COVID-19: BGS statement on research for older people during the COVID-19 pandemic

Position paper
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Authors:
British Geriatrics Society
Date Published:
30 March 2020
Last updated: 
01 April 2020

Research is an essential part of the global and UK strategy and response to COVID-19. This is the British Geriatrics Society's statement on research for older people during the COVID-19 pandemic.

1. In studies describing the clinical trajectories of patients with COVID-19:

  • Frailty should be described using:
    • The Clinical Frailty Scale for studies collecting new empirical data directly from patients.
    • The Electronic Frailty Index for studies using routinely collected data in the community.
    • The Hospital Frailty Risk Score for studies using routinely collected data in hospitals.
    • A calculated Frailty Index for studies based on remote completion of questionnaire data (postal, telephone, internet-based).
       
  • Delirium should be detected using the 4AT.
     
  • Cognition should be measured using the 4-point version of the Abbreviated Mental Test (AMT-4). Where a more sensitive or specific test is required, one that is both in wide clinical usage and relatively brief should be deployed. Where possible, an estimate of pre-morbid cognition should be taken with the Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE).
     
  • Functional status should be measured using the widely used 20-point Barthel Index for basic activities of daily living, and the Nottingham Extended Activities of Daily Living Index for instrumental activities of daily living.

2. Older people, including those with frailty, should be included in in clinical trials of treatments or interventions for COVID-19 that may subsequently be used in older populations with frailty.

3. It is important that issues apart from COVID-specific illness trajectory and treatments for the virus are investigated. Important areas for study include:

a. How prophylactic measures (including behaviour strategies, vaccines and pharmacological strategies) can reduce the risk of acquiring COVID-19 infection.

b. How COVID-19 infection may cause or worsen comorbid conditions, with a particular focus on multimorbidity and frailty.

c. How health and social care resources are used by those with COVID-19 and those with other health issues during the COVID pandemic.

d. How older patients’ functional status is affected by COVID-19 infection, how their muscle function is affected, how they recover, and the role of rehabilitation interventions in promoting recovery.

e. How older patients’ cognitive status is affected by COVID-19 infection and the role of cognitive rehabilitation interventions in promoting recovery across the continuum of care.

f. How older people respond physiologically to COVID-19 infection, especially with regard the ageing immune system, and how this may lead to stratified treatments or influence future immunisation strategies.

g. Advance Care Planning approaches employed during the pandemic and how these influence uptake rates.

h. How care homes and healthcare professionals, volunteers and community groups work together to manage the COVID-19 pandemic in the community.

i. How older people work to overcome social isolation during the pandemic.

j. How clinical teams have harnessed existing and new technology to co-ordinate care whilst remaining social distancing.

k. How peer-support, debriefing and other measures influence health and social care staff performance during the pandemic.

l. How to best to provide end of life care to those older people with frailty who are not fit enough for intensive treatment.

m. How does evidence from existing rehabilitation research contribute to our understanding of how to use rehabilitation to help older people recover from COVID-related illness.

4. Any studies undertaken during the pandemic period must use the most parsimonious approach to data collection available. This will be a very busy time for care staff and patients will often be anxious as a consequence of the pandemic. Even more so than usual, every piece of data collected within research must have a very robust justification and routinely collected healthcare data should be used wherever possible. Efforts should be made to encourage accurate coding of primary diagnoses and comorbidities on healthcare records to maximise the usefulness of routine data.

Most health and social care research in the UK has stopped or made major changes to research processes due to the COVID-19 pandemic. This is due to the inherent risks of virus transmission through face-to-face contact in research studies, necessary redeployment of research staff and resources to support the NHS as it responds to the pandemic, and Universities around the country closing down in response to social distancing measures.

Research is, however, a central plank of the global and UK response to COVID-19. The Department of Health and Social Care outlines four components in their COVID-19 strategy: 1. Contain; 2. Delay; 3. Research; 4. Mitigate. Research is not an optional extra – it is absolutely essential in the national response to this emergency.

Older people with frailty, multimorbidity and physical dependency are particularly vulnerable to COVID-19 and are less likely to benefit from intensive medical treatment if they become unwell. They also frequently live in environments, such as retirement villages or care homes, which may put them at increased risk from COVID outbreaks, because of the close proximity in which older people with multimorbidity and frailty live in these settings. Moreover, the immune system, and response to infection, changes with age – and this may explain why older people are at risk for more severe complications.

The British Geriatrics Society believes strongly that older people should be included in clinical research into the COVID pandemic, particularly because they are those with the highest probability of becoming very unwell as a consequence of infection. We believe that if multiple studies adhere to shared principles around how to research COVID-19 in older people, the impact of work undertaken will be multiplied.

