Frailty and comorbidity in predicting community COVID-19 mortality in the UK Biobank: The effect of sampling

被引:35
作者
Mak, Jonathan K. L. [1 ]
Kuja-Halkola, Ralf [1 ]
Wang, Yunzhang [1 ]
Hagg, Sara [1 ]
Jylhava, Juulia [1 ]
机构
[1] Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden
基金
瑞典研究理事会;
关键词
aging; comorbidity; COVID-19; frailty; mortality; OLDER-ADULTS; INDEX; OUTCOMES; FITNESS; RISK;
D O I
10.1111/jgs.17089
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
Background/Objectives Frailty has been linked to increased risk of COVID-19 mortality, but evidence is mainly limited to hospitalized older individuals. This study aimed to assess and compare predictive abilities of different frailty and comorbidity measures for COVID-19 mortality in a community sample and COVID-19 inpatients. Design Population-based cohort study. Setting Community. Participants We analyzed (i) the full sample of 410,199 U.K. Biobank participants in England, aged 49-86 years, and (ii) a subsample of 2812 COVID-19 inpatients with COVID-19 data from March 1 to November 30, 2020. Measurements Frailty was defined using the physical frailty phenotype (PFP), frailty index (FI), and Hospital Frailty Risk Score (HFRS), and comorbidity using the Charlson Comorbidity Index (CCI). PFP and FI were available at baseline, whereas HFRS and CCI were assessed both at baseline and concurrently with the start of the pandemic. Inpatient COVID-19 cases were confirmed by PCR and/or hospital records. COVID-19 mortality was ascertained from death registers. Results Overall, 514 individuals died of COVID-19. In the full sample, all frailty and comorbidity measures were associated with higher COVID-19 mortality risk after adjusting for age and sex. However, the associations were stronger for the concurrent versus baseline HFRS and CCI, with odds ratios of 20.40 (95% confidence interval = 16.24-25.63) comparing high (>15) to low (<5) concurrent HFRS risk category and 1.53 (1.48-1.59) per point increase in concurrent CCI. Moreover, only the concurrent HFRS or CCI significantly improved predictive ability of a model including age and sex, yielding areas under the receiver operating characteristic curve (AUC) >0.8. When restricting analyses to COVID-19 inpatients, similar improvement in AUC was not observed. Conclusion HFRS and CCI constructed from medical records concurrent with the start of the pandemic can be used in COVID-19 mortality risk stratification at the population level, but they show limited added value in COVID-19 inpatients.
引用
收藏
页码:1128 / 1139
页数:12
相关论文
共 34 条
  • [11] Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study
    Gilbert, Thomas
    Neuburger, Jenny
    Kraindler, Joshua
    Keeble, Eilis
    Smith, Paul
    Ariti, Cono
    Arora, Sandeepa
    Street, Andrew
    Parker, Stuart
    Roberts, Helen C.
    Bardsley, Martin
    Conroy, Simon
    [J]. LANCET, 2018, 391 (10132) : 1775 - 1782
  • [12] Collider bias undermines our understanding of COVID-19 disease risk and severity
    Griffith, Gareth J.
    Morris, Tim T.
    Tudball, Matthew J.
    Herbert, Annie
    Mancano, Giulia
    Pike, Lindsey
    Sharp, Gemma C.
    Sterne, Jonathan
    Palmer, Tom M.
    Smith, George Davey
    Tilling, Kate
    Zuccolo, Luisa
    Davies, Neil M.
    Hemani, Gibran
    [J]. NATURE COMMUNICATIONS, 2020, 11 (01)
  • [13] Age, Frailty, and Comorbidity as Prognostic Factors for Short-Term Outcomes in Patients With Coronavirus Disease 2019 in Geriatric Care
    Hagg, Sara
    Jylhava, Juulia
    Wang, Yunzhang
    Xu, Hong
    Metzner, Carina
    Annetorp, Martin
    Garcia-Ptacek, Sara
    Khedri, Masih
    Bostrom, Anne-Marie
    Kadir, Ahmadul
    Johansson, Anna
    Kivipelto, Miia
    Eriksdotter, Maria
    Cederholm, Tommy
    Religa, Dorota
    [J]. JOURNAL OF THE AMERICAN MEDICAL DIRECTORS ASSOCIATION, 2020, 21 (11) : 1555 - +
  • [14] Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493 737 UK Biobank participants
    Hanlon, Peter
    Nicholl, Barbara I.
