Cargando…
Prediction of presence of kidney disease in patients undergoing intravenous iodinated contrast enhanced computed tomography: a validation study
OBJECTIVES: To validate two previously presented models containing risk factors to identify patients with estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m(2) or eGFR <45 ml/min/1.73 m(2). METHODS: In random patients undergoing intravenous contrast-enhanced computed tomography (CEC...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5334394/ https://www.ncbi.nlm.nih.gov/pubmed/27436026 http://dx.doi.org/10.1007/s00330-016-4478-0 |
_version_ | 1782511844412358656 |
---|---|
author | Schreuder, Sanne M. Stoker, Jaap Bipat, Shandra |
author_facet | Schreuder, Sanne M. Stoker, Jaap Bipat, Shandra |
author_sort | Schreuder, Sanne M. |
collection | PubMed |
description | OBJECTIVES: To validate two previously presented models containing risk factors to identify patients with estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m(2) or eGFR <45 ml/min/1.73 m(2). METHODS: In random patients undergoing intravenous contrast-enhanced computed tomography (CECT) the following risk factors were assessed: history of urological/nephrological disease, hypertension, diabetes mellitus, anaemia, congestive heart failure, other cardiovascular disease or multiple myeloma or Waldenström disease. Data on kidney function, age, gender and type and indication of CECT were also registered. We studied two models: model A—diabetes mellitus, history of urological/nephrological disease, cardiovascular disease, hypertension; model B—diabetes mellitus, history of urological/nephrological disease, age >75 years and congestive heart failure. For each model, associations with eGFR <60 ml/min/1.73 m(2) or eGFR <45 ml/min/1.73 m(2) was studied. RESULTS: A total of 1,001 patients, mean age 60.36 years were included. In total, 92 (9.2 %) patients had an eGFR <60 ml/min/1.73 m(2) and 11 (1.1 %) patients an eGFR <45 ml/min/1.73 m(2). Model A detected 543 patients: 81 with eGFR <60 ml/min/1.73 m(2) (missing 11) and all 11 with eGFR <45 ml/min/1.73 m(2). Model B detected 420 patients: 70 (missing 22) with eGFR <60 ml/min/1.73 m(2) and all 11 with eGFR <45 ml/min/1.73 m(2). Associations were significant (p < 0.05). CONCLUSIONS: Model B resulted in the lowest superfluous eGFR measurements while detecting all patients with eGFR <45 ml/min/1.73 m(2) and nearly all with eGFR <60 ml/min/1.73 m(2). KEY POINTS: • Less than 10% of patients undergoing contrast-enhanced CT have an eGFR of <60ml/min/1.73m (2) • Four risk factors can be used to detect pre-existent kidney disease • It is safe to reduce eGFR measurements using a four-risk-factor model ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00330-016-4478-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5334394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-53343942017-03-15 Prediction of presence of kidney disease in patients undergoing intravenous iodinated contrast enhanced computed tomography: a validation study Schreuder, Sanne M. Stoker, Jaap Bipat, Shandra Eur Radiol Computed Tomography OBJECTIVES: To validate two previously presented models containing risk factors to identify patients with estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m(2) or eGFR <45 ml/min/1.73 m(2). METHODS: In random patients undergoing intravenous contrast-enhanced computed tomography (CECT) the following risk factors were assessed: history of urological/nephrological disease, hypertension, diabetes mellitus, anaemia, congestive heart failure, other cardiovascular disease or multiple myeloma or Waldenström disease. Data on kidney function, age, gender and type and indication of CECT were also registered. We studied two models: model A—diabetes mellitus, history of urological/nephrological disease, cardiovascular disease, hypertension; model B—diabetes mellitus, history of urological/nephrological disease, age >75 years and congestive heart failure. For each model, associations with eGFR <60 ml/min/1.73 m(2) or eGFR <45 ml/min/1.73 m(2) was studied. RESULTS: A total of 1,001 patients, mean age 60.36 years were included. In total, 92 (9.2 %) patients had an eGFR <60 ml/min/1.73 m(2) and 11 (1.1 %) patients an eGFR <45 ml/min/1.73 m(2). Model A detected 543 patients: 81 with eGFR <60 ml/min/1.73 m(2) (missing 11) and all 11 with eGFR <45 ml/min/1.73 m(2). Model B detected 420 patients: 70 (missing 22) with eGFR <60 ml/min/1.73 m(2) and all 11 with eGFR <45 ml/min/1.73 m(2). Associations were significant (p < 0.05). CONCLUSIONS: Model B resulted in the lowest superfluous eGFR measurements while detecting all patients with eGFR <45 ml/min/1.73 m(2) and nearly all with eGFR <60 ml/min/1.73 m(2). KEY POINTS: • Less than 10% of patients undergoing contrast-enhanced CT have an eGFR of <60ml/min/1.73m (2) • Four risk factors can be used to detect pre-existent kidney disease • It is safe to reduce eGFR measurements using a four-risk-factor model ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00330-016-4478-0) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2016-07-19 2017 /pmc/articles/PMC5334394/ /pubmed/27436026 http://dx.doi.org/10.1007/s00330-016-4478-0 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Computed Tomography Schreuder, Sanne M. Stoker, Jaap Bipat, Shandra Prediction of presence of kidney disease in patients undergoing intravenous iodinated contrast enhanced computed tomography: a validation study |
title | Prediction of presence of kidney disease in patients undergoing intravenous iodinated contrast enhanced computed tomography: a validation study |
title_full | Prediction of presence of kidney disease in patients undergoing intravenous iodinated contrast enhanced computed tomography: a validation study |
title_fullStr | Prediction of presence of kidney disease in patients undergoing intravenous iodinated contrast enhanced computed tomography: a validation study |
title_full_unstemmed | Prediction of presence of kidney disease in patients undergoing intravenous iodinated contrast enhanced computed tomography: a validation study |
title_short | Prediction of presence of kidney disease in patients undergoing intravenous iodinated contrast enhanced computed tomography: a validation study |
title_sort | prediction of presence of kidney disease in patients undergoing intravenous iodinated contrast enhanced computed tomography: a validation study |
topic | Computed Tomography |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5334394/ https://www.ncbi.nlm.nih.gov/pubmed/27436026 http://dx.doi.org/10.1007/s00330-016-4478-0 |
work_keys_str_mv | AT schreudersannem predictionofpresenceofkidneydiseaseinpatientsundergoingintravenousiodinatedcontrastenhancedcomputedtomographyavalidationstudy AT stokerjaap predictionofpresenceofkidneydiseaseinpatientsundergoingintravenousiodinatedcontrastenhancedcomputedtomographyavalidationstudy AT bipatshandra predictionofpresenceofkidneydiseaseinpatientsundergoingintravenousiodinatedcontrastenhancedcomputedtomographyavalidationstudy |