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Frailty assessed by administrative tools and mortality in patients with pneumonia admitted to the hospital and ICU in Wales

Tamas Szakmany, Joe Hollinghurst, Richard Pugh, Ashley Akbari Orcid Logo, Rowena Griffiths, Rowena Bailey, Ronan Lyons Orcid Logo

Scientific Reports, Volume: 11, Issue: 1

Swansea University Authors: Joe Hollinghurst, Ashley Akbari Orcid Logo, Rowena Griffiths, Rowena Bailey, Ronan Lyons Orcid Logo

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DOI (Published version): 10.1038/s41598-021-92874-w

Abstract

The ideal method of identifying frailty is uncertain, and data on long-term outcomes is relatively limited. We examined frailty indices derived from population-scale linked data on Intensive Care Unit (ICU) and hospitalised non-ICU patients with pneumonia to elucidate the influence of frailty on mor...

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ISSN: 2045-2322
Published: Springer Science and Business Media LLC 2021
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We examined frailty indices derived from population-scale linked data on Intensive Care Unit (ICU) and hospitalised non-ICU patients with pneumonia to elucidate the influence of frailty on mortality. Longitudinal cohort study between 2010&#x2013;2018 using population-scale anonymised data linkage of healthcare records for adults admitted to hospital with pneumonia in Wales. Primary outcome was in-patient mortality. Odds Ratios (ORs [95% confidence interval]) for age, hospital frailty risk score (HFRS), electronic frailty index (eFI), Charlson comorbidity index (CCI), and social deprivation index were estimated using multivariate logistic regression models. The area under the receiver operating characteristic curve (AUC) was estimated to determine the best fitting models. Of the 107,188 patients, mean (SD) age was 72.6 (16.6) years, 50% were men. The models adjusted for the two frailty indices and the comorbidity index had an increased odds of in-patient mortality for individuals with an ICU admission (ORs for ICU admission in the eFI model 2.67 [2.55, 2.79], HFRS model 2.30 [2.20, 2.41], CCI model 2.62 [2.51, 2.75]). Models indicated advancing age, increased frailty and comorbidity were also associated with an increased odds of in-patient mortality (eFI, baseline fit, ORs: mild 1.09 [1.04, 1.13], moderate 1.13 [1.08, 1.18], severe 1.17 [1.10, 1.23]. HFRS, baseline low, ORs: intermediate 2.65 [2.55, 2.75], high 3.31 [3.17, 3.45]). CCI, baseline&#x2009;&lt;&#x2009;1, ORs: &#x2018;1&#x2013;10&#x2032; 1.15 [1.11, 1.20],&#x2009;&gt;&#x2009;10 2.50 [2.41, 2.60]). For predicting inpatient deaths, the CCI and HFRS based models were similar, however for longer term outcomes the CCI based model was superior. Frailty and comorbidity are significant risk factors for patients admitted to hospital with pneumonia. Frailty and comorbidity scores based on administrative data have only moderate ability to predict outcome.</abstract><type>Journal Article</type><journal>Scientific Reports</journal><volume>11</volume><journalNumber>1</journalNumber><paginationStart/><paginationEnd/><publisher>Springer Science and Business Media LLC</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2045-2322</issnElectronic><keywords>Epidemiology, Outcomes research, Respiratory tract diseases, Risk factors</keywords><publishedDay>28</publishedDay><publishedMonth>6</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-06-28</publishedDate><doi>10.1038/s41598-021-92874-w</doi><url/><notes/><college>COLLEGE NANME</college><department>Medicine, Health and Life Science - Faculty</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>FGMHL</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>This work was supported by Health Data Research UK, which receives its funding from HDR UK Ltd (HDR-9006) funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust. This research has been supported by the ADR Wales programme of work. The ADR Wales programme of work is aligned to the priority themes as identified in the Welsh Government&#x2019;s national strategy: prosperity for All. ADR Wales brings together data science experts at Swansea University Medical School, staff from the Wales Institute of Social and Economic Research, Data and Methods (WISERD) at Cardiff University and specialist teams within the Welsh Government to develop new evidence which supports Prosperity for All by using the SAIL Databank at Swansea University, to link and analyse anonymised data. ADR Wales is part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant ES/S007393/1). Professor Szakmany and Dr Pugh have been supported by grants from the Welsh Government Critical Illness Implementation Group between 2017&#x2013;19.