We have described the clinical features and inpatient trajectory of older inpatients with clinically confirmed COVID-19 admitted as an emergency to an NHS University Hospital in England. Our findings confirm the range of symptoms other than fever, cough and breathlessness which are common presenting features of COVID-19 infection in this population group. Furthermore, we found that presenting features differed by level of frailty, with frail patients much more likely to present with new or worsening confusion, falls and non-specific illness and less likely to present with fever and cough than non-frail older adults. This is in keeping with other studies [14, 31] and characterises the ‘typical atypical’ way in which older patients, particularly those living with frailty, often present with acute illness.
In particular, new or worsening confusion was present in 36.9% of all patients on admission rising to 45.1% of frail patients. In total 57.0% of frail patients experienced new or worsening confusion at some point during their admission episode, either formally diagnosed as delirium or noted as a symptom by the healthcare team caring for the patient. High prevalence of delirium associated with COVID-19 infection has been identified in other studies  yet local and national guidelines often fail to emphasise the importance of delirium as a potential indicator of COVID-19 illness . Therefore, our findings on the prevalence of delirium and the range of other presenting features of COVID-19 in older adults, support recommendations which suggest lower thresholds for COVID-19 testing  in this population group during periods of significant community viral transmission.
Overall in hospital mortality was 34.6% which reflects the severity of the disease and the older age of our population and is similar to mortality reported in other studies [22–23]. Frail patients were more likely to die than non-frail patients and a dose response relationship was observed between frailty and mortality which persisted after adjustment for age, sex, illness acuity and multimorbidity. This finding has not been consistent across all recent reports, with some supporting our findings [22, 33] and others either equivocal  or failing to find an association . Intuitively, we would expect to find an association between a clinical syndrome such as frailty, which is defined by the presence of low physiological reserve and ‘vulnerability’, and mortality from an acute severe viral illness such as COVID-19. Differing study results to date may reflect small sample sizes and it is likely that large multicentre studies or meta-analyses will be required to resolve this issue. Interestingly, results from the COPE study, which includes over 1500 patients with COVID-19 from several centres across the United Kingdom and Italy, support an association between higher frailty and higher mortality from COVID-19 .
There is considerable interest in understanding more about the pathogenesis of COVID-19 and pathways to mortality. We observed that 28.5% of our patient cohort had a normal CXR around the time of COVID-19 presentation and only 34.6% had classic or probable CXR features suggestive of the disease. This is similar to a study in 64 younger patients (mean age of 56 years) which showed 31% of them having normal baseline CXRs . Therefore, since the initial CXR may be normal in COVID-19 , a negative result does not exclude COVID-19 illness and CXR results should only be used for clinical decision making in context of the clinical presentation . We also note that this observation was exaggerated in frail patients, with only around 1 in 4 patients having classical or probable CXR changes on presentation compared to 1 in 2 older adults without frailty. This could reflect the underlying vulnerability of frail patients, who may be less able to compensate for the effects of COVID-19 illness and present before the radiological features of lung inflammation have developed. However, it could also indicate that the manifestations of the illness differ by level of frailty.
Other reports have suggested that there may be differences in the physiological response to COVID-19 infection by frailty status. For example, another cohort study found inflammatory responses blunted in frail patients presenting with COVID-19 compared to non-frail patients . This is consistent with our findings in relation to CRP and IL-6 which were significantly higher in non-frail patients compared to frail patients; it is possible that frail older adults are not able to mount strong immune responses to COVID-19 infection due to immunosenescence . Higher inflammatory responses to COVID-19 have been associated with severe disease and poorer outcomes , and dexamethasone, an immunosuppressant therapy, has been proven to reduce mortality in patients with COVID-19 requiring oxygen therapy or mechanical ventilation . Therefore, if immune reactions differ in frail compared to non-frail older adults this may suggest the pathogenesis of COVID-19 differs by frailty and will have implications for the likely effectiveness of different treatments. It is also possible, as with the differences in CXR features, that frail patients are simply presenting earlier in their illness trajectory due to lower physiological reserve than non-frail patients and hence have lower levels of inflammatory markers on presentation. However, we also note that higher proportions of frail older adults in our cohort presented with raised HsTNI levels compared to non-frail older adults, and there was a non-significant trend for higher total white blood cell count driven by higher neutrophils. These findings hint at potential alternative pathological consequences of COVID-19 infection in older adults with frailty, with cardiac complications and bacterial superinfection perhaps more likely eventual causes of death than high levels of systemic inflammation.
