Predicting acute kidney injury: current status and future challenges
Acute kidney injury (AKI) is characterized by an acute decline in renal function and is associated to increased mortality rate, hospitalization time, and total health-related costs. The severity of this ‘fearsome’ clinical complication might depend on, or even be worsened by, the late detection of A...
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| Veröffentlicht in: | Journal of nephrology 2018-04, Vol.31 (2), p.209-223 |
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| container_title | Journal of nephrology |
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| creator | Pozzoli, Simona Simonini, Marco Manunta, Paolo |
| description | Acute kidney injury (AKI) is characterized by an acute decline in renal function and is associated to increased mortality rate, hospitalization time, and total health-related costs. The severity of this ‘fearsome’ clinical complication might depend on, or even be worsened by, the late detection of AKI, when the diagnosis is based on the elevation of serum creatinine (SCr). For these reasons, in recent years a great number of new tools, biomarkers and predictive models have been proposed to clinicians in order to improve diagnosis and prevent the development of AKI. The purpose of this narrative paper is to review the current state of the art in prediction and early detection of AKI and outline future challenges. |
| doi_str_mv | 10.1007/s40620-017-0416-8 |
| format | Article |
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The severity of this ‘fearsome’ clinical complication might depend on, or even be worsened by, the late detection of AKI, when the diagnosis is based on the elevation of serum creatinine (SCr). For these reasons, in recent years a great number of new tools, biomarkers and predictive models have been proposed to clinicians in order to improve diagnosis and prevent the development of AKI. 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The severity of this ‘fearsome’ clinical complication might depend on, or even be worsened by, the late detection of AKI, when the diagnosis is based on the elevation of serum creatinine (SCr). For these reasons, in recent years a great number of new tools, biomarkers and predictive models have been proposed to clinicians in order to improve diagnosis and prevent the development of AKI. 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Simonini, Marco ; Manunta, Paolo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c442t-2344f21682eb092e122a21b15d5f8e754efbdda68fa554d49601f45a23bd98653</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Acute Kidney Injury - blood</topic><topic>Acute Kidney Injury - complications</topic><topic>Acute Kidney Injury - diagnosis</topic><topic>Acute Kidney Injury - genetics</topic><topic>Biomarkers - blood</topic><topic>Cystatin C - blood</topic><topic>Early Diagnosis</topic><topic>Fatty Acid-Binding Proteins - blood</topic><topic>Genetic Predisposition to Disease</topic><topic>Genomics</topic><topic>Hepatitis A Virus Cellular Receptor 1 - blood</topic><topic>Humans</topic><topic>Insulin-Like Growth Factor Binding Proteins - blood</topic><topic>Interleukin-18 - blood</topic><topic>Kidney Function Tests</topic><topic>Lipocalin-2 - blood</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Models, Biological</topic><topic>Nephrology</topic><topic>Ouabain - blood</topic><topic>Renal Insufficiency, Chronic - blood</topic><topic>Renal Insufficiency, Chronic - etiology</topic><topic>Review</topic><topic>Risk Factors</topic><topic>Severity of Illness Index</topic><topic>Tissue Inhibitor of Metalloproteinase-2 - blood</topic><topic>Urology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pozzoli, Simona</creatorcontrib><creatorcontrib>Simonini, Marco</creatorcontrib><creatorcontrib>Manunta, Paolo</creatorcontrib><collection>Springer Nature OA/Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of nephrology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pozzoli, Simona</au><au>Simonini, Marco</au><au>Manunta, Paolo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting acute kidney injury: current status and future challenges</atitle><jtitle>Journal of nephrology</jtitle><stitle>J Nephrol</stitle><addtitle>J Nephrol</addtitle><date>2018-04-01</date><risdate>2018</risdate><volume>31</volume><issue>2</issue><spage>209</spage><epage>223</epage><pages>209-223</pages><issn>1121-8428</issn><eissn>1724-6059</eissn><abstract>Acute kidney injury (AKI) is characterized by an acute decline in renal function and is associated to increased mortality rate, hospitalization time, and total health-related costs. The severity of this ‘fearsome’ clinical complication might depend on, or even be worsened by, the late detection of AKI, when the diagnosis is based on the elevation of serum creatinine (SCr). For these reasons, in recent years a great number of new tools, biomarkers and predictive models have been proposed to clinicians in order to improve diagnosis and prevent the development of AKI. The purpose of this narrative paper is to review the current state of the art in prediction and early detection of AKI and outline future challenges.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>28624882</pmid><doi>10.1007/s40620-017-0416-8</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of nephrology, 2018-04, Vol.31 (2), p.209-223 |
| issn | 1121-8428 1724-6059 |
| language | eng |
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| source | MEDLINE; Springer Online Journals Complete |
| subjects | Acute Kidney Injury - blood Acute Kidney Injury - complications Acute Kidney Injury - diagnosis Acute Kidney Injury - genetics Biomarkers - blood Cystatin C - blood Early Diagnosis Fatty Acid-Binding Proteins - blood Genetic Predisposition to Disease Genomics Hepatitis A Virus Cellular Receptor 1 - blood Humans Insulin-Like Growth Factor Binding Proteins - blood Interleukin-18 - blood Kidney Function Tests Lipocalin-2 - blood Medicine Medicine & Public Health Models, Biological Nephrology Ouabain - blood Renal Insufficiency, Chronic - blood Renal Insufficiency, Chronic - etiology Review Risk Factors Severity of Illness Index Tissue Inhibitor of Metalloproteinase-2 - blood Urology |
| title | Predicting acute kidney injury: current status and future challenges |
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