It is essential for clinical teams to support research into COVID-19, and how health and wellbeing are influenced by COVID-19. By learning more about this understudied virus and the clinical conditions it causes, we will be able to reduce its impact and mitigate some of its more damaging effects, as well as providing evidence that may be transferable to other situations.

This document outlines, in brief, some core considerations when conducting research in this group during this time.

In order for research into COVID-19 to be both ethical and feasible it is important that studies adopt the most parsimonious approach to data collection possible. This will ensure that staff are able to support research data collection and that research will not unduly detract from care delivery during a time of high demand on health and social care.

Routinely collected clinical data should be used, wherever possible, to enable clinical staff to get on with their jobs without interference. We recommend avoiding face-to-face contact wherever possible to reduce risk to older study participants and research staff. Use of postal questionnaires, telephone and internet-based questionnaire completion is especially important for community-based studies.

For each of the measures outlined below, the BGS can signpost researchers to expert advisors. Please get in touch using the contact box at the bottom of this page if further advice is required.
 

The concept of frailty has already come under some scrutiny during the COVID-19 pandemic as it has been the focus of NICE guidance around escalation decisions in critical care.1 This is based upon evidence that older people with frailty do less well in most clinical scenarios, including intensive care, and the desire to base clinical decision making upon something more substantial than patient age alone. Yet data on how frailty influences presentations, clinical trajectories and response to supportive interventions in COVID-19 infection are very limited. Collating data on frailty is therefore an essential component of all clinical studies in the area, including to better inform national guidance about escalation and treatment decisions.

Frailty describes vulnerability to poor resolution of homoeostasis after a stressor event.2 A number of frailty indices are available and this can be potentially baffling.

In studies collecting new empirical data directly from patients, we advocate the use of the Clinical Frailty Scale (CFS)3. The CFS is a 9 point scale based upon clinical descriptors which has been shown have reasonable intra- and inter-rater reliability and to be predictive of outcomes in a number of clinical populations. It is part of the recently published NICE guidance about critical care escalations decisions.1 

The CFS can be found at: https://www.bgs.org.uk/sites/default/files/content/attachment/2018-07-05/rockwood_cfs.pdf

For studies using routinely collected data in primary care, we recommend the electronic Frailty Index (eFI).4 The eFI is an automated, nationally recommended, frailty index, which can be calculated on all GP computer systems in use in the UK. It is now well validated as being predictive of outcomes in clinical populations. It has the advantage of being highly standardised and already available through GP systems. It is generated electronically so does not require a face-to-face assessment by a researcher, reducing potential risk to participants. Standardised scripts for extracting eFI scores from practices using SystmOne and EMISWeb Electronic Health Records have been developed for use in research studies. It can be used for research studies analysing routine primary care electronic health record databases including CPRD, SAIL, ResearchOne and THIN.

For studies using routinely collected data in hospital populations, we advocate the use of the Hospital Frailty Risk Score.5 It has the same advantages that the eFI has in the community but has been specifically developed and validated for use in hospitals.

Scripts to generate Hospital Frailty Risk Scores have been written in SAS and are available open-access at: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(18)30668-8/fulltext

For remote postal questionnaire studies, a Frailty Index can be generated if sufficient variables of the right type are included. This has been done as part of the English Longitudinal Study of Ageing6 and Community Ageing Research 75+ Study.7 The BGS is happy to connect interested researchers with academics experienced in this field.

Delirium describes a neuropsychiatric syndrome which is usually triggered by underlying medical illness or drugs.8 It is commonly precipitated by infections in older people and may be present in at least 20% of all hospitalised patients.

Delirium can be a presenting feature and can complicate management of COVID-19 infections in older people. Because COVID-19 is new, the clinical trajectory of delirium in patients with this condition is unstudied.

To understand the relationship between COVID-19 and delirium, we need to be able to detect delirium accurately with a standard assessment. For this purpose, we recommend that researchers use the 4AT.9 This is brief, well-validated tool in widespread clinical and research use. The 4AT can be used in the initial detection of possible delirium, at other points in the care journey where delirium is suspected, and to assist in monitoring for recovery.

The 4AT can be downloaded from: http://www.the4AT.com

Dementia is common in older people in the UK, affecting over 20% of those over 80 and 30% of those over 90.10 Cognitive impairment interacts with frailty and is a risk factor for delirium. It can modify how people interact with and respond to clinical management. In addition, people with cognitive impairment are a vulnerable group, particularly in hospital, and it is important to ensure that they are not disadvantaged in their access to treatment on the basis of cognitive impairment alone.

The most economical way to measure cognition is using the 4 point version of the Abbreviated Mental Test (AMT-4).11 This is included in the 4-AT and if 4-AT is recorded in research records by individual domains, as well as a total score, then this records the AMT-4.

