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Physician agreement on the diagnosis of sepsis in the intensive care unit: estimation of concordance and analysis of underlying factors in a multicenter cohort
BACKGROUND: Differentiating sepsis from the systemic inflammatory response syndrome (SIRS) in critical care patients is challenging, especially before serious organ damage is evident, and with variable clinical presentations of patients and variable training and experience of attending physicians. O...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383290/ https://www.ncbi.nlm.nih.gov/pubmed/30828456 http://dx.doi.org/10.1186/s40560-019-0368-2 |
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author | Lopansri, Bert K. Miller III, Russell R. Burke, John P. Levy, Mitchell Opal, Steven Rothman, Richard E. D’Alessio, Franco R. Sidhaye, Venkataramana K. Balk, Robert Greenberg, Jared A. Yoder, Mark Patel, Gourang P. Gilbert, Emily Afshar, Majid Parada, Jorge P. Martin, Greg S. Esper, Annette M. Kempker, Jordan A. Narasimhan, Mangala Tsegaye, Adey Hahn, Stella Mayo, Paul McHugh, Leo Rapisarda, Antony Sampson, Dayle Brandon, Roslyn A. Seldon, Therese A. Yager, Thomas D. Brandon, Richard B. |
author_facet | Lopansri, Bert K. Miller III, Russell R. Burke, John P. Levy, Mitchell Opal, Steven Rothman, Richard E. D’Alessio, Franco R. Sidhaye, Venkataramana K. Balk, Robert Greenberg, Jared A. Yoder, Mark Patel, Gourang P. Gilbert, Emily Afshar, Majid Parada, Jorge P. Martin, Greg S. Esper, Annette M. Kempker, Jordan A. Narasimhan, Mangala Tsegaye, Adey Hahn, Stella Mayo, Paul McHugh, Leo Rapisarda, Antony Sampson, Dayle Brandon, Roslyn A. Seldon, Therese A. Yager, Thomas D. Brandon, Richard B. |
author_sort | Lopansri, Bert K. |
collection | PubMed |
description | BACKGROUND: Differentiating sepsis from the systemic inflammatory response syndrome (SIRS) in critical care patients is challenging, especially before serious organ damage is evident, and with variable clinical presentations of patients and variable training and experience of attending physicians. Our objective was to describe and quantify physician agreement in diagnosing SIRS or sepsis in critical care patients as a function of available clinical information, infection site, and hospital setting. METHODS: We conducted a post hoc analysis of previously collected data from a prospective, observational trial (N = 249 subjects) in intensive care units at seven US hospitals, in which physicians at different stages of patient care were asked to make diagnostic calls of either SIRS, sepsis, or indeterminate, based on varying amounts of available clinical information (clinicaltrials.gov identifier: NCT02127502). The overall percent agreement and the free-marginal, inter-observer agreement statistic kappa (κ(free)) were used to quantify agreement between evaluators (attending physicians, site investigators, external expert panelists). Logistic regression and machine learning techniques were used to search for significant variables that could explain heterogeneity within the indeterminate and SIRS patient subgroups. RESULTS: Free-marginal kappa decreased between the initial impression of the attending physician and (1) the initial impression of the site investigator (κ(free) 0.68), (2) the consensus discharge diagnosis of the site investigators (κ(free) 0.62), and (3) the consensus diagnosis of the external expert panel (κ(free) 0.58). In contrast, agreement was greatest between the consensus discharge impression of site investigators and the consensus diagnosis of the external expert panel (κ(free) 0.79). When stratified by infection site, κ(free) for agreement between initial and later diagnoses had a mean value + 0.24 (range − 0.29 to + 0.39) for respiratory infections, compared to + 0.70 (range + 0.42 to + 0.88) for abdominal + urinary + other infections. Bioinformatics analysis failed to clearly resolve the indeterminate diagnoses and also failed to explain why 60% of SIRS patients were treated with antibiotics. CONCLUSIONS: Considerable uncertainty surrounds the differential clinical diagnosis of sepsis vs. SIRS, especially before organ damage has become highly evident, and for patients presenting with respiratory clinical signs. Our findings underscore the need to provide physicians with accurate, timely diagnostic information in evaluating possible sepsis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40560-019-0368-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6383290 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63832902019-03-01 Physician agreement on the diagnosis of sepsis in the intensive care unit: estimation of concordance and analysis of underlying factors in a multicenter cohort Lopansri, Bert K. Miller III, Russell R. Burke, John P. Levy, Mitchell Opal, Steven Rothman, Richard E. D’Alessio, Franco R. Sidhaye, Venkataramana K. Balk, Robert Greenberg, Jared A. Yoder, Mark Patel, Gourang P. Gilbert, Emily Afshar, Majid Parada, Jorge P. Martin, Greg S. Esper, Annette