</funders><projectreference/><lastEdited>2022-08-16T13:50:43.8731839</lastEdited><Created>2021-06-29T07:24:47.2450017</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Tamas</firstname><surname>Szakmany</surname><order>1</order></author><author><firstname>Joe</firstname><surname>Hollinghurst</surname><order>2</order></author><author><firstname>Richard</firstname><surname>Pugh</surname><order>3</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>4</order></author><author><firstname>Rowena</firstname><surname>Griffiths</surname><order>5</order></author><author><firstname>Rowena</firstname><surname>Bailey</surname><order>6</order></author><author><firstname>Ronan</firstname><surname>Lyons</surname><orcid>0000-0001-5225-000X</orcid><order>7</order></author></authors><documents><document><filename>57235__20366__737f8f7ba83b4f4a8f1c4296ce9313e4.pdf</filename><originalFilename>57235.pdf</originalFilename><uploaded>2021-07-08T15:58:07.4145290</uploaded><type>Output</type><contentLength>1190078</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>&#xA9; The Author(s) 2021. 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spelling 2022-08-16T13:50:43.8731839 v2 57235 2021-06-29 Frailty assessed by administrative tools and mortality in patients with pneumonia admitted to the hospital and ICU in Wales d7c51b69270b644a11b904629fe56ab0 Joe Hollinghurst Joe Hollinghurst true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 381464f639f98bd388c29326ca7f862c Rowena Griffiths Rowena Griffiths true false 455e2c1e6193448f6269b9e72acaf865 Rowena Bailey Rowena Bailey true false 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 2021-06-29 FGMHL The ideal method of identifying frailty is uncertain, and data on long-term outcomes is relatively limited. We examined frailty indices derived from population-scale linked data on Intensive Care Unit (ICU) and hospitalised non-ICU patients with pneumonia to elucidate the influence of frailty on mortality. Longitudinal cohort study between 2010–2018 using population-scale anonymised data linkage of healthcare records for adults admitted to hospital with pneumonia in Wales. Primary outcome was in-patient mortality. Odds Ratios (ORs [95% confidence interval]) for age, hospital frailty risk score (HFRS), electronic frailty index (eFI), Charlson comorbidity index (CCI), and social deprivation index were estimated using multivariate logistic regression models. The area under the receiver operating characteristic curve (AUC) was estimated to determine the best fitting models. Of the 107,188 patients, mean (SD) age was 72.6 (16.6) years, 50% were men. The models adjusted for the two frailty indices and the comorbidity index had an increased odds of in-patient mortality for individuals with an ICU admission (ORs for ICU admission in the eFI model 2.67 [2.55, 2.79], HFRS model 2.30 [2.20, 2.41], CCI model 2.62 [2.51, 2.75]). Models indicated advancing age, increased frailty and comorbidity were also associated with an increased odds of in-patient mortality (eFI, baseline fit, ORs: mild 1.09 [1.04, 1.13], moderate 1.13 [1.08, 1.18], severe 1.17 [1.10, 1.23]. HFRS, baseline low, ORs: intermediate 2.65 [2.55, 2.75], high 3.31 [3.17, 3.45]). CCI, baseline < 1, ORs: ‘1–10′ 1.15 [1.11, 1.20], > 10 2.50 [2.41, 2.60]). For predicting inpatient deaths, the CCI and HFRS based models were similar, however for longer term outcomes the CCI based model was superior. Frailty and comorbidity are significant risk factors for patients admitted to hospital with pneumonia. Frailty and comorbidity scores based on administrative data have only moderate ability to predict outcome. Journal Article Scientific Reports 11 1 Springer Science and Business Media LLC 2045-2322 Epidemiology, Outcomes research, Respiratory tract diseases, Risk factors 28 6 2021 2021-06-28 10.1038/s41598-021-92874-w COLLEGE NANME Medicine, Health and Life Science - Faculty COLLEGE CODE FGMHL Swansea University This work was supported by Health Data Research UK, which receives its funding from HDR UK Ltd (HDR-9006) funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust. This research has been supported by the ADR Wales programme of work. The ADR Wales programme of work is aligned to the priority themes as identified in the Welsh Government’s national strategy: prosperity for All. ADR Wales brings together data science experts at Swansea University Medical School, staff from the Wales Institute of Social and Economic Research, Data and Methods (WISERD) at Cardiff University and specialist teams within the Welsh Government to develop new evidence which supports Prosperity for All by using the SAIL Databank at Swansea University, to link and analyse anonymised data. ADR Wales is part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant ES/S007393/1). Professor Szakmany and Dr Pugh have been supported by grants from the Welsh Government Critical Illness Implementation Group between 2017–19. 2022-08-16T13:50:43.8731839 2021-06-29T07:24:47.2450017 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Tamas Szakmany 1 Joe Hollinghurst 2 Richard Pugh 3 Ashley Akbari 0000-0003-0814-0801 4 Rowena Griffiths 5 Rowena Bailey 6 Ronan Lyons 0000-0001-5225-000X 7 57235__20366__737f8f7ba83b4f4a8f1c4296ce9313e4.pdf 57235.pdf 2021-07-08T15:58:07.4145290 Output 1190078 application/pdf Version of Record true © The Author(s) 2021. Tis article is licensed under a Creative Commons Attribution 4.0 International License true eng http://creativecommons.org/licenses/by/4.0/
