as well as categorization capacity for TACtroughusing eNose breathprints is too inaccurate to be applicable in TDM.
期刊介绍:
Journal of Breath Research is dedicated to all aspects of scientific breath research. The traditional focus is on analysis of volatile compounds and aerosols in exhaled breath for the investigation of exogenous exposures, metabolism, toxicology, health status and the diagnosis of disease and breath odours. The journal also welcomes other breath-related topics.
Typical areas of interest include:
Big laboratory instrumentation: describing new state-of-the-art analytical instrumentation capable of performing high-resolution discovery and targeted breath research; exploiting complex technologies drawn from other areas of biochemistry and genetics for breath research.
Engineering solutions: developing new breath sampling technologies for condensate and aerosols, for chemical and optical sensors, for extraction and sample preparation methods, for automation and standardization, and for multiplex analyses to preserve the breath matrix and facilitating analytical throughput. Measure exhaled constituents (e.g. CO2, acetone, isoprene) as markers of human presence or mitigate such contaminants in enclosed environments.
Human and animal in vivo studies: decoding the ''breath exposome'', implementing exposure and intervention studies, performing cross-sectional and case-control research, assaying immune and inflammatory response, and testing mammalian host response to infections and exogenous exposures to develop information directly applicable to systems biology. Studying inhalation toxicology; inhaled breath as a source of internal dose; resultant blood, breath and urinary biomarkers linked to inhalation pathway.
Cellular and molecular level in vitro studies.
Clinical, pharmacological and forensic applications.
Mathematical, statistical and graphical data interpretation.