Where greater sensitivity and specificity are required, we recommend using a widely available test that is in regular clinical usage. In the UK this is likely to be one of the Montreal Cognitive Assessment (MoCA),12 the Mini Mental State Examination (MMSE)13 and mini-Addenbrookes Cognitive Examination (M-ACE)14 which are widely used around the country. The rationale is that these clinical diagnostic tools are already likely be used in clinical settings and additional training will not be required. They are all relatively brief.

Informant-based tools are very effective in detecting previously undiagnosed dementia. They involve asking an informant about the person’s cognition and general functioning whilst stable, in the period before an acute illness. This is helpful in determining if post-infection cognitive decline is new or was present before the illness.

We recommend the 5-minute Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for this purpose: https://rsph.anu.edu.au/research/tools-resources/informant-questionnaire-cognitive-decline-elderly

Levels of functional dependency at the onset of illness may influence how older people respond to COVID-19. Older people with differing baseline exposures may respond differently in terms of functional decline as illness progresses. Understanding how abilities, and disability, interact with multimorbidity and frailty, will be key to teasing out risk profiles for decompensation and recovery of older people affected by COVID-19. Such observations could enable us, in time, to provide more personalised recommendations on access to treatment.

We recommend the use of the 20-point version of the Barthel Index for basic activities of daily living,15 most relevant in highly dependent populations, and the Nottingham Extended Activities of Daily Living (NEADL)16 Index for instrumental activities of daily living, more useful in more independent populations. We have chosen these because they are both well validated and in widespread clinical use. Both have been used as postal questionnaires in the past. The Barthel Index can be found at: https://www.albertahealthservices.ca/assets/about/scn/ahs-scn-bjh-hf-barthel-index-of-adls.pdf.

As treatments for COVID-19 start to emerge, including vaccines, clinical trials will be necessary. Older people, particularly those with frailty and functional dependency, are frequently excluded from clinical trials on a number of grounds. Comorbidities and treatments used for them can confound analysis of treatment effect.

It is important that older people, including those with frailty, are included in studies of interventions for COVID-19, where it is eventually intended that these interventions will be used in older patient groups. For these trials, we recommend assessment of participant frailty at baseline, using the methods outlined previously, to enable investigation of differential treatment response and outcomes across the frailty spectrum. The rationale for this is that immune responses, physiological responses, and clinical trajectories, including functional recovery rates, differ in older people with frailty. The clinical efficacy of treatments in patients most affected with the virus cannot be understood without the inclusion of such groups in trials.

It is unacceptable to use age as an exclusion criterion for clinical studies; such an approach is unethical, particularly in conditions such as COVID-19 infection that older people suffer from disproportionately.

It is likely that much of the research proposed around COVID-19 will be biomedical in nature and focussed predominantly around better understanding the acute clinical course of the illness to enable treatment approaches to be developed. There are, though, a number of important areas for research which we outline here, which should not be neglected during this pandemic. These are:

