bims-covirf 2020-08-30 papers

bims-covirf

Biomed News

on COVID19 risk factors

Issue of 2020‒08‒30
ten papers selected by
Catherine Rycroft
BresMed

Predictors of COVID-19 severity: A literature review.
Risk factors for Covid-19 severity and fatality: a structured literature review.
Features of severe COVID-19: A systematic review and meta-analysis.
Association of cardiovascular disease and 10 other pre-existing comorbidities with COVID-19 mortality: A systematic review and meta-analysis.
Comorbidity and its Impact on Patients with COVID-19.
Disparities in the excess risk of mortality in the first wave of COVID-19: cross sectional study of the English sentinel network.
Patient Characteristics and Outcomes of 11,721 Patients with COVID19 Hospitalized Across the United States.
Sex Differences in Age and Comorbidities for COVID-19 Mortality in Urban New York City.
The association of race and COVID-19 mortality.
COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: a prospective cohort study.

Rev Med Virol. 2020 Jul 30. e2146

Predictors of COVID-19 severity: A literature review.

Benjamin Gallo Marin, Ghazal Aghagoli, Katya Lavine, Lanbo Yang, Emily J Siff, Silvia S Chiang, Thais P Salazar-Mather, Luba Dumenco, Michael C Savaria, Su N Aung, Timothy Flanigan, Ian C Michelow.

  The coronavirus disease 2019 (COVID-19) pandemic is a rapidly evolving global emergency that continues to strain healthcare systems. Emerging research describes a plethora of patient factors-including demographic, clinical, immunologic, hematological, biochemical, and radiographic findings-that may be of utility to clinicians to predict COVID-19 severity and mortality. We present a synthesis of the current literature pertaining to factors predictive of COVID-19 clinical course and outcomes. Findings associated with increased disease severity and/or mortality include age > 55 years, multiple pre-existing comorbidities, hypoxia, specific computed tomography findings indicative of extensive lung involvement, diverse laboratory test abnormalities, and biomarkers of end-organ dysfunction. Hypothesis-driven research is critical to identify the key evidence-based prognostic factors that will inform the design of intervention studies to improve the outcomes of patients with COVID-19 and to appropriately allocate scarce resources.

Keywords:  COVID‐19; SARS‐CoV‐2; predictors; severity

DOI:  https://doi.org/10.1002/rmv.2146
Infection. 2020 Aug 28.

Risk factors for Covid-19 severity and fatality: a structured literature review.

Dominik Wolff, Sarah Nee, Natalie Sandy Hickey, Michael Marschollek.

  PURPOSE: Covid-19 is a global threat that pushes health care to its limits. Since there is neither a vaccine nor a drug for Covid-19, people with an increased risk for severe and fatal courses of disease particularly need protection. Furthermore, factors increasing these risks are of interest in the search of potential treatments. A systematic literature review on the risk factors of severe and fatal Covid-19 courses is presented.METHODS: The review is carried out on PubMed and a publicly available preprint dataset. For analysis, risk factors are categorized and information regarding the study such as study size and location are extracted. The results are compared to risk factors listed by four public authorities from different countries.
RESULTS: The 28 records included, eleven of which are preprints, indicate that conditions and comorbidities connected to a poor state of health such as high age, obesity, diabetes and hypertension are risk factors for severe and fatal disease courses. Furthermore, severe and fatal courses are associated with organ damages mainly affecting the heart, liver and kidneys. Coagulation dysfunctions could play a critical role in the organ damaging. Time to hospital admission, tuberculosis, inflammation disorders and coagulation dysfunctions are identified as risk factors found in the review but not mentioned by the public authorities.
CONCLUSION: Factors associated with increased risk of severe or fatal disease courses were identified, which include conditions connected with a poor state of health as well as organ damages and coagulation dysfunctions. The results may facilitate upcoming Covid-19 research.

