An early prediction of delirium in the acute phase after stroke

A.W. Oldenbeuving, P.L. de Kort, J.F. van Eck van der Sluijs, LJ Kappelle, G. Roks

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Background
We developed and validated a risk score to predict delirium after stroke which was derived from our prospective cohort study where several risk factors were identified.
Methods
Using the β coefficients from the logistic regression model, we allocated a score to values of the risk factors. In the first model, stroke severity, stroke subtype, infection, stroke localisation, pre-existent cognitive decline and age were included. The second model included age, stroke severity, stroke subtype and infection. A third model only included age and stroke severity. The risk score was validated in an independent dataset.
Results
The area under the curve (AUC) of the first model was 0.85 (sensitivity 86%, specificity 74%). In the second model, the AUC was 0.84 (sensitivity 80%, specificity 75%). The third model had an AUC of 0.80 (sensitivity 79%, specificity 73%). In the validation set, model 1 had an AUC of 0.83 (sensitivity 78%, specificity 77%). The second had an AUC of 0.83 (sensitivity 76%, specificity 81%). The third model gave an AUC of 0.82 (sensitivity of 73%, specificity 75%). We conclude that model 2 is easy to use in clinical practice and slightly better than model 3 and, therefore, was used to create risk tables to use as a tool in clinical practice.
Conclusions
A model including age, stroke severity, stroke subtype and infection can be used to identify patients who have a high risk to develop delirium in the early phase of stroke.
Original languageEnglish
Pages (from-to)431-434
JournalJournal of Neurology, Neurosurgery & Psychiatry
Volume85
Issue number4
DOIs
Publication statusPublished - 2013

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Area Under Curve
Logistic Models

Cite this

Oldenbeuving, A. W., de Kort, P. L., van Eck van der Sluijs, J. F., Kappelle, LJ., & Roks, G. (2013). An early prediction of delirium in the acute phase after stroke. Journal of Neurology, Neurosurgery & Psychiatry, 85(4), 431-434. https://doi.org/10.1136/jnnp-2013-304920
Oldenbeuving, A.W. ; de Kort, P.L. ; van Eck van der Sluijs, J.F. ; Kappelle, LJ ; Roks, G. / An early prediction of delirium in the acute phase after stroke. In: Journal of Neurology, Neurosurgery & Psychiatry. 2013 ; Vol. 85, No. 4. pp. 431-434.
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title = "An early prediction of delirium in the acute phase after stroke",
abstract = "Background We developed and validated a risk score to predict delirium after stroke which was derived from our prospective cohort study where several risk factors were identified.Methods Using the β coefficients from the logistic regression model, we allocated a score to values of the risk factors. In the first model, stroke severity, stroke subtype, infection, stroke localisation, pre-existent cognitive decline and age were included. The second model included age, stroke severity, stroke subtype and infection. A third model only included age and stroke severity. The risk score was validated in an independent dataset.Results The area under the curve (AUC) of the first model was 0.85 (sensitivity 86{\%}, specificity 74{\%}). In the second model, the AUC was 0.84 (sensitivity 80{\%}, specificity 75{\%}). The third model had an AUC of 0.80 (sensitivity 79{\%}, specificity 73{\%}). In the validation set, model 1 had an AUC of 0.83 (sensitivity 78{\%}, specificity 77{\%}). The second had an AUC of 0.83 (sensitivity 76{\%}, specificity 81{\%}). The third model gave an AUC of 0.82 (sensitivity of 73{\%}, specificity 75{\%}). We conclude that model 2 is easy to use in clinical practice and slightly better than model 3 and, therefore, was used to create risk tables to use as a tool in clinical practice.Conclusions A model including age, stroke severity, stroke subtype and infection can be used to identify patients who have a high risk to develop delirium in the early phase of stroke.",
author = "A.W. Oldenbeuving and {de Kort}, P.L. and {van Eck van der Sluijs}, J.F. and LJ Kappelle and G. Roks",
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Oldenbeuving, AW, de Kort, PL, van Eck van der Sluijs, JF, Kappelle, LJ & Roks, G 2013, 'An early prediction of delirium in the acute phase after stroke', Journal of Neurology, Neurosurgery & Psychiatry, vol. 85, no. 4, pp. 431-434. https://doi.org/10.1136/jnnp-2013-304920

An early prediction of delirium in the acute phase after stroke. / Oldenbeuving, A.W.; de Kort, P.L.; van Eck van der Sluijs, J.F.; Kappelle, LJ; Roks, G.

