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Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time

BACKGROUND: Laser-Doppler imaging (LDI) of cutaneous blood flow is beginning to be used by burn surgeons to predict the healing time of burn wounds; predicted healing time is used to determine wound treatment as either dressings or surgery. In this paper, we do a statistical analysis of the performa...

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Autores principales: Baker, Rose D, Weinand, Christian, Jeng, James C, Hoeksema, Henk, Monstrey, Stan, Pape, Sarah A, Spence, Robert, Wilson, David
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2680202/
https://www.ncbi.nlm.nih.gov/pubmed/19220885
http://dx.doi.org/10.1186/1471-2288-9-11
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author Baker, Rose D
Weinand, Christian
Jeng, James C
Hoeksema, Henk
Monstrey, Stan
Pape, Sarah A
Spence, Robert
Wilson, David
author_facet Baker, Rose D
Weinand, Christian
Jeng, James C
Hoeksema, Henk
Monstrey, Stan
Pape, Sarah A
Spence, Robert
Wilson, David
author_sort Baker, Rose D
collection PubMed
description BACKGROUND: Laser-Doppler imaging (LDI) of cutaneous blood flow is beginning to be used by burn surgeons to predict the healing time of burn wounds; predicted healing time is used to determine wound treatment as either dressings or surgery. In this paper, we do a statistical analysis of the performance of the technique. METHODS: We used data from a study carried out by five burn centers: LDI was done once between days 2 to 5 post burn, and healing was assessed at both 14 days and 21 days post burn. Random-effects ordinal logistic regression and other models such as the continuation ratio model were used to model healing-time as a function of the LDI data, and of demographic and wound history variables. Statistical methods were also used to study the false-color palette, which enables the laser-Doppler imager to be used by clinicians as a decision-support tool. RESULTS: Overall performance is that diagnoses are over 90% correct. Related questions addressed were what was the best blood flow summary statistic and whether, given the blood flow measurements, demographic and observational variables had any additional predictive power (age, sex, race, % total body surface area burned (%TBSA), site and cause of burn, day of LDI scan, burn center). It was found that mean laser-Doppler flux over a wound area was the best statistic, and that, given the same mean flux, women recover slightly more slowly than men. Further, the likely degradation in predictive performance on moving to a patient group with larger %TBSA than those in the data sample was studied, and shown to be small. CONCLUSION: Modeling healing time is a complex statistical problem, with random effects due to multiple burn areas per individual, and censoring caused by patients missing hospital visits and undergoing surgery. This analysis applies state-of-the art statistical methods such as the bootstrap and permutation tests to a medical problem of topical interest. New medical findings are that age and %TBSA are not important predictors of healing time when the LDI results are known, whereas gender does influence recovery time, even when blood flow is controlled for. The conclusion regarding the palette is that an optimum three-color palette can be chosen 'automatically', but the optimum choice of a 5-color palette cannot be made solely by optimizing the percentage of correct diagnoses.
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spelling pubmed-26802022009-05-12 Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time Baker, Rose D Weinand, Christian Jeng, James C Hoeksema, Henk Monstrey, Stan Pape, Sarah A Spence, Robert Wilson, David BMC Med Res Methodol Research Article BACKGROUND: Laser-Doppler imaging (LDI) of cutaneous blood flow is beginning to be used by burn surgeons to predict the healing time of burn wounds; predicted healing time is used to determine wound treatment as either dressings or surgery. In this paper, we do a statistical analysis of the performance of the technique. METHODS: We used data from a study carried out by five burn centers: LDI was done once between days 2 to 5 post burn, and healing was assessed at both 14 days and 21 days post burn. Random-effects ordinal logistic regression and other models such as the continuation ratio model were used to model healing-time as a function of the LDI data, and of demographic and wound history variables. Statistical methods were also used to study the false-color palette, which enables the laser-Doppler imager to be used by clinicians as a decision-support tool. RESULTS: Overall performance is that diagnoses are over 90% correct. Related questions addressed were what was the best blood flow summary statistic and whether, given the blood flow measurements, demographic and observational variables had any additional predictive power (age, sex, race, % total body surface area burned (%TBSA), site and cause of burn, day of LDI scan, burn center). It was found that mean laser-Doppler flux over a wound area was the best statistic, and that, given the same mean flux, women recover slightly more slowly than men. Further, the likely degradation in predictive performance on moving to a patient group with larger %TBSA than those in the data sample was studied, and shown to be small. CONCLUSION: Modeling healing time is a complex statistical problem, with random effects due to multiple burn areas per individual, and censoring caused by patients missing hospital visits and undergoing surgery. This analysis applies state-of-the art statistical methods such as the bootstrap and permutation tests to a medical problem of topical interest. New medical findings are that age and %TBSA are not important predictors of healing time when the LDI results are known, whereas gender does influence recovery time, even when blood flow is controlled for. The conclusion regarding the palette is that an optimum three-color palette can be chosen 'automatically', but the optimum choice of a 5-color palette cannot be made solely by optimizing the percentage of correct diagnoses. BioMed Central 2009-02-16 /pmc/articles/PMC2680202/ /pubmed/19220885 http://dx.doi.org/10.1186/1471-2288-9-11 Text en Copyright ©2009 Baker et al; 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
Baker, Rose D
Weinand, Christian
Jeng, James C
Hoeksema, Henk
Monstrey, Stan
Pape, Sarah A
Spence, Robert
Wilson, David
Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time
title Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time
title_full Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time
title_fullStr Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time
title_full_unstemmed Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time
title_short Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time
title_sort using ordinal logistic regression to evaluate the performance of laser-doppler predictions of burn-healing time
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2680202/
https://www.ncbi.nlm.nih.gov/pubmed/19220885
http://dx.doi.org/10.1186/1471-2288-9-11
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