Sir,
Wang and colleagues recently reported in this journal the characteristics and prognostic factors of novel coronavirus 2019 (COVID-19) disease in 339 patients over 60 years of age presenting to Renmin Hospital of Wuhan University in Wuhan, China.1 This highlighted the higher case fatality rate in this patient group with 19.2% dying within 30 days and frequent comorbidities including hypertension, diabetes and cardiovascular disease. Numerous other case series of hospitalised patients in China have provided valuable insight into the clinical features of disease, risk factors for severity and case fatality rate. These have informed diagnostic criteria, treatment strategies and public health policy worldwide. In the largest of these, patients over 65 years of age represented 27% of patients with severe disease and 49.2% of patients admitted to the intensive care unit.2 To date there has been limited clinical data published outside of China and none from the epidemic in the UK which is estimated to be now nearing its peak (14th April 2020). It is anticipated that age and the frequency of co-existing comorbidities in the UK population are likely to be strong drivers of outcome of and mortality in patients hospitalised with COVID-19 disease.
Here, we describe a retrospective single-centre study of all patients hospitalised with SARS-COV-2 infection from March 10th to March 30th within North Bristol NHS Trust, a large, regional teaching hospital in the UK. During this period, 95 cases were admitted to the trust and by the final day of follow up on April 6th, 21 patients (21%) had died, 44 patients (43%) had been discharged, and 30 (29%) were still inpatients. Of the 21 patients that died, 20 died within 14 days suggesting that most mortality occurs within two weeks. 7 patients were admitted to the intensive care unit, of whom 4 had died by the 6th of April, and 3 remained in intensive care. Length of stay for patients who were discharged from hospital was a median of 4 days (IQR 1–16), for those that died 8 days (IQR 6–9) and for those that remained inpatients 9 days (IQR 3–23). Longer length of stay was influenced by the timing of a positive test, which for 23 patients (24%) was more than 7 days after admission. Fifteen patients (16%) had a negative test preceding the positive result indicating some delay in diagnosis due to false negative results.
The demographics, symptoms, radiology, laboratory findings and comorbidities of our patient group are presented in Tables 1 and 2 . The median age of patients was similar in both patients alive at 14 days and those that had died, at 74 and 77 respectively. No differences by gender were observed, but there were more men in the study overall (63%). Cardiovascular and cerebrovascular disease was significantly more common in those that had died by 14 days (90% vs 48%) and of these; congestive cardiac failure was the most notably associated with non-survival (35% vs 11%). Diabetes was also significantly more common in those that had died at 14 days (65% vs 32%) whilst respiratory disease was equally distributed between the two groups (30% vs 33%).The most common symptoms were fever (72%) cough (74%) and shortness of breath (43%), followed by confusion (20%). Two patients presented with anosmia. This has recently been recognised as an early clinical feature in European patients3 and may be underrepresented in our cohort due to the frequency of advanced disease and confusion. Shortness of breath was the only symptom that was significantly more common in patients that died within 14 days (p = 0.013).
Table 1.
Patient demographics, comorbidities and symptoms.
Characteristic | N = 951 | Alive N = 751 | Dead N = 201 | p-value2 |
---|---|---|---|---|
Age | 75 (59, 82) | 74 (56, 82) | 77 (72, 85) | 0.062 |
Gender | >0.9 | |||
F | 35 (37%) | 27 (36%) | 8 (40%) | |
M | 60 (63%) | 48 (64%) | 12 (60%) | |
Comorbidities | ||||
