Literature DB >> 32353384

Clinical features of 95 sequential hospitalised patients with novel coronavirus 2019 disease (COVID-19), the first UK cohort.

Jennifer Tomlins1, Fergus Hamilton2, Samuel Gunning2, Caitlin Sheehy2, Ed Moran2, Alastair MacGowan2.   

Abstract

Entities:  

Mesh:

Year:  2020        PMID: 32353384      PMCID: PMC7184992          DOI: 10.1016/j.jinf.2020.04.020

Source DB:  PubMed          Journal:  J Infect        ISSN: 0163-4453            Impact factor:   6.072


× No keyword cloud information.
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. 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. 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 patients 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.

CharacteristicN = 951Alive N = 751Dead N = 201p-value2
Age75 (59, 82)74 (56, 82)77 (72, 85)0.062
Gender>0.9
 F35 (37%)27 (36%)8  (40%)
 M60 (63%)48 (64%)12 (60%)
Comorbidities
All Cardiovascular disease54 (57%)36 (48%)18 (90%)0.002
 Hypertension35 (37%)24 (32%)11 (55%)0.10
 Ischaemic heart disease21 (22%)14 (19%)7  (35%)0.14
 Cardiac failure15 (16%)8  (11%)7  (35%)0.014
 Arrhythmia13 (14%)10 (13%)3  (15%)>0.9
 Valve disease6  (6.3%)6  (8.0%)0  (0%)0.3
 Cerebrovascular8  (8.4%)6  (8.0%)2 (10%)0.7
All Respiratory disease31 (33%)25 (33%)6  (30%)>0.9
 Asthma21 (22%)17 (23%)4  (20%)>0.9
 COPD10 (11%)6  (8.0%)4  (20%)0.2
 Bronchiectasis1  (1.1%)1  (1.3%)0  (0%)>0.9
 Obstructive Sleep Apnoea8  (8.4%)6  (8.0%)2  (10%)0.7
Gastrointestinal disease11 (12%)8  (11%)3  (15%)0.7
Endocrine disease6  (6.3%)4  (5.3%)2  (10%)0.6
Diabetes37 (39%)24 (32%)13 (65%)0.015
Malignancy20 (21%)17 (23%)3  (15%)0.6
Neurological disease14 (15%)11 (15%)3  (15%)>0.9
Renal disease22 (23%)16 (21%)6  (30%)0.6
Immunocompromised1  (1.1%)1  (1.3%)0  (0%)>0.9
Symptoms
Fever68 (72%)56 (75%)12 (60%)0.3
Cough70 (74%)56 (75%)14 (70%)0.9
Shortness of breath41 (43%)27 (36%)14 (70%)0.013
Myalgia13 (14%)12 (16%)1  (5.0%)0.3
Confusion20 (21%)16 (21%)4  (20%)>0.9
Seizure1  (1.1%)1  (1.3%)0  (0%)>0.9
Headache9  (9.5%)9  (12%)0  (0%)0.2
Sore throat6  (6.3%)6  (8.0%)0  (0%)0.3
Chest pain7  (7.4%)6  (8.0%)1  (5.0%)>0.9
Diarrhoea11 (12%)7  (9.3%)4  (20%)0.2
Nausea and vomiting13 (14%)9  (12%)4  (20%)0.5
Abdominal pain5  (5.3%)4  (5.3%)1  (5.0%)>0.9
Constipation4  (4.2%)4  (5.3%)0  (0%)0.6
Anosmia3  (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.

CharacteristicNormal RangeN = 951Alive N = 751Dead N = 201p-value2
C-reactive protein (mg/L)<642 (18, 86)36 (14, 67)77 (53, 124)0.001
 Not measured330
Lymphocytes (x109/L)1–40.79 (0.54, 1.23)0.81 (0.52, 1.22)0.73 (0.55, 1.26)0.9
 Not measured330
Neutrophil:Lymphocyte Ratio6 (3, 11)6 (3, 11)7 (4, 11)0.6
 Not measured330
Ferritin (ug/L)33–490557 (235, 974)493 (184, 948)816 (592, 1706)0.4
 Not measured685414
Alanine aminotransferase (U/L)10–6026 (19, 37)26 (19, 38)28 (17, 37)0.7
 Not measured17170
Albumin (g/L)35–5031 (26, 34)32 (27, 36)30 (24, 32)0.024
 Not measured16160
Troponin T (ng/L)<1425 (15, 65)23 (15, 61)31 (19, 66)0.5
 Not measured605010
Creatinine (umol/L)45–8498 (69, 138)87 (66, 120)117 (102, 151)0.014
 Not measured330
Chest-X Ray Findings0.008
 Bilateral Consolidation24 (27%)14 (20%)10 (50%)
 Unilateral Consolidation25 (28%)18 (26%)7 (35%)
 No Consolidation31 (34%)28 (40%)3 (15%)
 Not Performed10 (11%)10 (14%)0 (0%)
CURB65+ Score0.001
 011 (14%)11 (18%)0 (0%)
 116 (21%)16 (27%)0 (0%)
 229 (38%)22 (37%)7 (41%)
 315 (19%)7 (12%)8 (47%)
 45 (6.5%)3 (5.0%)2 (12%)
 51 (1.3%)1 (1.7%)0 (0%)
 Not calculable18153
Respiratory support:<0.001
 Non-invasive ventilation10 (10.5%)4 (5.5%)6 (30%)
 Invasive ventilation6 (6.3%)3 (4.1%)3 (15%)
 Oxygen38 (40%)27 (37%)11 (55%)
 None39 (41%)39 (53%)0 (0%)