    Jani, Bhautesh Dinesh
    Lee, Duncan
    McQueenie, Ross
    Mair, Frances S.
    [J]. LANCET PUBLIC HEALTH, 2018, 3 (07) : E323 - E332
  • [15] The effect of frailty on survival in patients with COVID-19 (COPE): a multicentre, European, observational cohort study
    Hewitt, Jonathan
    Carter, Ben
    Vilches-Moraga, Arturo
    Quinn, Terence J.
    Braude, Philip
    Verduri, Alessia
    Pearce, Lyndsay
    Stechman, Michael
    Short, Roxanna
    Price, Angeline
    Collins, Jemima T.
    Bruce, Eilidh
    Einarsson, Alice
    Rickard, Frances
    Mitchell, Emma
    Holloway, Mark
    Hesford, James
    Barlow-Pay, Fenella
    Clini, Enrico
    Myint, Phyo K.
    Moug, Susan J.
    McCarthy, Kathryn
    [J]. LANCET PUBLIC HEALTH, 2020, 5 (08) : E444 - E451
  • [16] Prediction for Progression Risk in Patients With COVID-19 Pneumonia: The CALL Score
    Ji, Dong
    Zhang, Dawei
    Xu, Jing
    Chen, Zhu
    Yang, Tieniu
    Zhao, Peng
    Chen, Guofeng
    Cheng, Gregory
    Wang, Yudong
    Bi, Jingfeng
    Tan, Lin
    Lau, George
    Qin, Enqiang
    [J]. CLINICAL INFECTIOUS DISEASES, 2020, 71 (06) : 1393 - 1399
  • [17] The role of Frailty on Adverse Outcomes Among Older Patients with COVID-19
    Kundi, Harun
    Cetin, Elif Hande Ozcan
    Canpolat, Ugur
    Aras, Sevgi
    Celik, Osman
    Ata, Naim
    Birinci, Suayip
    Cay, Serkan
    Ozeke, Ozcan
    Tanboga, Ibrahim Halil
    Topaloglu, Serkan
    [J]. JOURNAL OF INFECTION, 2020, 81 (06) : 944 - 951
  • [18] Association of Frailty With 30-Day Outcomes for Acute Myocardial Infarction, Heart Failure, and Pneumonia Among Elderly Adults
    Kundi, Harun
    Wadhera, Rishi K.
    Strom, Jordan B.
    Valsdottir, Linda R.
    Shen, Changyu
    Kazi, Dhruv S.
    Yeh, Robert W.
    [J]. JAMA CARDIOLOGY, 2019, 4 (11) : 1084 - 1091
  • [19] The frailty index is a predictor of cause-specific mortality independent of familial effects from midlife onwards: a large cohort study
    Li, Xia
    Ploner, Alexander
    Karlsson, Ida K.
    Liu, Xingrong
    Magnusson, Patrik K. E.
    Pedersen, Nancy L.
    Haegg, Sara
    Jylhava, Juulia
    [J]. BMC MEDICINE, 2019, 17 (1)
  • [20] A comparison of mortality-related risk factors of COVID-19, SARS, and MERS: A systematic review and meta-analysis
    Lu, Lvliang
    Zhong, Wenyu
    Bian, Ziwei
    Li, Zhiming
    Zhang, Ke
    Liang, Boxuan
    Zhong, Yizhou
    Hu, Manjiang
    Lin, Li
    Liu, Jun
    Lin, Xi
    Huang, Yuji
    Jiang, Junying
    Yang, Xingfen
    Zhang, Xin
    Huang, Zhenlie
    [J]. JOURNAL OF INFECTION, 2020, 81 (04) : E18 - E25