All Cardiovascular disease | 54 (57%) | 36 (48%) | 18 (90%) | 0.002 |
Hypertension | 35 (37%) | 24 (32%) | 11 (55%) | 0.10 |
Ischaemic heart disease | 21 (22%) | 14 (19%) | 7 (35%) | 0.14 |
Cardiac failure | 15 (16%) | 8 (11%) | 7 (35%) | 0.014 |
Arrhythmia | 13 (14%) | 10 (13%) | 3 (15%) | >0.9 |
Valve disease | 6 (6.3%) | 6 (8.0%) | 0 (0%) | 0.3 |
Cerebrovascular | 8 (8.4%) | 6 (8.0%) | 2 (10%) | 0.7 |
All Respiratory disease | 31 (33%) | 25 (33%) | 6 (30%) | >0.9 |
Asthma | 21 (22%) | 17 (23%) | 4 (20%) | >0.9 |
COPD | 10 (11%) | 6 (8.0%) | 4 (20%) | 0.2 |
Bronchiectasis | 1 (1.1%) | 1 (1.3%) | 0 (0%) | >0.9 |
Obstructive Sleep Apnoea | 8 (8.4%) | 6 (8.0%) | 2 (10%) | 0.7 |
Gastrointestinal disease | 11 (12%) | 8 (11%) | 3 (15%) | 0.7 |
Endocrine disease | 6 (6.3%) | 4 (5.3%) | 2 (10%) | 0.6 |
Diabetes | 37 (39%) | 24 (32%) | 13 (65%) | 0.015 |
Malignancy | 20 (21%) | 17 (23%) | 3 (15%) | 0.6 |
Neurological disease | 14 (15%) | 11 (15%) | 3 (15%) | >0.9 |
Renal disease | 22 (23%) | 16 (21%) | 6 (30%) | 0.6 |
Immunocompromised | 1 (1.1%) | 1 (1.3%) | 0 (0%) | >0.9 |
Symptoms | ||||
Fever | 68 (72%) | 56 (75%) | 12 (60%) | 0.3 |
Cough | 70 (74%) | 56 (75%) | 14 (70%) | 0.9 |
Shortness of breath | 41 (43%) | 27 (36%) | 14 (70%) | 0.013 |
Myalgia | 13 (14%) | 12 (16%) | 1 (5.0%) | 0.3 |
Confusion | 20 (21%) | 16 (21%) | 4 (20%) | >0.9 |
Seizure | 1 (1.1%) | 1 (1.3%) | 0 (0%) | >0.9 |
Headache | 9 (9.5%) | 9 (12%) | 0 (0%) | 0.2 |
Sore throat | 6 (6.3%) | 6 (8.0%) | 0 (0%) | 0.3 |
Chest pain | 7 (7.4%) | 6 (8.0%) | 1 (5.0%) | >0.9 |
Diarrhoea | 11 (12%) | 7 (9.3%) | 4 (20%) | 0.2 |
Nausea and vomiting | 13 (14%) | 9 (12%) | 4 (20%) | 0.5 |
Abdominal pain | 5 (5.3%) | 4 (5.3%) | 1 (5.0%) | >0.9 |
Constipation | 4 (4.2%) | 4 (5.3%) | 0 (0%) | 0.6 |
Anosmia | 3 (3.2%) | 3 (4.0%) | 0 (0%) | >0.9 |
Statistics presented: median (IQR); n (%).
Statistical tests performed: Wilcoxon rank-sum test; chi-square test of independence; Fisher's exact test.
Table 2.
Patient laboratory, imaging findings and respiratory support.
Characteristic | Normal Range | N = 951 | Alive N = 751 | Dead N = 201 | p-value2 |
---|---|---|---|---|---|
C-reactive protein (mg/L) | <6 | 42 (18, 86) | 36 (14, 67) | 77 (53, 124) | 0.001 |
Not measured | 3 | 3 | 0 | ||
Lymphocytes (x109/L) | 1–4 | 0.79 (0.54, 1.23) | 0.81 (0.52, 1.22) | 0.73 (0.55, 1.26) | 0.9 |
Not measured | 3 | 3 | 0 | ||
Neutrophil:Lymphocyte Ratio | 6 (3, 11) | 6 (3, 11) | 7 (4, 11) | 0.6 | |
Not measured | 3 | 3 | 0 | ||
Ferritin (ug/L) | 33–490 | 557 (235, 974) | 493 (184, 948) | 816 (592, 1706) | 0.4 |
Not measured | 68 | 54 | 14 | ||
Alanine aminotransferase (U/L) | 10–60 | 26 (19, 37) | 26 (19, 38) | 28 (17, 37) | 0.7 |
Not measured | 17 | 17 | 0 | ||
Albumin (g/L) | 35–50 | 31 (26, 34) | 32 (27, 36) | 30 (24, 32) | 0.024 |
Not measured | 16 | 16 | 0 | ||
Troponin T (ng/L) | <14 | 25 (15, 65) | 23 (15, 61) | 31 (19, 66) | 0.5 |
Not measured | 60 | 50 | 10 | ||
Creatinine (umol/L) | 45–84 | 98 (69, 138) | 87 (66, 120) | 117 (102, 151) | 0.014 |
Not measured | 3 | 3 | 0 | ||
Chest-X Ray Findings | 0.008 | ||||
Bilateral Consolidation | 24 (27%) | 14 (20%) | 10 (50%) | ||
Unilateral Consolidation | 25 (28%) | 18 (26%) | 7 (35%) | ||
No Consolidation | 31 (34%) | 28 (40%) | 3 (15%) | ||
Not Performed | 10 (11%) | 10 (14%) | 0 (0%) | ||
CURB65+ Score | 0.001 | ||||
0 | 11 (14%) | 11 (18%) | 0 (0%) | ||
1 | 16 (21%) | 16 (27%) | 0 (0%) | ||
2 | 29 (38%) | 22 (37%) | 7 (41%) | ||
3 | 15 (19%) | 7 (12%) | 8 (47%) | ||
4 | 5 (6.5%) | 3 (5.0%) | 2 (12%) | ||
5 | 1 (1.3%) | 1 (1.7%) | 0 (0%) | ||
Not calculable | 18 | 15 | 3 | ||
Respiratory support: | <0.001 | ||||
Non-invasive ventilation | 10 (10.5%) | 4 (5.5%) | 6 (30%) | ||
Invasive ventilation | 6 (6.3%) | 3 (4.1%) | 3 (15%) | ||
Oxygen | 38 (40%) | 27 (37%) | 11 (55%) | ||
None | 39 (41%) | 39 (53%) | 0 (0%) |
Statistics presented: median (IQR); n (%).
