Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study.

Statistical models for outcome prediction are central to traumatic brain injury research and critical to baseline risk adjustment. Glasgow coma score (GCS) and pupil reactivity are crucial covariates in all such models but may be measured at multiple time points between the time of injury and hospit...

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Autores principales:	Ari Ercole, Abhishek Dixit, David W Nelson, Shubhayu Bhattacharyay, Frederick A Zeiler, Daan Nieboer, Omar Bouamra, David K Menon, Andrew I R Maas, Simone A Dijkland, Hester F Lingsma, Lindsay Wilson, Fiona Lecky, Ewout W Steyerberg, CENTER-TBI Investigators and Participants
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7882c1e269324ffcb16c5f1c89d7569b
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spelling	oai:doaj.org-article:7882c1e269324ffcb16c5f1c89d7569b2021-12-02T20:18:36ZImputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study.1932-620310.1371/journal.pone.0253425https://doaj.org/article/7882c1e269324ffcb16c5f1c89d7569b2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0253425https://doaj.org/toc/1932-6203Statistical models for outcome prediction are central to traumatic brain injury research and critical to baseline risk adjustment. Glasgow coma score (GCS) and pupil reactivity are crucial covariates in all such models but may be measured at multiple time points between the time of injury and hospital and are subject to a variable degree of unreliability and/or missingness. Imputation of missing data may be undertaken using full multiple imputation or by simple substitution of measurements from other time points. However, it is unknown which strategy is best or which time points are more predictive. We evaluated the pseudo-R2 of logistic regression models (dichotomous survival) and proportional odds models (Glasgow Outcome Score-extended) using different imputation strategies on the The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study dataset. Substitution strategies were easy to implement, achieved low levels of missingness (<< 10%) and could outperform multiple imputation without the need for computationally costly calculations and pooling multiple final models. While model performance was sensitive to imputation strategy, this effect was small in absolute terms and clinical relevance. A strategy of using the emergency department discharge assessments and working back in time when these were missing generally performed well. Full multiple imputation had the advantage of preserving time-dependence in the models: the pre-hospital assessments were found to be relatively unreliable predictors of survival or outcome. The predictive performance of later assessments was model-dependent. In conclusion, simple substitution strategies for imputing baseline GCS and pupil response can perform well and may be a simple alternative to full multiple imputation in many cases.Ari ErcoleAbhishek DixitDavid W NelsonShubhayu BhattacharyayFrederick A ZeilerDaan NieboerOmar BouamraDavid K MenonAndrew I R MaasSimone A DijklandHester F LingsmaLindsay WilsonFiona LeckyEwout W SteyerbergCENTER-TBI Investigators and ParticipantsPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0253425 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ari Ercole Abhishek Dixit David W Nelson Shubhayu Bhattacharyay Frederick A Zeiler Daan Nieboer Omar Bouamra David K Menon Andrew I R Maas Simone A Dijkland Hester F Lingsma Lindsay Wilson Fiona Lecky Ewout W Steyerberg CENTER-TBI Investigators and Participants Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study.
description	Statistical models for outcome prediction are central to traumatic brain injury research and critical to baseline risk adjustment. Glasgow coma score (GCS) and pupil reactivity are crucial covariates in all such models but may be measured at multiple time points between the time of injury and hospital and are subject to a variable degree of unreliability and/or missingness. Imputation of missing data may be undertaken using full multiple imputation or by simple substitution of measurements from other time points. However, it is unknown which strategy is best or which time points are more predictive. We evaluated the pseudo-R2 of logistic regression models (dichotomous survival) and proportional odds models (Glasgow Outcome Score-extended) using different imputation strategies on the The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study dataset. Substitution strategies were easy to implement, achieved low levels of missingness (<< 10%) and could outperform multiple imputation without the need for computationally costly calculations and pooling multiple final models. While model performance was sensitive to imputation strategy, this effect was small in absolute terms and clinical relevance. A strategy of using the emergency department discharge assessments and working back in time when these were missing generally performed well. Full multiple imputation had the advantage of preserving time-dependence in the models: the pre-hospital assessments were found to be relatively unreliable predictors of survival or outcome. The predictive performance of later assessments was model-dependent. In conclusion, simple substitution strategies for imputing baseline GCS and pupil response can perform well and may be a simple alternative to full multiple imputation in many cases.
format	article
author	Ari Ercole Abhishek Dixit David W Nelson Shubhayu Bhattacharyay Frederick A Zeiler Daan Nieboer Omar Bouamra David K Menon Andrew I R Maas Simone A Dijkland Hester F Lingsma Lindsay Wilson Fiona Lecky Ewout W Steyerberg CENTER-TBI Investigators and Participants
author_facet	Ari Ercole Abhishek Dixit David W Nelson Shubhayu Bhattacharyay Frederick A Zeiler Daan Nieboer Omar Bouamra David K Menon Andrew I R Maas Simone A Dijkland Hester F Lingsma Lindsay Wilson Fiona Lecky Ewout W Steyerberg CENTER-TBI Investigators and Participants
author_sort	Ari Ercole
title	Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study.
title_short	Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study.
title_full	Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study.
title_fullStr	Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study.
title_full_unstemmed	Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study.
title_sort	imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: a center-tbi study.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/7882c1e269324ffcb16c5f1c89d7569b
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Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study.

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