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Development and internal validation of a predictive model of cognitive decline 36 months following elective surgery

INTRODUCTION: Our goal was to determine if features of surgical patients, easily obtained from the medical chart or brief interview, could be used to predict those likely to experience more rapid cognitive decline following surgery. METHODS: We analyzed data from an observational study of 560 older...

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Autores principales: Jones, Richard N., Tommet, Douglas, Steingrimsson, Jon, Racine, Annie M., Fong, Tamara G., Gou, Yun, Hshieh, Tammy T., Metzger, Eran D., Schmitt, Eva M., Tabloski, Patricia A., Travison, Thomas G., Vasunilashorn, Sarinnapha M., Abdeen, Ayesha, Earp, Brandon, Kunze, Lisa, Lange, Jeffrey, Vlassakov, Kamen, Dickerson, Bradford C., Marcantonio, Edward R., Inouye, Sharon K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8140204/
https://www.ncbi.nlm.nih.gov/pubmed/34046520
http://dx.doi.org/10.1002/dad2.12201
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author Jones, Richard N.
Tommet, Douglas
Steingrimsson, Jon
Racine, Annie M.
Fong, Tamara G.
Gou, Yun
Hshieh, Tammy T.
Metzger, Eran D.
Schmitt, Eva M.
Tabloski, Patricia A.
Travison, Thomas G.
Vasunilashorn, Sarinnapha M.
Abdeen, Ayesha
Earp, Brandon
Kunze, Lisa
Lange, Jeffrey
Vlassakov, Kamen
Dickerson, Bradford C.
Marcantonio, Edward R.
Inouye, Sharon K.
author_facet Jones, Richard N.
Tommet, Douglas
Steingrimsson, Jon
Racine, Annie M.
Fong, Tamara G.
Gou, Yun
Hshieh, Tammy T.
Metzger, Eran D.
Schmitt, Eva M.
Tabloski, Patricia A.
Travison, Thomas G.
Vasunilashorn, Sarinnapha M.
Abdeen, Ayesha
Earp, Brandon
Kunze, Lisa
Lange, Jeffrey
Vlassakov, Kamen
Dickerson, Bradford C.
Marcantonio, Edward R.
Inouye, Sharon K.
author_sort Jones, Richard N.
collection PubMed
description INTRODUCTION: Our goal was to determine if features of surgical patients, easily obtained from the medical chart or brief interview, could be used to predict those likely to experience more rapid cognitive decline following surgery. METHODS: We analyzed data from an observational study of 560 older adults (≥70 years) without dementia undergoing major elective non‐cardiac surgery. Cognitive decline was measured using change in a global composite over 2 to 36 months following surgery. Predictive features were identified as variables readily obtained from chart review or a brief patient assessment. We developed predictive models for cognitive decline (slope) and predicting dichotomized cognitive decline at a clinically determined cut. RESULTS: In a hold‐out testing set, the regularized regression predictive model achieved a root mean squared error (RMSE) of 0.146 and a model r‐square (R(2)) of .31. Prediction of “rapid” decliners as a group achieved an area under the curve (AUC) of .75. CONCLUSION: Some of our models could predict persons with increased risk for accelerated cognitive decline with greater accuracy than relying upon chance, and this result might be useful for stratification of surgical patients for inclusion in future clinical trials.
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spelling pubmed-81402042021-05-26 Development and internal validation of a predictive model of cognitive decline 36 months following elective surgery Jones, Richard N. Tommet, Douglas Steingrimsson, Jon Racine, Annie M. Fong, Tamara G. Gou, Yun Hshieh, Tammy T. Metzger, Eran D. Schmitt, Eva M. Tabloski, Patricia A. Travison, Thomas G. Vasunilashorn, Sarinnapha M. Abdeen, Ayesha Earp, Brandon Kunze, Lisa Lange, Jeffrey Vlassakov, Kamen Dickerson, Bradford C. Marcantonio, Edward R. Inouye, Sharon K. Alzheimers Dement (Amst) Diagnostic Assessment & Prognosis INTRODUCTION: Our goal was to determine if features of surgical patients, easily obtained from the medical chart or brief interview, could be used to predict those likely to experience more rapid cognitive decline following surgery. METHODS: We analyzed data from an observational study of 560 older adults (≥70 years) without dementia undergoing major elective non‐cardiac surgery. Cognitive decline was measured using change in a global composite over 2 to 36 months following surgery. Predictive features were identified as variables readily obtained from chart review or a brief patient assessment. We developed predictive models for cognitive decline (slope) and predicting dichotomized cognitive decline at a clinically determined cut. RESULTS: In a hold‐out testing set, the regularized regression predictive model achieved a root mean squared error (RMSE) of 0.146 and a model r‐square (R(2)) of .31. Prediction of “rapid” decliners as a group achieved an area under the curve (AUC) of .75. CONCLUSION: Some of our models could predict persons with increased risk for accelerated cognitive decline with greater accuracy than relying upon chance, and this result might be useful for stratification of surgical patients for inclusion in future clinical trials. John Wiley and Sons Inc. 2021-05-21 /pmc/articles/PMC8140204/ /pubmed/34046520 http://dx.doi.org/10.1002/dad2.12201 Text en © 2021 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Diagnostic Assessment & Prognosis
Jones, Richard N.
Tommet, Douglas
Steingrimsson, Jon
Racine, Annie M.
Fong, Tamara G.
Gou, Yun
Hshieh, Tammy T.
Metzger, Eran D.
Schmitt, Eva M.
Tabloski, Patricia A.
Travison, Thomas G.
Vasunilashorn, Sarinnapha M.
Abdeen, Ayesha
Earp, Brandon
Kunze, Lisa
Lange, Jeffrey
Vlassakov, Kamen
Dickerson, Bradford C.
Marcantonio, Edward R.
Inouye, Sharon K.
Development and internal validation of a predictive model of cognitive decline 36 months following elective surgery
title Development and internal validation of a predictive model of cognitive decline 36 months following elective surgery
title_full Development and internal validation of a predictive model of cognitive decline 36 months following elective surgery
title_fullStr Development and internal validation of a predictive model of cognitive decline 36 months following elective surgery
title_full_unstemmed Development and internal validation of a predictive model of cognitive decline 36 months following elective surgery
title_short Development and internal validation of a predictive model of cognitive decline 36 months following elective surgery
title_sort development and internal validation of a predictive model of cognitive decline 36 months following elective surgery
topic Diagnostic Assessment & Prognosis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8140204/
https://www.ncbi.nlm.nih.gov/pubmed/34046520
http://dx.doi.org/10.1002/dad2.12201
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