M. Kempker, Jordan A. Narasimhan, Mangala Tsegaye, Adey Hahn, Stella Mayo, Paul McHugh, Leo Rapisarda, Antony Sampson, Dayle Brandon, Roslyn A. Seldon, Therese A. Yager, Thomas D. Brandon, Richard B. J Intensive Care Research BACKGROUND: Differentiating sepsis from the systemic inflammatory response syndrome (SIRS) in critical care patients is challenging, especially before serious organ damage is evident, and with variable clinical presentations of patients and variable training and experience of attending physicians. Our objective was to describe and quantify physician agreement in diagnosing SIRS or sepsis in critical care patients as a function of available clinical information, infection site, and hospital setting. METHODS: We conducted a post hoc analysis of previously collected data from a prospective, observational trial (N = 249 subjects) in intensive care units at seven US hospitals, in which physicians at different stages of patient care were asked to make diagnostic calls of either SIRS, sepsis, or indeterminate, based on varying amounts of available clinical information (clinicaltrials.gov identifier: NCT02127502). The overall percent agreement and the free-marginal, inter-observer agreement statistic kappa (κ(free)) were used to quantify agreement between evaluators (attending physicians, site investigators, external expert panelists). Logistic regression and machine learning techniques were used to search for significant variables that could explain heterogeneity within the indeterminate and SIRS patient subgroups. RESULTS: Free-marginal kappa decreased between the initial impression of the attending physician and (1) the initial impression of the site investigator (κ(free) 0.68), (2) the consensus discharge diagnosis of the site investigators (κ(free) 0.62), and (3) the consensus diagnosis of the external expert panel (κ(free) 0.58). In contrast, agreement was greatest between the consensus discharge impression of site investigators and the consensus diagnosis of the external expert panel (κ(free) 0.79). When stratified by infection site, κ(free) for agreement between initial and later diagnoses had a mean value + 0.24 (range − 0.29 to + 0.39) for respiratory infections, compared to + 0.70 (range + 0.42 to + 0.88) for abdominal + urinary + other infections. Bioinformatics analysis failed to clearly resolve the indeterminate diagnoses and also failed to explain why 60% of SIRS patients were treated with antibiotics. CONCLUSIONS: Considerable uncertainty surrounds the differential clinical diagnosis of sepsis vs. SIRS, especially before organ damage has become highly evident, and for patients presenting with respiratory clinical signs. Our findings underscore the need to provide physicians with accurate, timely diagnostic information in evaluating possible sepsis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40560-019-0368-2) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-21 /pmc/articles/PMC6383290/ /pubmed/30828456 http://dx.doi.org/10.1186/s40560-019-0368-2 Text en © The Author(s). 2019 Open AccessThis 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Lopansri, Bert K. Miller III, Russell R. Burke, John P. Levy, Mitchell Opal, Steven Rothman, Richard E. D’Alessio, Franco R. Sidhaye, Venkataramana K. Balk, Robert Greenberg, Jared A. Yoder, Mark Patel, Gourang P. Gilbert, Emily Afshar, Majid Parada, Jorge P. Martin, Greg S. Esper, Annette M. Kempker, Jordan A. Narasimhan, Mangala Tsegaye, Adey Hahn, Stella Mayo, Paul McHugh, Leo Rapisarda, Antony Sampson, Dayle Brandon, Roslyn A. Seldon, Therese A. Yager, Thomas D. Brandon, Richard B. Physician agreement on the diagnosis of sepsis in the intensive care unit: estimation of concordance and analysis of underlying factors in a multicenter cohort |
title | Physician agreement on the diagnosis of sepsis in the intensive care unit: estimation of concordance and analysis of underlying factors in a multicenter cohort |
title_full | Physician agreement on the diagnosis of sepsis in the intensive care unit: estimation of concordance and analysis of underlying factors in a multicenter cohort |
title_fullStr | Physician agreement on the diagnosis of sepsis in the intensive care unit: estimation of concordance and analysis of underlying factors in a multicenter cohort |
title_full_unstemmed | Physician agreement on the diagnosis of sepsis in the intensive care unit: estimation of concordance and analysis of underlying factors in a multicenter cohort |
title_short | Physician agreement on the diagnosis of sepsis in the intensive care unit: estimation of concordance and analysis of underlying factors in a multicenter cohort |
title_sort | physician agreement on the diagnosis of sepsis in the intensive care unit: estimation of concordance and analysis of underlying factors in a multicenter cohort |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383290/ https://www.ncbi.nlm.nih.gov/pubmed/30828456 http://dx.doi.org/10.1186/s40560-019-0368-2 |
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