title Frailty assessed by administrative tools and mortality in patients with pneumonia admitted to the hospital and ICU in Wales
spellingShingle Frailty assessed by administrative tools and mortality in patients with pneumonia admitted to the hospital and ICU in Wales
Joe Hollinghurst
Ashley Akbari
Rowena Griffiths
Rowena Bailey
Ronan Lyons
title_short Frailty assessed by administrative tools and mortality in patients with pneumonia admitted to the hospital and ICU in Wales
title_full Frailty assessed by administrative tools and mortality in patients with pneumonia admitted to the hospital and ICU in Wales
title_fullStr Frailty assessed by administrative tools and mortality in patients with pneumonia admitted to the hospital and ICU in Wales
title_full_unstemmed Frailty assessed by administrative tools and mortality in patients with pneumonia admitted to the hospital and ICU in Wales
title_sort Frailty assessed by administrative tools and mortality in patients with pneumonia admitted to the hospital and ICU in Wales
author_id_str_mv d7c51b69270b644a11b904629fe56ab0
aa1b025ec0243f708bb5eb0a93d6fb52
381464f639f98bd388c29326ca7f862c
455e2c1e6193448f6269b9e72acaf865
83efcf2a9dfcf8b55586999d3d152ac6
author_id_fullname_str_mv d7c51b69270b644a11b904629fe56ab0_***_Joe Hollinghurst
aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari
381464f639f98bd388c29326ca7f862c_***_Rowena Griffiths
455e2c1e6193448f6269b9e72acaf865_***_Rowena Bailey
83efcf2a9dfcf8b55586999d3d152ac6_***_Ronan Lyons
author Joe Hollinghurst
Ashley Akbari
Rowena Griffiths
Rowena Bailey
Ronan Lyons
author2 Tamas Szakmany
Joe Hollinghurst
Richard Pugh
Ashley Akbari
Rowena Griffiths
Rowena Bailey
Ronan Lyons
format Journal article
container_title Scientific Reports
container_volume 11
container_issue 1
publishDate 2021
institution Swansea University
issn 2045-2322
doi_str_mv 10.1038/s41598-021-92874-w
publisher Springer Science and Business Media LLC
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
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description The ideal method of identifying frailty is uncertain, and data on long-term outcomes is relatively limited. We examined frailty indices derived from population-scale linked data on Intensive Care Unit (ICU) and hospitalised non-ICU patients with pneumonia to elucidate the influence of frailty on mortality. Longitudinal cohort study between 2010–2018 using population-scale anonymised data linkage of healthcare records for adults admitted to hospital with pneumonia in Wales. Primary outcome was in-patient mortality. Odds Ratios (ORs [95% confidence interval]) for age, hospital frailty risk score (HFRS), electronic frailty index (eFI), Charlson comorbidity index (CCI), and social deprivation index were estimated using multivariate logistic regression models. The area under the receiver operating characteristic curve (AUC) was estimated to determine the best fitting models. Of the 107,188 patients, mean (SD) age was 72.6 (16.6) years, 50% were men. The models adjusted for the two frailty indices and the comorbidity index had an increased odds of in-patient mortality for individuals with an ICU admission (ORs for ICU admission in the eFI model 2.67 [2.55, 2.79], HFRS model 2.30 [2.20, 2.41], CCI model 2.62 [2.51, 2.75]). Models indicated advancing age, increased frailty and comorbidity were also associated with an increased odds of in-patient mortality (eFI, baseline fit, ORs: mild 1.09 [1.04, 1.13], moderate 1.13 [1.08, 1.18], severe 1.17 [1.10, 1.23]. HFRS, baseline low, ORs: intermediate 2.65 [2.55, 2.75], high 3.31 [3.17, 3.45]). CCI, baseline < 1, ORs: ‘1–10′ 1.15 [1.11, 1.20], > 10 2.50 [2.41, 2.60]). For predicting inpatient deaths, the CCI and HFRS based models were similar, however for longer term outcomes the CCI based model was superior. Frailty and comorbidity are significant risk factors for patients admitted to hospital with pneumonia. Frailty and comorbidity scores based on administrative data have only moderate ability to predict outcome.
published_date 2021-06-28T04:12:49Z
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