a Emergency Department, University Hospital Basel, University of Basel, Switzerland
b Intensive Care Unit, University Hospital Basel, University of Basel, Switzerland
Age, comorbidity and frailty
As of now, studies on COVID‐19 have consistently shown that older age and comorbidity are major risk factors for adverse outcomes and mortality [1–3]. However, it is unknown which of these components has the strongest prognostic power for prediction of adverse health outcomes in COVID-19, because there is a substantial overlap between them . Atypical disease presentation in older adults may contribute to an unfavourable course of disease [5, 6]. Nursing home residents appear to be particularly at risk for adverse outcomes from COVID-19 [7, 8], especially if requiring mechanical ventilation . It can be speculated that this increased vulnerability is due to a high frailty prevalence in nursing home facilities .
Not all older adults appear to be equally vulnerable to COVID-19. A recent case series presented five patients aged 98 years and older who recovered from COVID-19 and were discharged from hospital, being China’s oldest COVID-19 survivors .
On the other hand, frail older adults have an increased vulnerability to such a stressor event – they tend to be more seriously affected by acute disease in general and they often do not regain their baseline level of health and independence, as compared with non-frail older adults of the same age group . To date, there is no consensus on a frailty definition and the two most relevant concepts are the phenotype model and the cumulative deficit model [12, 13].
There is evidence that frailty status by itself is as predictive of adverse outcomes as older age in several different conditions including pneumonia (see table 1 for summary, for systematic review see ).
|Sample size||Outcomes||Frailty assessment tool||Effect of frailty independent of age?|
|CPR of in-patients ||Median: 74||Included: 179|
|Survival to discharge:|
|Clinical Frailty Scale. Frailty defined as CFS levels 6 to 9.||Yes (logistic regression analysis)|
|Emergency surgical patients ||Median: 54||Included: 2279|
|Mortality at day 30 (adjusted OR):|
CFS 1: reference
CFS 5: 2.24
CFS 6: 3.78
CFS 7: 22.33
|7-Point Clinical Frailty Scale. Frailty defined as CFS levels 5 to 7.||Yes (logistic regression analysis)|
|Geriatric trauma ||Mean: 78||Included: 250|
|In-hospital mortality, primary outcome (unadjusted):|
Discharge to skilled nursing facility or in-hospital mortality (adjusted OR):
|Frailty defined as|
Frailty Index ≥0.25.
|Yes (logistic regression analysis)|
|Pneumonia ||Mean: 79||Included: 270,308|
High HFRS: 11.5%
Intermediate HFRS: 55.2%
Low HFRS: 33.4%
|Mortality at day 30 (adjusted OR):|
HFRS low risk: reference
HFRS intermediate risk: 2.08
HFRS high risk: 2.45
|Hospital Frailty Risk Score (HFRS).|
Low risk HFRS <5,
Intermediate risk HFRS 5–15
High risk HFRS >15
|Yes (logistic regression analysis)|
|Sepsis ||Mean: 65 (estimated)||Included: 30,239|
Sepsis cases: 1479
|30-day case fatality (adjusted OR):|
1 indicator: 1.05
2 indicators: 1.53
3 indicators: 2.03
|Frailty defined by the presence of at least 2 frailty indicators (weakness, exhaustion, low physical activity)||Yes (logistic regression analysis)|
|Critically ill patients ||Mean: 67||Included: 421|
|Clinical Frailty Scale. Frailty defined as CFS levels 5 to 8.||Yes (logistic regression analysis)|
|COVID-19 in Italy ||NA||Included: 22,512||Case fatality rate:|
Age 0–29: 0%
Age 30–39: 0.3%
Age 40–49: 0.4%
Age 50–59: 1.0%
Age 60–69: 3.5%
Age 70–79: 12.8%
Age ≥80: 20.2%
|Not assessed||Not tested|
|COVID-19 in China ||Median: 47||Included: 1099|
Age ≥65: 15.1%
Age <65: 84.9%
|Composite outcome (ICU admission, mechanical ventilation, death):|
Age ≥65: 49.2%
Age <65: 25.4%
|Not assessed||Not tested|
To determine frailty status, several tools have been developed. The Clinical Frailty Scale (CFS)  is an easy-to-use screening tool for frailty. A pictograph and a short clinical description help to assign scores from 1 (very fit) to 9 (terminally ill). The CFS score should be based on the person’s baseline status, for example, 2 weeks ago. The CFS is a predictor for in-hospital mortality independent of age and gender [15, 22, 23] and was recently validated in a consecutive sample of patients aged 65 years and older in an emergency department (ED) setting . Early determination of frailty status, preferably during ED triage, could therefore be useful to identify older adults who may benefit from a comprehensive geriatric assessment . In addition, it could assist disposition decisions  and possibly resource allocation, particularly at times of high patient influx, such as during the current COVID-19 pandemic. Disposition in this context means the decision for either discharge, admission or transfer after ED triage and work-up.