  • How prophylaxis measures (including behaviour strategies and pharmacological strategies) can reduce the risk of acquiring COVID-19 infection.
  • How COVID-19 infection may cause or worsen comorbid conditions, with a particular focus on multimorbidity and frailty.
  • How older patients’ functional status is affected by COVID-19 infection, how their muscle function is affected, how they recover, and the role of rehabilitation interventions in promoting recovery.
  • How health and social care resources are used by those with COVID-19 and those with other health issues during the COVID pandemic.
  • How older patients’ cognitive status is affected by COVID-19 infection and the role of cognitive rehabilitation interventions in promoting recovery across the continuum of care.
  • How older people respond physiologically to COVID-19 infection, especially with regard to the ageing immune system, and how this may lead to stratified treatments or influence future immunisation strategies.
  • Advance Care Planning approaches employed during the pandemic and how these influence uptake rates.
  • How care homes and healthcare professionals, volunteers and community groups have worked together to manage the COVID-19 pandemic in the community.
  • How older people work to overcome social isolation during the pandemic.
  • How clinical teams harness existing and new technology to co-ordinate care whilst maintaining social distancing.
  • How peer support, debriefing and other measures influence health and social care staff performance during the pandemic.
  • How best to provide end of life care to those older people with frailty who are not fit enough for critical care treatment, and who deteriorate despite ward-based supportive care.
  • How does evidence from existing rehabilitation research contribute to our understanding of how to use rehabilitation to help older people recover from COVID-related illness.
  1. National Institute of Clinical Excellence. COVID-19 rapid guideline: critical care in adult, available online at https://www.nice.org.uk/guidance/ng159
  2. Clegg A, Young J, Iliffe S, et al. Frailty in elderly people. Lancet 2013;381:752–62.
  3. Rockwood K, Song X, MacKnight C, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ;173:489–95.
  4. Clegg A, Bates C, Young J, et al. Development and validation of an electronic frailty index using routine primary care electronic health record data. Age Ageing 2016;45:353–60.
  5. Gilbert T, Neuburger J, Kraindler J, et al. Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study. Lancet 2018;391:1775–82.
  6. Marshall A, Nazroo J, Tampubolon G, et al. Cohort differences in the levels and trajectories of frailty among older people in England. J Epidemiol Community Health 2015;69:316–21.
  7. Heaven A, Brown L, Young J, et al. Community ageing research 75+ study (CARE75+): An experimental ageing and frailty research cohort. BMJ Open 2019;9:e026744.
  8. Jackson TA, Gladman JRF, Harwood RH, et al. Challenges and opportunities in understanding dementia and delirium in the acute hospital. PLOS Med 2017;14:e1002247.
  9. Shenkin SD, Fox C, Godfrey M, et al. Delirium detection in older acute medical inpatients: A multicentre prospective comparative diagnostic test accuracy study of the 4AT and the confusion assessment method. BMC Med 2019;17:138.
  10. Alzheimer’s Society. Dementia UK: Second Report, available online at http://eprints.lse.ac.uk/59437/1/Dementia_UK_Second_edition_-_Overview.pdf. 2014
  11. Swain DG, Nightingale PG. Evaluation of a shortened version of the Abbreviated Mental Test in a series of elderly patients. Clin Rehabil 1997;11:243–8.
  12. Hobson J. The Montreal Cognitive Assessment (MoCA). Occup Med (Chic Ill) 2015;65:764–764.
  13. Folstein MF, Folstein SE, McHugh PR. ‘Mini-mental state’ : A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189–98.
  14. Miranda DDC, Brucki SMD, Yassuda MS. The mini-addenbrooke’s cognitive examination (M-ACE) as a brief cognitive screening instrument in mild cognitive impairment and mild Alzheimer’s disease. Dement e Neuropsychol 2018;12:368–73.
  15. Wade DT, Collin C. The Barthel ADL Index: a standard measure of physical disability? Int Disabil Stud 1988;10:64–7.
  16. Nicholl CR, Lincoln NB, Playford ED. The reliability and validity of the Nottingham Extended Activities of Daily Living Scale in patients with multiple sclerosis. Mult Scler 2002;8:372–6.

Acknowledgements

With very many thanks to the expert author group who assembled this guidance for the British Geriatrics Society:

  • Prof Adam L Gordon
    Professor of the Care of Older People, University of Nottingham; Vice President (Academic Affairs), British Geriatrics Society

  • Dr Atul Anand
    CSO Clinical Lecturer and Geriatric Specialist Registrar, University of Edinburgh
  • Prof Andy Clegg
    Professor of Geriatric Medicine, University of Leeds; Consultant Geriatrician, Bradford Teaching Hospitals NHS Foundation Trust
  • Prof Simon Conroy
    Professor of Geriatric Medicine, University of Leicester
  • Dr Richard Dodds
    Clinical Intermediate Fellow, AGE Research Group, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University
  • Prof John Gladman
    Professor of Medicine of Older People, School of Medicine, University of Nottingham
  • Prof Rowan Harwood
    Professor of Palliative and End of Life Care, School of Health Sciences, University of Nottingham
  • Dr Jonathan Hewitt
    Clinical Senior Lecturer, Division of Population Medicine Cardiff University
  • Dr Thomas Jackson
    Clinician Scientist in Geriatric Medicine, Institute of Inflammation and Ageing, University of Birmingham
  • Prof Alasdair Maclullich
    Professor of Geriatric Medicine, University of Edinburgh
  • Prof Avan Aihie Sayer
    William Leech Professor of Geriatric Medicine, AGE Research Group, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University; Director, NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle upon Tyne Hospitals NHS Foundation Trust
  • Dr Susan Shenkin
    Senior Clinical Lecturer, Geriatric Medicine & Usher Institute, University of Edinburgh; NRS (NHS Research Scotland) Ageing Specialty Lead
  • Prof Helen Roberts
    Professor of Medicine for Older People, University of Southampton
  • Prof Miles Witham
    Professor of Trials for Older People, NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle upon Tyne Hospitals; NIHR Ageing Clinical Research Network National Specialty Lead
  • Prof Vicki Goodwin
    Associate Professor of Ageing and Rehabilitation, College of Medicine and Health, University of Exeter; Ageing Clinical Research Network Speciality Lead (South West Peninsula)
  • Prof Sallie Lamb
    Mireille Gillings Professor of Health Innovation, College of Medicine and Health, University of Exeter

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