Statistical tests performed: Wilcoxon rank-sum test; Fisher's exact test.
We found significantly higher CRP and creatinine in those that died in keeping with progressive inflammation and end organ damage. Median lymphocyte count was low in both groups, ALT was raised in 5 patients and Ferritin was > 2000 in 6 patients but was performed infrequently and showed no significant difference between survivors and non-survivors. We found little evidence of viral or bacterial co-infection with rhinovirus and human metapneumovirus in 2 of the 88 patients tested and one significant respiratory isolate (K. oxytoca). However, sputum culture and testing for Legionella and Pneumococcal antigens was performed infrequently. There were 3 positive blood cultures (D. hominis, S. aureus and E. faecium) none of which were felt to be respiratory in origin. 55 patients received antibiotic therapy, including 20 of the 21 patients that died and 2 patients received antivirals (Aciclovir for suspected meningoencephalitis). Consistent with evidence supporting the use of CURB65 as a predictor of mortality secondary to community acquired pneumonia4 we found a significantly higher median score in non-survivors versus survivors (2.5 versus 1 respectively). Patients who did not survive were more likely to have chest X-ray findings, and in particular, were more likely to have bilateral consolidation than unilateral. 40% of survivors did not have any radiological evidence of consolidation. Only 6 patients had a CT chest performed which may be useful in detecting early disease in patients that test negative by rtRT-PCR.5
To our knowledge, this is the first description of a UK cohort of patients with SARS-COV-2 infection and the largest descriptive study of the infection outside of China. We found a much higher median age and case fatality rate than that reported by other studies of all hospitalised patients with COVID-19. All the patients that died were over the age of 60 and only 4 were admitted to intensive care. Given the current availability of beds and ventilatory equipment in the hospital during this study this does not represent deficiencies of medical care. Rather it suggests that there was an anticipated deterioration in these patients in the context of poor premorbid state, and planned decision making around intensive care unit admission. NICE guidance published during this period endorsed the use of a Clinical Frailty Scale (CFS) Score in the assessment for critical care admission which has been shown to perform better than evaluation of cognitive function or comorbidity in estimating risk of death and has been validated in intensive care outcomes.6, 7 Further assessment of its application to the COVID-19 pandemic is required and may be instrumental in guiding further public health policy, particularly in areas with a low prevalence where the suspension of health care services such as cancer services may be detrimental to other preventable health outcomes. In summary, despite limited stress on our health care service, around 20% of our hospitalised population died, with the majority dying outside intensive care with significant comorbidities. Further work is needed to characterise other UK cohorts.
Acknowledgments
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
References
- 1.Lang Wang, Wenbo He, Xiaomei Yu, Dalong Hu, Mingwei Bao, Huafen Liu. Coronavirus Disease 2019 in elderly patients: characteristics and prognostic factors based on 4-week follow-up. J Infect. 2020 doi: 10.1016/j.jinf.2020.03.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Wei-Jie Guan, Zheng-Yi Ni, Yu Hu, Wen-Hua Liang, Chun-Quan Ou, Jian-Xing He. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020 doi: 10.1056/nejmoa2002032. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Lechien Jerome R., Chiesa-Estomba Carlos M., De Siati Daniele R., Mihaela Horoi, Le Bon Serge D., Alexandra Rodriguez. Olfactory and gustatory dysfunctions as a clinical presentation of mild-to-moderate forms of the coronavirus disease (COVID-19): a multicenter European study. Eur Arch Otorhinolaryngol. 2020 doi: 10.1007/s00405-020-05965-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Chalmers James D., Aran Singanayagam, Akram Ahsan R., Pallavi Mandal, Short Philip M., Gourab Choudhury. Severity assessment tools for predicting mortality in hospitalised patients with community-acquired pneumonia. Systematic review and meta-analysis. Thorax. 2010;65(10):878–883. doi: 10.1136/thx.2009.133280. [DOI] [PubMed] [Google Scholar]
- 5.Felix Chua, Darius Armstrong-James, Desai Sujal R., Joseph Barnett, Vasileios Kouranos, Min Kon Onn. The role of CT in case ascertainment and management of COVID-19 pneumonia in the UK: insights from high-incidence regions. Lancet Respir Med. 2020 doi: 10.1016/S2213-2600(20)30132-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Kenneth Rockwood, Xiaowei Song, Chris MacKnight, Howard Bergman, Hogan David B., Ian McDowell. A global clinical measure of fitness and frailty in elderly people. CMAJ. 2005;173(5):489–495. doi: 10.1503/cmaj.050051. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.John Muscedere, Braden Waters, Aditya Varambally, Bagshaw Sean M., Gordon Boyd J., David Maslove. The impact of frailty on intensive care unit outcomes: a systematic review and meta-analysis. Intensive Care Med. 2017;43(8):1105–1122. doi: 10.1007/s00134-017-4867-0. [DOI] [PMC free article] [PubMed] [Google Scholar]