Disposition decisions during the COVID-19 pandemic
Admission to acute medicine or transfer to geriatric medicine should not be based simply on age. On the contrary, the balance between frailty status and disease acuity/severity should be gauged individually, with consideration of the patients’ preferences and goals of care. The combination of the CFS with an aggregated vital sign score as a marker of acute illness severity appears to improve outcome prediction . Disposition decisions must take outcome prediction into account  as, for example, unexpected death after ED discharge should not occur, and in a situation of very high acuity/severity transfer to the intensive care unit has to be considered.
Resource allocation during the COVID-19 pandemic
Resource allocation should be based on concepts similar to those of disposition decisions, because short-term prognosis and the patients’ preferences and goals of care are the cornerstones of vitally important choices. “Left digit bias” (e.g., patients admitted 2 weeks after their 80th birthday were less likely to undergo bypass surgery than patients admitted 2 weeks before ) must affect neither disposition nor resource allocation. Whereas disposition decisions should ideally be independent of available resources, they pose an even greater challenge in times of resource scarcity due to COVID-19. Although age and comorbidity are considered to be important outcome predictors in Swiss  and Italian  guidelines on resource allocation, frailty intensive care assessment (with the Clinical Frailty Scale) has so far only been endorsed by guidelines of the UK National Institute for Health and Care Excellence (NICE) , as well as the guidelines of the German Society of Intensive Care .
Due to the lack of data in the present COVID-19 pandemic, we can only speculate that frailty status, rather than chronological age, largely determines outcome in patients with COVID-19. However, in many other conditions, this has already been demonstrated (table 1).
As suggested by Canadian experts [34, 35], three aspects are of utmost importance: first, determination of frailty status (and not just the patient’s age), second, balancing of benefits and harms while considering the most likely outcome taking comorbidity into account, and third, shared decision-making focusing on the individual’s goals of care.
Thanks to all ED and ICU staff of the Basel University Hospital, particularly Thomas Dreher, as well as Florian Grossmann, and Anja Ulrich from the Department of Internal Medicine, for support with implementation of the Clinical Frailty Scale and helping to make our ED more senior-friendly. Acknowledgements and thanks go to Manuel Battegay for continuous input and helpful discussions.
No financial support and no other potential conflict of interest relevant to this article was reported.
