Loading…

Biomarkers and predicting acute kidney injury

Aim How can we convert biomarkers into reliable, validated laboratory tests? Glomerular filtration rate (GFR) estimators exist for more than a century. The first utilitarian biomarkers were endogenously produced urea and creatinine. Clinicians then developed simple tests to determine whether or not...

Full description

Saved in:
Bibliographic Details
Published in:Acta Physiologica 2021-01, Vol.231 (1), p.e13479-n/a
Main Author: Luft, Friedrich C.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c3939-d755a0d6ae94b8466a17bc572f9a6e51c58f0789b61bc80e252d4308ba8a2e5f3
cites cdi_FETCH-LOGICAL-c3939-d755a0d6ae94b8466a17bc572f9a6e51c58f0789b61bc80e252d4308ba8a2e5f3
container_end_page n/a
container_issue 1
container_start_page e13479
container_title Acta Physiologica
container_volume 231
creator Luft, Friedrich C.
description Aim How can we convert biomarkers into reliable, validated laboratory tests? Glomerular filtration rate (GFR) estimators exist for more than a century. The first utilitarian biomarkers were endogenously produced urea and creatinine. Clinicians then developed simple tests to determine whether or not renal tubular function was maintained. Are there faster and better tests that reflect decreased renal function and increased acute kidney injury (AKI) risk? Methods We inspect earlier, and recently propagated biomarkers. Cystatin C reflects GFR and is not confounded by muscle mass. Direct GFR and plasma volume can now be measured acutely within 3 hours. Better yet would be tests that give information before GFR decreases and prior to urea, creatinine, and cystatin C increases. Prospective tests identifying those persons likely to develop AKI would be helpful. Even more utilitarian would be a test that also suggests a therapeutic avenue. Results A number of highly provocative biomarkers have recently been proposed. Moreover the application of big data from huge electronic medical records promise new directions in identifying and dealing with AKI. Conclusions Pipedreams are in the pipeline; the novel findings require immediate testing, verification, and perhaps application. Future research promises to make such dreams come true.
doi_str_mv 10.1111/apha.13479
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2393044512</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2393044512</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3939-d755a0d6ae94b8466a17bc572f9a6e51c58f0789b61bc80e252d4308ba8a2e5f3</originalsourceid><addsrcrecordid>eNp90E1LwzAYB_AgihtzFz-AFLyI0Jn3pMc5fIOBHvQc0jTVbF1bkxXptzezcwcP5pIcfvyfJ38AzhGcoXhudPuhZ4hQkR2BMRJUpkggfnx4QzkC0xBWEEKEo8P4FIwIJghJAscgvXXNRvu19SHRdZG03hbObF39nmjTbW2ydkVt-8TVq873Z-Ck1FWw0_09AW_3d6-Lx3T5_PC0mC9TQzKSpYVgTMOCa5vRXFLONRK5YQKXmeaWIcNkCYXMco5yI6HFDBeUQJlrqbFlJZmAqyG39c1nZ8NWbVwwtqp0bZsuKBzHQEoZwpFe_qGrpvN13E5hyjMuOYUwqutBGd-E4G2pWu_iv3uFoNr1qHY9qp8eI77YR3b5xhYH-ttaBGgAX66y_T9Rav7yOB9CvwHsrHqf</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2469686400</pqid></control><display><type>article</type><title>Biomarkers and predicting acute kidney injury</title><source>EBSCOhost SPORTDiscus with Full Text</source><source>Wiley-Blackwell Read &amp; Publish Collection</source><creator>Luft, Friedrich C.</creator><creatorcontrib>Luft, Friedrich C.</creatorcontrib><description>Aim How can we convert biomarkers into reliable, validated laboratory tests? Glomerular filtration rate (GFR) estimators exist for more than a century. The first utilitarian biomarkers were endogenously produced urea and creatinine. Clinicians then developed simple tests to determine whether or not renal tubular function was maintained. Are there faster and better tests that reflect decreased renal function and increased acute kidney injury (AKI) risk? Methods We inspect earlier, and recently propagated biomarkers. Cystatin C reflects GFR and is not confounded by muscle mass. Direct GFR and plasma volume can now be measured acutely within 3 hours. Better yet would be tests that give information before GFR decreases and prior to urea, creatinine, and cystatin C increases. Prospective tests identifying those persons likely to develop AKI would be helpful. Even more utilitarian would be a test that also suggests a therapeutic avenue. Results A number of highly provocative biomarkers have recently been proposed. Moreover the application of big data from huge electronic medical records promise new directions in identifying and dealing with AKI. Conclusions Pipedreams are in the pipeline; the novel findings require immediate testing, verification, and perhaps application. Future research promises to make such dreams come true.