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Simple approaches to characterising multiple long‐term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants

BACKGROUND: Numerous approaches are used to characterise multiple long‐term conditions (MLTC), including counts and indices. Few studies have compared approaches within the same dataset. We aimed to characterise MLTC using simple approaches, and compare their prevalence estimates of MLTC and associa...

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Autores principales: Dodds, Richard M., Bunn, Jonathan G., Hillman, Susan J., Granic, Antoneta, Murray, James, Witham, Miles D., Robinson, Sian M., Cooper, Rachel, Sayer, Avan A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10086957/
https://www.ncbi.nlm.nih.gov/pubmed/36131375
http://dx.doi.org/10.1111/joim.13567
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author Dodds, Richard M.
Bunn, Jonathan G.
Hillman, Susan J.
Granic, Antoneta
Murray, James
Witham, Miles D.
Robinson, Sian M.
Cooper, Rachel
Sayer, Avan A.
author_facet Dodds, Richard M.
Bunn, Jonathan G.
Hillman, Susan J.
Granic, Antoneta
Murray, James
Witham, Miles D.
Robinson, Sian M.
Cooper, Rachel
Sayer, Avan A.
author_sort Dodds, Richard M.
collection PubMed
description BACKGROUND: Numerous approaches are used to characterise multiple long‐term conditions (MLTC), including counts and indices. Few studies have compared approaches within the same dataset. We aimed to characterise MLTC using simple approaches, and compare their prevalence estimates of MLTC and associations with emergency hospital admission in the UK Biobank. METHODS: We used baseline data from 495,465 participants (age 38–73 years) to characterise MLTC using four approaches: Charlson index (CI), Byles index (BI), count of 43 conditions (CC) and count of body systems affected (BC). We defined MLTC as more than two conditions using CI, BI and CC, and more than two body systems using BC. We categorised scores (incorporating weightings for the indices) from each approach as 0, 1, 2 and 3+. We used linked hospital episode statistics and performed survival analyses to test associations with an endpoint of emergency hospital admission or death over 5 years. RESULTS: The prevalence of MLTC was 44% (BC), 33% (CC), 6% (BI) and 2% (CI). Higher scores using all approaches were associated with greater outcome rates independent of sex and age group. For example, using CC, compared with score 0, score 2 had 1.95 (95% CI: 1.91, 1.99) and a score of 3+ had 3.12 (95% CI: 3.06, 3.18) times greater outcome rates. The discriminant value of all approaches was modest (C‐statistics 0.60–0.63). CONCLUSIONS: The counts classified a greater proportion as having MLTC than the indices, highlighting that prevalence estimates of MLTC vary depending on the approach. All approaches had strong statistical associations with emergency hospital admission but a modest ability to identify individuals at risk.
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spelling pubmed-100869572023-04-12 Simple approaches to characterising multiple long‐term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants Dodds, Richard M. Bunn, Jonathan G. Hillman, Susan J. Granic, Antoneta Murray, James Witham, Miles D. Robinson, Sian M. Cooper, Rachel Sayer, Avan A. J Intern Med Original Articles BACKGROUND: Numerous approaches are used to characterise multiple long‐term conditions (MLTC), including counts and indices. Few studies have compared approaches within the same dataset. We aimed to characterise MLTC using simple approaches, and compare their prevalence estimates of MLTC and associations with emergency hospital admission in the UK Biobank. METHODS: We used baseline data from 495,465 participants (age 38–73 years) to characterise MLTC using four approaches: Charlson index (CI), Byles index (BI), count of 43 conditions (CC) and count of body systems affected (BC). We defined MLTC as more than two conditions using CI, BI and CC, and more than two body systems using BC. We categorised scores (incorporating weightings for the indices) from each approach as 0, 1, 2 and 3+. We used linked hospital episode statistics and performed survival analyses to test associations with an endpoint of emergency hospital admission or death over 5 years. RESULTS: The prevalence of MLTC was 44% (BC), 33% (CC), 6% (BI) and 2% (CI). Higher scores using all approaches were associated with greater outcome rates independent of sex and age group. For example, using CC, compared with score 0, score 2 had 1.95 (95% CI: 1.91, 1.99) and a score of 3+ had 3.12 (95% CI: 3.06, 3.18) times greater outcome rates. The discriminant value of all approaches was modest (C‐statistics 0.60–0.63). CONCLUSIONS: The counts classified a greater proportion as having MLTC than the indices, highlighting that prevalence estimates of MLTC vary depending on the approach. All approaches had strong statistical associations with emergency hospital admission but a modest ability to identify individuals at risk. John Wiley and Sons Inc. 2022-09-21 2023-01 /pmc/articles/PMC10086957/ /pubmed/36131375 http://dx.doi.org/10.1111/joim.13567 Text en © 2022 The Authors. Journal of Internal Medicine published by John Wiley & Sons Ltd on behalf of Association for Publication of The Journal of Internal Medicine. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Dodds, Richard M.
Bunn, Jonathan G.
Hillman, Susan J.
Granic, Antoneta
Murray, James
Witham, Miles D.
Robinson, Sian M.
Cooper, Rachel
Sayer, Avan A.
Simple approaches to characterising multiple long‐term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants
title Simple approaches to characterising multiple long‐term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants
title_full Simple approaches to characterising multiple long‐term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants
title_fullStr Simple approaches to characterising multiple long‐term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants
title_full_unstemmed Simple approaches to characterising multiple long‐term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants
title_short Simple approaches to characterising multiple long‐term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants
title_sort simple approaches to characterising multiple long‐term conditions (multimorbidity) and rates of emergency hospital admission: findings from 495,465 uk biobank participants
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10086957/
https://www.ncbi.nlm.nih.gov/pubmed/36131375
http://dx.doi.org/10.1111/joim.13567
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