Header image: © Rido | Dreamstime.com
Christian Nickel, MD, Emergency Department, University Hospital Basel, University of Basel, Petersgraben 2, CH-4031 Basel, christian.nickel[at]usb.ch
1 Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al.Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395(10229):1054–62. doi:. http://dx.doi.org/10.1016/S0140-6736(20)30566-3 PubMed
2 Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al.; China Medical Treatment Expert Group for Covid-19. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020:NEJMoa2002032. doi:. http://dx.doi.org/10.1056/NEJMoa2002032 PubMed
3 Onder G, Rezza G, Brusaferro S. Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy. JAMA. Published online March 23 2020. doi:. http://dx.doi.org/10.1001/jama.2020.4683 PubMed
6 Hofman MR, van den Hanenberg F, Sierevelt IN, Tulner CR. Elderly patients with an atypical presentation of illness in the emergency department. Neth J Med. 2017;75(6):241–6. PubMed
7 McMichael TM, Currie DW, Clark S, Pogosjans S, Kay M, Schwartz NG, et al.Epidemiology of Covid-19 in a Long-Term Care Facility in King County, Washington. N Engl J Med. 2020:NEJMoa2005412. doi:. http://dx.doi.org/10.1056/NEJMoa2005412 PubMed
8 Arons MM, Hatfield KM, Reddy SC, Kimball A, James A, Jacobs JR, et al.Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility. N Engl J Med. 2020:NEJMoa2008457. doi:. http://dx.doi.org/10.1056/NEJMoa2008457 PubMed
9 Arentz M, Yim E, Klaff L, Lokhandwala S, Riedo FX, Chong M, et al.Characteristics and Outcomes of 21 Critically Ill Patients With COVID-19 in Washington State. JAMA. 2020;323(16):1612. doi:. http://dx.doi.org/10.1001/jama.2020.4326 PubMed
13 Rodríguez-Mañas L, Féart C, Mann G, Viña J, Chatterji S, Chodzko-Zajko W, et al.; The Frailty Operative Definition-Consensus Conference Project. Searching for an operational definition of frailty: a Delphi method based consensus statement. J Gerontol A Biol Sci Med Sci. 2013;68(1):62–7. doi:. http://dx.doi.org/10.1093/gerona/gls119 PubMed
14 Wharton C, King E, MacDuff A. Frailty is associated with adverse outcome from in-hospital cardiopulmonary resuscitation. Resuscitation. 2019;143:208–11. doi:. http://dx.doi.org/10.1016/j.resuscitation.2019.07.021 PubMed
15 Hewitt J, Carter B, McCarthy K, Pearce L, Law J, Wilson FV, et al.Frailty predicts mortality in all emergency surgical admissions regardless of age. An observational study. Age Ageing. 2019;48(3):388–94. doi:. http://dx.doi.org/10.1093/ageing/afy217 PubMed
16 Joseph B, Pandit V, Zangbar B, Kulvatunyou N, Hashmi A, Green DJ, et al.Superiority of frailty over age in predicting outcomes among geriatric trauma patients: a prospective analysis. JAMA Surg. 2014;149(8):766–72. doi:. http://dx.doi.org/10.1001/jamasurg.2014.296 PubMed
17 Kundi H, Wadhera RK, Strom JB, Valsdottir LR, Shen C, Kazi DS, et al.Association of frailty with 30-day outcomes for acute myocardial infarction, heart failure, and pneumonia among elderly adults. JAMA Cardiol. 2019;4(11):1084–91. doi:. http://dx.doi.org/10.1001/jamacardio.2019.3511 PubMed
18 Mahalingam M, Moore JX, Donnelly JP, Safford MM, Wang HE. Frailty Syndrome and Risk of Sepsis in the REasons for Geographic And Racial Differences in Stroke (REGARDS) Cohort. J Intensive Care Med. 2019;34(4):292–300. doi:. http://dx.doi.org/10.1177/0885066617715251 PubMed
19 Bagshaw SM, Stelfox HT, McDermid RC, Rolfson DB, Tsuyuki RT, Baig N, et al.Association between frailty and short- and long-term outcomes among critically ill patients: a multicentre prospective cohort study. CMAJ. 2014;186(2):E95–102. doi:. http://dx.doi.org/10.1503/cmaj.130639 PubMed