</description><identifier>ISSN: 1748-1708</identifier><identifier>EISSN: 1748-1716</identifier><identifier>DOI: 10.1111/apha.13479</identifier><identifier>PMID: 32311830</identifier><language>eng</language><publisher>England: Wiley Subscription Services, Inc</publisher><subject>acute kidney injury ; artificial intelligence ; Biomarkers ; Creatinine ; Cystatin C ; Electronic medical records ; Glomerular filtration rate ; Kidneys ; Renal function ; Urea</subject><ispartof>Acta Physiologica, 2021-01, Vol.231 (1), p.e13479-n/a</ispartof><rights>2020 The Authors. published by John Wiley &amp; Sons Ltd on behalf of Scandinavian Physiological Society</rights><rights>2020 The Authors. Acta Physiologica published by John Wiley &amp; Sons Ltd on behalf of Scandinavian Physiological Society.</rights><rights>2020. This article is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3939-d755a0d6ae94b8466a17bc572f9a6e51c58f0789b61bc80e252d4308ba8a2e5f3</citedby><cites>FETCH-LOGICAL-c3939-d755a0d6ae94b8466a17bc572f9a6e51c58f0789b61bc80e252d4308ba8a2e5f3</cites><orcidid>0000-0002-8635-1199</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32311830$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Luft, Friedrich C.</creatorcontrib><title>Biomarkers and predicting acute kidney injury</title><title>Acta Physiologica</title><addtitle>Acta Physiol (Oxf)</addtitle><description>Aim How can we convert biomarkers into reliable, validated laboratory tests? Glomerular filtration rate (GFR) estimators exist for more than a century. The first utilitarian biomarkers were endogenously produced urea and creatinine. Clinicians then developed simple tests to determine whether or not renal tubular function was maintained. Are there faster and better tests that reflect decreased renal function and increased acute kidney injury (AKI) risk? Methods We inspect earlier, and recently propagated biomarkers. Cystatin C reflects GFR and is not confounded by muscle mass. Direct GFR and plasma volume can now be measured acutely within 3 hours. Better yet would be tests that give information before GFR decreases and prior to urea, creatinine, and cystatin C increases. Prospective tests identifying those persons likely to develop AKI would be helpful. Even more utilitarian would be a test that also suggests a therapeutic avenue. Results A number of highly provocative biomarkers have recently been proposed. Moreover the application of big data from huge electronic medical records promise new directions in identifying and dealing with AKI. Conclusions Pipedreams are in the pipeline; the novel findings require immediate testing, verification, and perhaps application. Future research promises to make such dreams come true.</description><subject>acute kidney injury</subject><subject>artificial intelligence</subject><subject>Biomarkers</subject><subject>Creatinine</subject><subject>Cystatin C</subject><subject>Electronic medical records</subject><subject>Glomerular filtration rate</subject><subject>Kidneys</subject><subject>Renal function</subject><subject>Urea</subject><issn>1748-1708</issn><issn>1748-1716</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp90E1LwzAYB_AgihtzFz-AFLyI0Jn3pMc5fIOBHvQc0jTVbF1bkxXptzezcwcP5pIcfvyfJ38AzhGcoXhudPuhZ4hQkR2BMRJUpkggfnx4QzkC0xBWEEKEo8P4FIwIJghJAscgvXXNRvu19SHRdZG03hbObF39nmjTbW2ydkVt-8TVq873Z-Ck1FWw0_09AW_3d6-Lx3T5_PC0mC9TQzKSpYVgTMOCa5vRXFLONRK5YQKXmeaWIcNkCYXMco5yI6HFDBeUQJlrqbFlJZmAqyG39c1nZ8NWbVwwtqp0bZsuKBzHQEoZwpFe_qGrpvN13E5hyjMuOYUwqutBGd-E4G2pWu_iv3uFoNr1qHY9qp8eI77YR3b5xhYH-ttaBGgAX66y_T9Rav7yOB9CvwHsrHqf</recordid><startdate>202101</startdate><enddate>202101</enddate><creator>Luft, Friedrich C.