Our data did not show a statistical difference in the LOS between frail and non-frail patients, unlike other studies , although there was a trend in this direction and frail patients were more likely to stay in hospital beyond their clinically fit date than non-frail patients. Delayed transfer of care has been previously observed in association with frailty and likely reflects difficulties in sourcing social care or accessing onward care facilities, such as inpatient rehabilitation centres and care homes . Consistent with this, frail patients had lower mobility on discharge than non-frail patients and a higher proportion were discharged to a new institution, although this finding did not reach statistical significance. A limitation in our assessment of hospital outcomes other than mortality was the smaller sample size, after taking into account those who died during the inpatient episode.
Non-frail patients were more likely to be admitted to the high dependency unit or intensive care unit compared to frail patients (29% vs 0.7%, p < 0.001). This suggests that in our centre, decisions regarding admissions to critical care were considered appropriately in our cohort in keeping with NICE guidelines . It should be noted, however, decisions on access to critical care or mechanical ventilation for older adults overall should remain individualized and take into consideration patients’ preference and goals of care .
Our study has some limitations. It is a single-centre, retrospective, observational study of inpatients in England, hence our results may not be generalisable to the whole population. For example, the older population in Cambridge is a highly homogenous demographic consisting mostly of individuals of White ethnicity. The impact of ethnicity on the morbidity and mortality of this disease has been widely reported [41, 42] but we were not able to add to this. The sample size was also relatively small, thus limiting the potential to detect differences between frail and non-frail patients, particularly with respect to secondary outcome measures such as hospital readmission, where the sample size was further reduced. Additionally, only routinely collected data were used and our definition of frailty and cognition were limited by the tools which are available locally at our centre. Furthermore, some patients were not assessed by their treating team for frailty, necessitating retrospective scoring. This was done by physicians experienced in frailty assessment using information about the patient documented in the EHR on admission by medical and therapy professionals. However, it is possible that retrospective scoring introduced bias, for example if the scorer was aware of the outcome status.
The absence of CFS in some of our patients, necessitating retrospective scoring, was partly due to the inclusion of patients 65 years and above in our study whereas routine frailty scoring in our centre is only mandated for patients aged 75 years and over. However, it may also suggest the unfamiliarity of some clinicians with this scoring system, though widespread. As a result of changes to workforce organisation in preparation for the pandemic, many clinicians who were not familiar with modern geriatric medicine practices were incorporated into acute medicine and general medicine rotas. Additionally, therapy teams such as our hospital’s Early Intervention Team who routinely assess older patients on admission to hospital were temporarily re-deployed. Given the known associations of frailty with outcomes such as mortality, new institutionalisation and prolonged hospital stay in general medical patients , and the emerging evidence of the association of frailty with atypical presentations of COVID-19 and higher mortality following COVID-19 infection, the current pandemic is an opportunity for local educational and quality improvement work to increase awareness of frailty, its clinical assessment and implications for patient care .
The main strengths of our study are that it offers a detailed description of the clinical presentation, laboratory profile and inpatient trajectory of a cohort of hospitalised older adults with COVID-19 and includes a description of these patients by level of frailty. Data was retrieved digitally from the EHR or manually using a standardised data collection tool and missing data was limited. Also, the use of an EHR system in our hospital enabled clinicians to review patient medical records remotely and data was retrieved without the need for research staff to enter clinical areas which could increase the risk of infection.