20 Vermeiren S, Vella-Azzopardi R, Beckwée D, Habbig AK, Scafoglieri A, Jansen B, et al.; Gerontopole Brussels Study group. Frailty and the Prediction of Negative Health Outcomes: A Meta-Analysis. J Am Med Dir Assoc. 2016;17(12):1163.e1–17. doi:. http://dx.doi.org/10.1016/j.jamda.2016.09.010 PubMed
21 Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, et al.A global clinical measure of fitness and frailty in elderly people. CMAJ. 2005;173(5):489–95. doi:. http://dx.doi.org/10.1503/cmaj.050051 PubMed
22 Basic D, Shanley C. Frailty in an older inpatient population: using the clinical frailty scale to predict patient outcomes. J Aging Health. 2015;27(4):670–85. doi:. http://dx.doi.org/10.1177/0898264314558202 PubMed
24 Kaeppeli T, Rueegg M, Dreher-Hummel T, Brabrand M, Kabell-Nissen S, Carpenter CR, et al.Validation of the Clinical Frailty Scale for Prediction of Thirty-Day Mortality in the Emergency Department. Ann Emerg Med. 2020;S0196-0644(20)30218-3. doi:. http://dx.doi.org/10.1016/j.annemergmed.2020.03.028 PubMed
25 Ellis G, Gardner M, Tsiachristas A, Langhorne P, Burke O, Harwood RH, et al.Comprehensive geriatric assessment for older adults admitted to hospital. Cochrane Database Syst Rev. 2017;9(9):CD006211. doi:. http://dx.doi.org/10.1002/14651858.CD006211.pub3 PubMed
26 Bingisser R, Nickel CH. The last decade of symptom-oriented research in emergency medicine: triage, work-up, and disposition. Swiss Med Wkly. 2019;149:w20141. doi:. http://dx.doi.org/10.4414/smw.2019.20141 PubMed
27 Romero-Ortuno R, Wallis S, Biram R, Keevil V. Clinical frailty adds to acute illness severity in predicting mortality in hospitalized older adults: An observational study. Eur J Intern Med. 2016;35:24–34. doi:. http://dx.doi.org/10.1016/j.ejim.2016.08.033 PubMed
28 Kellett J, Nickel CH, Skyttberg N, Brabrand M. Is it possible to quickly identify acutely unwell patients who can be safely managed as outpatients? The need for a “Universal Safe to Discharge Score”. Eur J Intern Med. 2019;67:e13–5. doi:. http://dx.doi.org/10.1016/j.ejim.2019.07.018 PubMed
30 Scheidegger D, Fumeaux T, Hurst S, Salathé M; Swiss Academy of Medical Sciences. Covid-19-Pandemic: Intensive care medicine: triage in case of bottlenecks. 2020. https://www.samw.ch/en/Ethics/Topics-A-to-Z/Intensive-care-medicine.html.
31 Vergano MBG, Giannini A, Mascarin S, Iacobone E, Giubbilo I, Bonfanti S, et al.; Italian Society of Anesthesia, Analgesia, Resuscitation, and Intensive Care (SIAARTI). Clinical Ethics Recommendations for the Allocation of Intensive Care Treatments, in Exceptional, Resource-Limited Circumstances. [cited 2020 April 16]. http://www.siaarti.it/News/COVID19%20-%20documenti%20SIAARTI.aspx.
32 National Institute for Health and Care Excellence. COVID-19 rapid guideline: critical care in adults. 2020. https://www.nice.org.uk/guidance/ng159.
33 Jochen Dutzmann CH, Janssens U, Jöbges S, Knochel K, Marckmann G, Michalsen A, et al. Entscheidungen über die Zuteilung von Ressourcen in der Notfall-und der Intensivmedizin im Kontext der COVID-19-Pandemie. 2020 [cited 2020 April 20]. https://www.divi.de/empfehlungen/publikationen/covid-19/1540-covid-19-ethik-empfehlung-v2/file..
34 Boreskie KF, Boreskie PE, Melady D. Age is just a number - and so is frailty: Strategies to inform resource allocation during the COVID-19 pandemic. CJEM. 2020:1–3. doi:. http://dx.doi.org/10.1017/cem.2020.358 PubMed
35 Montero-Odasso M, Goens SD, Kamkar N, Lam R, Madden K, Molnar F, et al.Canadian Geriatrics Society COVID-19 Recommendations for Older Adults. What Do Older Adults Need To Know?Can Geriatr J. 2020;23(1):149–51. doi:. http://dx.doi.org/10.5770/cgj.23.443 PubMed
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