</creator><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TK</scope><scope>7TS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-8635-1199</orcidid></search><sort><creationdate>202101</creationdate><title>Biomarkers and predicting acute kidney injury</title><author>Luft, Friedrich C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3939-d755a0d6ae94b8466a17bc572f9a6e51c58f0789b61bc80e252d4308ba8a2e5f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>acute kidney injury</topic><topic>artificial intelligence</topic><topic>Biomarkers</topic><topic>Creatinine</topic><topic>Cystatin C</topic><topic>Electronic medical records</topic><topic>Glomerular filtration rate</topic><topic>Kidneys</topic><topic>Renal function</topic><topic>Urea</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Luft, Friedrich C.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley-Blackwell Free Backfiles(OpenAccess)</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Neurosciences Abstracts</collection><collection>Physical Education Index</collection><collection>MEDLINE - Academic</collection><jtitle>Acta Physiologica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Luft, Friedrich C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Biomarkers and predicting acute kidney injury</atitle><jtitle>Acta Physiologica</jtitle><addtitle>Acta Physiol (Oxf)</addtitle><date>2021-01</date><risdate>2021</risdate><volume>231</volume><issue>1</issue><spage>e13479</spage><epage>n/a</epage><pages>e13479-n/a</pages><issn>1748-1708</issn><eissn>1748-1716</eissn><abstract>Aim How can we convert biomarkers into reliable, validated laboratory tests? Glomerular filtration rate (GFR) estimators exist for more than a century. The first utilitarian biomarkers were endogenously produced urea and creatinine. Clinicians then developed simple tests to determine whether or not renal tubular function was maintained. Are there faster and better tests that reflect decreased renal function and increased acute kidney injury (AKI) risk? Methods We inspect earlier, and recently propagated biomarkers. Cystatin C reflects GFR and is not confounded by muscle mass. Direct GFR and plasma volume can now be measured acutely within 3 hours. Better yet would be tests that give information before GFR decreases and prior to urea, creatinine, and cystatin C increases. Prospective tests identifying those persons likely to develop AKI would be helpful. Even more utilitarian would be a test that also suggests a therapeutic avenue. Results A number of highly provocative biomarkers have recently been proposed. Moreover the application of big data from huge electronic medical records promise new directions in identifying and dealing with AKI. Conclusions Pipedreams are in the pipeline; the novel findings require immediate testing, verification, and perhaps application. Future research promises to make such dreams come true.</abstract><cop>England</cop><pub>Wiley Subscription Services, Inc</pub><pmid>32311830</pmid><doi>10.1111/apha.13479</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-8635-1199</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1748-1708
ispartof Acta Physiologica, 2021-01, Vol.231 (1), p.e13479-n/a
issn 1748-1708
1748-1716
language eng
recordid cdi_proquest_miscellaneous_2393044512
source EBSCOhost SPORTDiscus with Full Text; Wiley-Blackwell Read & Publish Collection
subjects acute kidney injury
artificial intelligence
Biomarkers
Creatinine
Cystatin C
Electronic medical records
Glomerular filtration rate
Kidneys
Renal function
Urea
title Biomarkers and predicting acute kidney injury
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T19%3A45%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Biomarkers%20and%20predicting%20acute%20kidney%20injury&rft.jtitle=Acta%20Physiologica&rft.au=Luft,%20Friedrich%20C.&rft.date=2021-01&rft.volume=231&rft.issue=1&rft.spage=e13479&rft.epage=n/a&rft.pages=e13479-n/a&rft.issn=1748-1708&rft.eissn=1748-1716&rft_id=info:doi/10.1111/apha.13479&rft_dat=%3Cproquest_cross%3E2393044512%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c3939-d755a0d6ae94b8466a17bc572f9a6e51c58f0789b61bc80e252d4308ba8a2e5f3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2469686400&rft_id=info:pmid/32311830&rfr_iscdi=true