In: Journal of Neurology, Neurosurgery & Psychiatry, Vol. 85, No. 4, 2013, p. 431-434.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - An early prediction of delirium in the acute phase after stroke

AU - Oldenbeuving, A.W.

AU - de Kort, P.L.

AU - van Eck van der Sluijs, J.F.

AU - Kappelle, LJ

AU - Roks, G.

PY - 2013

Y1 - 2013

N2 - Background We developed and validated a risk score to predict delirium after stroke which was derived from our prospective cohort study where several risk factors were identified.Methods Using the β coefficients from the logistic regression model, we allocated a score to values of the risk factors. In the first model, stroke severity, stroke subtype, infection, stroke localisation, pre-existent cognitive decline and age were included. The second model included age, stroke severity, stroke subtype and infection. A third model only included age and stroke severity. The risk score was validated in an independent dataset.Results The area under the curve (AUC) of the first model was 0.85 (sensitivity 86%, specificity 74%). In the second model, the AUC was 0.84 (sensitivity 80%, specificity 75%). The third model had an AUC of 0.80 (sensitivity 79%, specificity 73%). In the validation set, model 1 had an AUC of 0.83 (sensitivity 78%, specificity 77%). The second had an AUC of 0.83 (sensitivity 76%, specificity 81%). The third model gave an AUC of 0.82 (sensitivity of 73%, specificity 75%). We conclude that model 2 is easy to use in clinical practice and slightly better than model 3 and, therefore, was used to create risk tables to use as a tool in clinical practice.Conclusions A model including age, stroke severity, stroke subtype and infection can be used to identify patients who have a high risk to develop delirium in the early phase of stroke.

AB - Background We developed and validated a risk score to predict delirium after stroke which was derived from our prospective cohort study where several risk factors were identified.Methods Using the β coefficients from the logistic regression model, we allocated a score to values of the risk factors. In the first model, stroke severity, stroke subtype, infection, stroke localisation, pre-existent cognitive decline and age were included. The second model included age, stroke severity, stroke subtype and infection. A third model only included age and stroke severity. The risk score was validated in an independent dataset.Results The area under the curve (AUC) of the first model was 0.85 (sensitivity 86%, specificity 74%). In the second model, the AUC was 0.84 (sensitivity 80%, specificity 75%). The third model had an AUC of 0.80 (sensitivity 79%, specificity 73%). In the validation set, model 1 had an AUC of 0.83 (sensitivity 78%, specificity 77%). The second had an AUC of 0.83 (sensitivity 76%, specificity 81%). The third model gave an AUC of 0.82 (sensitivity of 73%, specificity 75%). We conclude that model 2 is easy to use in clinical practice and slightly better than model 3 and, therefore, was used to create risk tables to use as a tool in clinical practice.Conclusions A model including age, stroke severity, stroke subtype and infection can be used to identify patients who have a high risk to develop delirium in the early phase of stroke.

U2 - 10.1136/jnnp-2013-304920

DO - 10.1136/jnnp-2013-304920

M3 - Article

VL - 85

SP - 431

EP - 434

JO - Journal of neurology, neurosurgery and psychiatry

JF - Journal of neurology, neurosurgery and psychiatry

SN - 0022-3050

IS - 4

ER -

Oldenbeuving AW, de Kort PL, van Eck van der Sluijs JF, Kappelle LJ, Roks G. An early prediction of delirium in the acute phase after stroke. Journal of Neurology, Neurosurgery & Psychiatry. 2013;85(4):431-434. https://doi.org/10.1136/jnnp-2013-304920