Statistics presented: median (IQR); n (%).

Statistical tests performed: Wilcoxon rank-sum test; Fisher's exact test.

Patient demographics, comorbidities and symptoms. Statistics presented: median (IQR); n (%). Statistical tests performed: Wilcoxon rank-sum test; chi-square test of independence; Fisher's exact test. Patient laboratory, imaging findings and respiratory support. 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 pneumonia 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. 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.
  7 in total

Review 1.  Severity assessment tools for predicting mortality in hospitalised patients with community-acquired pneumonia. Systematic review and meta-analysis.

Authors:  James D Chalmers; Aran Singanayagam; Ahsan R Akram; Pallavi Mandal; Philip M Short; Gourab Choudhury; Victoria Wood; Adam T Hill
Journal:  Thorax       Date:  2010-08-20       Impact factor: 9.139

2.  A global clinical measure of fitness and frailty in elderly people.

Authors:  Kenneth Rockwood; Xiaowei Song; Chris MacKnight; Howard Bergman; David B Hogan; Ian McDowell; Arnold Mitnitski
Journal:  CMAJ       Date:  2005-08-30       Impact factor: 8.262

3.  Olfactory and gustatory dysfunctions as a clinical presentation of mild-to-moderate forms of the coronavirus disease (COVID-19): a multicenter European study.

Authors:  Jerome R Lechien; Carlos M Chiesa-Estomba; Daniele R De Siati; Mihaela Horoi; Serge D Le Bon; Alexandra Rodriguez; Didier Dequanter; Serge Blecic; Fahd El Afia; Lea Distinguin; Younes Chekkoury-Idrissi; Stéphane Hans; Irene Lopez Delgado; Christian Calvo-Henriquez; Philippe Lavigne; Chiara Falanga; Maria Rosaria Barillari; Giovanni Cammaroto; Mohamad Khalife; Pierre Leich; Christel Souchay; Camelia Rossi; Fabrice Journe; Julien Hsieh; Myriam Edjlali; Robert Carlier; Laurence Ris; Andrea Lovato; Cosimo De Filippis; Frederique Coppee; Nicolas Fakhry; Tareck Ayad; Sven Saussez
Journal:  Eur Arch Otorhinolaryngol       Date:  2020-04-06       Impact factor: 2.503

4.  Clinical Characteristics of Coronavirus Disease 2019 in China.

Authors:  Wei-Jie Guan; Zheng-Yi Ni; Yu Hu; Wen-Hua Liang; Chun-Quan Ou; Jian-Xing He; Lei Liu; Hong Shan; Chun-Liang Lei; David S C Hui; Bin Du; Lan-Juan Li; Guang Zeng; Kwok-Yung Yuen; Ru-Chong Chen; Chun-Li Tang; Tao Wang; Ping-Yan Chen; Jie Xiang; Shi-Yue Li; Jin-Lin Wang; Zi-Jing Liang; Yi-Xiang Peng; Li Wei; Yong Liu; Ya-Hua Hu; Peng Peng; Jian-Ming Wang; Ji-Yang Liu; Zhong Chen; Gang Li; Zhi-Jian Zheng; Shao-Qin Qiu; Jie Luo; Chang-Jiang Ye; Shao-Yong Zhu; Nan-Shan Zhong
Journal:  N Engl J Med       Date:  2020-02-28       Impact factor: 91.245

Review 5.  The impact of frailty on intensive care unit outcomes: a systematic review and meta-analysis.

Authors:  John Muscedere; Braden Waters; Aditya Varambally; Sean M Bagshaw; J Gordon Boyd; David Maslove; Stephanie Sibley; Kenneth Rockwood
Journal:  Intensive Care Med       Date:  2017-07-04       Impact factor: 17.440

6.  The role of CT in case ascertainment and management of COVID-19 pneumonia in the UK: insights from high-incidence regions.

