A comparison of comorbidity measures for predicting mortality after elective hip and knee replacement: A cohort study of data from the National Joint Registry in England and Wales.

<h4>Background</h4>The risk of mortality following elective total hip (THR) and knee replacements (KR) may be influenced by patients' pre-existing comorbidities. There are a variety of scores derived from individual comorbidities that can be used in an attempt to quantify this. The...

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Autores principales:	Chris M Penfold, Michael R Whitehouse, Ashley W Blom, Andrew Judge, J Mark Wilkinson, Adrian Sayers
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a2d2bd0c8e564e8c9702a6247014d01f
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spelling	oai:doaj.org-article:a2d2bd0c8e564e8c9702a6247014d01f2021-12-02T20:18:17ZA comparison of comorbidity measures for predicting mortality after elective hip and knee replacement: A cohort study of data from the National Joint Registry in England and Wales.1932-620310.1371/journal.pone.0255602https://doaj.org/article/a2d2bd0c8e564e8c9702a6247014d01f2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0255602https://doaj.org/toc/1932-6203<h4>Background</h4>The risk of mortality following elective total hip (THR) and knee replacements (KR) may be influenced by patients' pre-existing comorbidities. There are a variety of scores derived from individual comorbidities that can be used in an attempt to quantify this. The aims of this study were to a) identify which comorbidity score best predicts risk of mortality within 90 days or b) determine which comorbidity score best predicts risk of mortality at other relevant timepoints (30, 45, 120 and 365 days).<h4>Patients and methods</h4>We linked data from the National Joint Registry (NJR) on primary elective hip and knee replacements performed between 2011-2015 with pre-existing conditions recorded in the Hospital Episodes Statistics. We derived comorbidity scores (Charlson Comorbidity Index-CCI, Elixhauser, Hospital Frailty Risk Score-HFRS). We used binary logistic regression models of all-cause mortality within 90-days and within 30, 45, 120 and 365-days of the primary operation using, adjusted for age and gender. We compared the performance of these models in predicting all-cause mortality using the area under the Receiver-operator characteristics curve (AUROC) and the Index of Prediction Accuracy (IPA).<h4>Results</h4>We included 276,594 elective primary THRs and 338,287 elective primary KRs for any indication. Mortality within 90-days was 0.34% (N = 939) after THR and 0.26% (N = 865) after KR. The AUROC for the CCI and Elixhauser scores in models of mortality ranged from 0.78-0.81 after THR and KR, which slightly outperformed models with ASA grade (AUROC = 0.77-0.78). HFRS performed similarly to ASA grade (AUROC = 0.76-0.78). The inclusion of comorbidities prior to the primary operation offers no improvement beyond models with comorbidities at the time of the primary. The discriminative ability of all prediction models was best for mortality within 30 days and worst for mortality within 365 days.<h4>Conclusions</h4>Comorbidity scores add little improvement beyond simpler models with age, gender and ASA grade for predicting mortality within one year after elective hip or knee replacement. The additional patient-specific information required to construct comorbidity scores must be balanced against their prediction gain when considering their utility.Chris M PenfoldMichael R WhitehouseAshley W BlomAndrew JudgeJ Mark WilkinsonAdrian SayersPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0255602 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Chris M Penfold Michael R Whitehouse Ashley W Blom Andrew Judge J Mark Wilkinson Adrian Sayers A comparison of comorbidity measures for predicting mortality after elective hip and knee replacement: A cohort study of data from the National Joint Registry in England and Wales.
description	<h4>Background</h4>The risk of mortality following elective total hip (THR) and knee replacements (KR) may be influenced by patients' pre-existing comorbidities. There are a variety of scores derived from individual comorbidities that can be used in an attempt to quantify this. The aims of this study were to a) identify which comorbidity score best predicts risk of mortality within 90 days or b) determine which comorbidity score best predicts risk of mortality at other relevant timepoints (30, 45, 120 and 365 days).<h4>Patients and methods</h4>We linked data from the National Joint Registry (NJR) on primary elective hip and knee replacements performed between 2011-2015 with pre-existing conditions recorded in the Hospital Episodes Statistics. We derived comorbidity scores (Charlson Comorbidity Index-CCI, Elixhauser, Hospital Frailty Risk Score-HFRS). We used binary logistic regression models of all-cause mortality within 90-days and within 30, 45, 120 and 365-days of the primary operation using, adjusted for age and gender. We compared the performance of these models in predicting all-cause mortality using the area under the Receiver-operator characteristics curve (AUROC) and the Index of Prediction Accuracy (IPA).<h4>Results</h4>We included 276,594 elective primary THRs and 338,287 elective primary KRs for any indication. Mortality within 90-days was 0.34% (N = 939) after THR and 0.26% (N = 865) after KR. The AUROC for the CCI and Elixhauser scores in models of mortality ranged from 0.78-0.81 after THR and KR, which slightly outperformed models with ASA grade (AUROC = 0.77-0.78). HFRS performed similarly to ASA grade (AUROC = 0.76-0.78). The inclusion of comorbidities prior to the primary operation offers no improvement beyond models with comorbidities at the time of the primary. The discriminative ability of all prediction models was best for mortality within 30 days and worst for mortality within 365 days.<h4>Conclusions</h4>Comorbidity scores add little improvement beyond simpler models with age, gender and ASA grade for predicting mortality within one year after elective hip or knee replacement. The additional patient-specific information required to construct comorbidity scores must be balanced against their prediction gain when considering their utility.
format	article
author	Chris M Penfold Michael R Whitehouse Ashley W Blom Andrew Judge J Mark Wilkinson Adrian Sayers
author_facet	Chris M Penfold Michael R Whitehouse Ashley W Blom Andrew Judge J Mark Wilkinson Adrian Sayers
author_sort	Chris M Penfold
title	A comparison of comorbidity measures for predicting mortality after elective hip and knee replacement: A cohort study of data from the National Joint Registry in England and Wales.
title_short	A comparison of comorbidity measures for predicting mortality after elective hip and knee replacement: A cohort study of data from the National Joint Registry in England and Wales.
title_full	A comparison of comorbidity measures for predicting mortality after elective hip and knee replacement: A cohort study of data from the National Joint Registry in England and Wales.
title_fullStr	A comparison of comorbidity measures for predicting mortality after elective hip and knee replacement: A cohort study of data from the National Joint Registry in England and Wales.
title_full_unstemmed	A comparison of comorbidity measures for predicting mortality after elective hip and knee replacement: A cohort study of data from the National Joint Registry in England and Wales.
title_sort	comparison of comorbidity measures for predicting mortality after elective hip and knee replacement: a cohort study of data from the national joint registry in england and wales.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/a2d2bd0c8e564e8c9702a6247014d01f
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A comparison of comorbidity measures for predicting mortality after elective hip and knee replacement: A cohort study of data from the National Joint Registry in England and Wales.

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