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Making it possible to measure knowledge, experience and intuition in diagnosing lung injury severity: a fuzzy logic vision based on the Murray score

BACKGROUND: Murray score is the result of an equation that gives all its variables the same linear contribution and weight and makes use of consented cut-offs. Everyday physicians' vocabulary is full of terms (adjectives) like: little, small, low, high, etc. that they handle in an intuitive and...

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Autores principales: D'Negri, Carlos E, De Vito, Eduardo L
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2991274/
https://www.ncbi.nlm.nih.gov/pubmed/21050478
http://dx.doi.org/10.1186/1472-6947-10-70
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author D'Negri, Carlos E
De Vito, Eduardo L
author_facet D'Negri, Carlos E
De Vito, Eduardo L
author_sort D'Negri, Carlos E
collection PubMed
description BACKGROUND: Murray score is the result of an equation that gives all its variables the same linear contribution and weight and makes use of consented cut-offs. Everyday physicians' vocabulary is full of terms (adjectives) like: little, small, low, high, etc. that they handle in an intuitive and not always linear way to make therapeutic decisions. The purpose of this paper is to develop a fuzzy logic (FL) vision of Murray's score variables to enable the measurement of physicians' knowledge, experience and intuition in diagnosing lung injury and test if they followed Murray's equation predictions. METHODS: For a prospective survey carried out among a team of professionals (aged 29 to 53) in a University Hospital Intensive Care Unit, twelve physicians filled in two questionnaires. In the first one they had to define the ranks which should be categorized as normal, moderate and severe for three of four Murray variables. In another questionnaire, which represented all probable combinations of those categories, they had to tick the pulmonary condition as: no injury, mild, moderate, and ARDS. This procedure gave rise to a Fuzzy Inference System designed to provide the degree of severity as sensed by the group. RESULTS: The survey showed fuzzy frontiers for the categories and fuzzy diagnosis. In all, 45% of the hypothetical patients (n 18,013) were equally diagnosed by the survey and Murray's equation, whereas another 51% was overestimated in one level by the survey. Physicians agreed with 96.5% of ARDS cases according to Murray's test but only 11.6% of its mild cases were equally diagnosed by the survey. Nonlinearity of the survey reasoning (high relevance to gas exchange and chest film) was apparent. CONCLUSIONS: The contiguous categories of the variables confirm the existence of fuzzy frontiers. An overestimation was found in the surveyed group's interpretation of severity. This overestimation was mainly due to the different weight assigned to PO(2)/FiO(2 )and chest film variables. The FL approach made it possible to measure knowledge, experience and intuition as they appear in physicians' thinking. FL methodology could overcome a series of restrictions that current tests have due to cut-offs
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spelling pubmed-29912742010-11-25 Making it possible to measure knowledge, experience and intuition in diagnosing lung injury severity: a fuzzy logic vision based on the Murray score D'Negri, Carlos E De Vito, Eduardo L BMC Med Inform Decis Mak Research Article BACKGROUND: Murray score is the result of an equation that gives all its variables the same linear contribution and weight and makes use of consented cut-offs. Everyday physicians' vocabulary is full of terms (adjectives) like: little, small, low, high, etc. that they handle in an intuitive and not always linear way to make therapeutic decisions. The purpose of this paper is to develop a fuzzy logic (FL) vision of Murray's score variables to enable the measurement of physicians' knowledge, experience and intuition in diagnosing lung injury and test if they followed Murray's equation predictions. METHODS: For a prospective survey carried out among a team of professionals (aged 29 to 53) in a University Hospital Intensive Care Unit, twelve physicians filled in two questionnaires. In the first one they had to define the ranks which should be categorized as normal, moderate and severe for three of four Murray variables. In another questionnaire, which represented all probable combinations of those categories, they had to tick the pulmonary condition as: no injury, mild, moderate, and ARDS. This procedure gave rise to a Fuzzy Inference System designed to provide the degree of severity as sensed by the group. RESULTS: The survey showed fuzzy frontiers for the categories and fuzzy diagnosis. In all, 45% of the hypothetical patients (n 18,013) were equally diagnosed by the survey and Murray's equation, whereas another 51% was overestimated in one level by the survey. Physicians agreed with 96.5% of ARDS cases according to Murray's test but only 11.6% of its mild cases were equally diagnosed by the survey. Nonlinearity of the survey reasoning (high relevance to gas exchange and chest film) was apparent. CONCLUSIONS: The contiguous categories of the variables confirm the existence of fuzzy frontiers. An overestimation was found in the surveyed group's interpretation of severity. This overestimation was mainly due to the different weight assigned to PO(2)/FiO(2 )and chest film variables. The FL approach made it possible to measure knowledge, experience and intuition as they appear in physicians' thinking. FL methodology could overcome a series of restrictions that current tests have due to cut-offs BioMed Central 2010-11-04 /pmc/articles/PMC2991274/ /pubmed/21050478 http://dx.doi.org/10.1186/1472-6947-10-70 Text en Copyright ©2010 D'Negri and De Vito; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
D'Negri, Carlos E
De Vito, Eduardo L
Making it possible to measure knowledge, experience and intuition in diagnosing lung injury severity: a fuzzy logic vision based on the Murray score
title Making it possible to measure knowledge, experience and intuition in diagnosing lung injury severity: a fuzzy logic vision based on the Murray score
title_full Making it possible to measure knowledge, experience and intuition in diagnosing lung injury severity: a fuzzy logic vision based on the Murray score
title_fullStr Making it possible to measure knowledge, experience and intuition in diagnosing lung injury severity: a fuzzy logic vision based on the Murray score
title_full_unstemmed Making it possible to measure knowledge, experience and intuition in diagnosing lung injury severity: a fuzzy logic vision based on the Murray score
title_short Making it possible to measure knowledge, experience and intuition in diagnosing lung injury severity: a fuzzy logic vision based on the Murray score
title_sort making it possible to measure knowledge, experience and intuition in diagnosing lung injury severity: a fuzzy logic vision based on the murray score
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2991274/
https://www.ncbi.nlm.nih.gov/pubmed/21050478
http://dx.doi.org/10.1186/1472-6947-10-70
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