Authors:  Felix Chua; Darius Armstrong-James; Sujal R Desai; Joseph Barnett; Vasileios Kouranos; Onn Min Kon; Ricardo José; Rama Vancheeswaran; Michael R Loebinger; Joyce Wong; Maria Teresa Cutino-Moguel; Cliff Morgan; Stephane Ledot; Boris Lams; Wing Ho Yip; Leski Li; Ying Cheong Lee; Adrian Draper; Sze Shyang Kho; Elisabetta Renzoni; Katie Ward; Jimstan Periselneris; Sisa Grubnic; Marc Lipman; Athol U Wells; Anand Devaraj
Journal:  Lancet Respir Med       Date:  2020-03-25       Impact factor: 30.700

7.  Coronavirus disease 2019 in elderly patients: Characteristics and prognostic factors based on 4-week follow-up.

Authors:  Lang Wang; Wenbo He; Xiaomei Yu; Dalong Hu; Mingwei Bao; Huafen Liu; Jiali Zhou; Hong Jiang
Journal:  J Infect       Date:  2020-03-30       Impact factor: 6.072

  7 in total
  34 in total

1.  Prevalence of Chemosensory Dysfunction in COVID-19 Patients: A Systematic Review and Meta-analysis Reveals Significant Ethnic Differences.

Authors:  Christopher S von Bartheld; Molly M Hagen; Rafal Butowt
Journal:  ACS Chem Neurosci       Date:  2020-09-17       Impact factor: 4.418

Review 2.  COVID-19 and Parkinson's disease: Defects in neurogenesis as the potential cause of olfactory system impairments and anosmia.

Authors:  Harini Sri Rethinavel; Sowbarnika Ravichandran; Risna Kanjirassery Radhakrishnan; Mahesh Kandasamy
Journal:  J Chem Neuroanat       Date:  2021-05-11       Impact factor: 3.052

3.  Predicting outcomes of COVID-19 from admission biomarkers: a prospective UK cohort study.

Authors:  David T Arnold; Marie Attwood; Shaney Barratt; Anna Morley; Karen T Elvers; Jorgen McKernon; Charmaine Donald; Adrian Oates; Alan Noel; Alasdair MacGowan; Nick A Maskell; Fergus W Hamilton
Journal:  Emerg Med J       Date:  2021-05-21       Impact factor: 2.740

4.  Effect of comorbid pulmonary disease on the severity of COVID-19: A systematic review and meta-analysis.

Authors:  Askin Gülsen; Inke R König; Uta Jappe; Daniel Drömann
Journal:  Respirology       Date:  2021-05-06       Impact factor: 6.424

5.  COVID-19 risk: Adult Medicaid beneficiaries with autism, intellectual disability, and mental health conditions.

Authors:  Whitney Schott; Sha Tao; Lindsay Shea
Journal:  Autism       Date:  2021-08-21

6.  Differences in Outcomes and Factors Associated With Mortality Among Patients With SARS-CoV-2 Infection and Cancer Compared With Those Without Cancer: A Systematic Review and Meta-analysis.

Authors:  Emma Khoury; Sarah Nevitt; William Rohde Madsen; Lance Turtle; Gerry Davies; Carlo Palmieri
Journal:  JAMA Netw Open       Date:  2022-05-02

7.  Cerebrovascular disease is associated with the risk of mortality in coronavirus disease 2019.

Authors:  Ying Wang; Li Shi; Yadong Wang; Guangcai Duan; Haiyan Yang
Journal:  Neurol Sci       Date:  2020-06-30       Impact factor: 3.307

8.  Approaches to understanding COVID-19 and its neurological associations.

Authors:  Ettore Beghi; Benedict D Michael; Tom Solomon; Erica Westenberg; Andrea S Winkler
Journal:  Ann Neurol       Date:  2021-04-09       Impact factor: 10.422

9.  Can we predict the severe course of COVID-19 - a systematic review and meta-analysis of indicators of clinical outcome?

Authors:  Stephan Katzenschlager; Alexandra J Zimmer; Claudius Gottschalk; Jürgen Grafeneder; Stephani Schmitz; Sara Kraker; Marlene Ganslmeier; Amelie Muth; Alexander Seitel; Lena Maier-Hein; Andrea Benedetti; Jan Larmann; Markus A Weigand; Sean McGrath; Claudia M Denkinger
Journal:  PLoS One       Date:  2021-07-29       Impact factor: 3.240

Review 10.  COVID-19 and COPD.

Authors:  Janice M Leung; Masahiro Niikura; Cheng Wei Tony Yang; Don D Sin
Journal:  Eur Respir J       Date:  2020-08-13       Impact factor: 16.671

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.