Keywords:  Covid-19; Population at risk; Review; Risk factors; SARS-CoV-2

DOI:  https://doi.org/10.1007/s15010-020-01509-1
Eur J Clin Invest. 2020 Aug 09. e13378

Features of severe COVID-19: A systematic review and meta-analysis.

Francesco Del Sole, Alessio Farcomeni, Lorenzo Loffredo, Roberto Carnevale, Danilo Menichelli, Tommasa Vicario, Pasquale Pignatelli, Daniele Pastori.

  BACKGROUND: To systematically review clinical and biochemical characteristics associated with the severity of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related disease (COVID-19).MATERIALS AND METHODS: Systematic review of observational studies from PubMed, ISI Web of Science, SCOPUS and Cochrane databases including people affected by COVID-19 and reporting data according to the severity of the disease. Data were combined with odds ratio (OR) and metanalysed. Severe COVID-19 was defined by acute respiratory distress syndrome, intensive care unit admission and death.
RESULTS: We included 12 studies with 2794 patients, of whom 596 (21.33%) had severe disease. A slightly higher age was found in severe vs non-severe disease. We found that prevalent cerebrovascular disease (odds ratio [OR] 3.66, 95% confidence interval [CI] 1.73-7.72), chronic obstructive pulmonary disease (OR: 2.39, 95% CI 1.10-5.19), prevalent cardiovascular disease (OR: 2.84, 95% CI 1.59-5.10), diabetes (OR: 2.78, 95% CI 2.09-3.72), hypertension (OR: 2.24, 95% CI 1.63-3.08), smoking (OR: 1.54, 95% CI 1.07-2.22) and male sex (OR: 1.22, 95% CI 1.01-1.49) were associated with severe disease. Furthermore, increased procalcitonin (OR: 8.21, 95% CI 4.48-15.07), increased D-Dimer (OR: 5.67, 95% CI 1.45-22.16) and thrombocytopenia (OR: 3.61, 95% CI 2.62-4.97) predicted severe infection.
CONCLUSION: Characteristics associated with the severity of SARS-CoV-2 infection may allow an early identification and management of patients with poor outcomes.

Keywords:  SARS-CoV-2; d-dimer; infection; procalcitonin; severity; sex; thrombocytopenia

DOI:  https://doi.org/10.1111/eci.13378
PLoS One. 2020 ;15(8): e0238215

Association of cardiovascular disease and 10 other pre-existing comorbidities with COVID-19 mortality: A systematic review and meta-analysis.

Paddy Ssentongo, Anna E Ssentongo, Emily S Heilbrunn, Djibril M Ba, Vernon M Chinchilli.

BACKGROUND: Estimating the risk of pre-existing comorbidities on coronavirus disease 2019 (COVID-19) mortality may promote the importance of targeting populations at risk to improve survival. This systematic review and meta-analysis aimed to estimate the association of pre-existing comorbidities with COVID-19 mortality.METHODS: We searched MEDLINE, SCOPUS, OVID, and Cochrane Library databases, and medrxiv.org from December 1st, 2019, to July 9th, 2020. The outcome of interest was the risk of COVID-19 mortality in patients with and without pre-existing comorbidities. We analyzed 11 comorbidities: cardiovascular diseases, hypertension, diabetes, congestive heart failure, cerebrovascular disease, chronic kidney disease, chronic liver disease, cancer, chronic obstructive pulmonary disease, asthma, and HIV/AIDS. Two reviewers independently extracted data and assessed the risk of bias. All analyses were performed using random-effects models and heterogeneity was quantified.
RESULTS: Eleven pre-existing comorbidities from 25 studies were included in the meta-analysis (n = 65, 484 patients with COVID-19; mean age; 61 years; 57% male). Overall, the between-study heterogeneity was medium, and studies had low publication bias and high quality. Cardiovascular disease (risk ratio (RR) 2.25, 95% CI = 1.60-3.17, number of studies (n) = 14), hypertension (1.82 [1.43 to 2.32], n = 13), diabetes (1.48 [1.02 to 2.15], n = 16), congestive heart failure (2.03 [1.28 to 3.21], n = 3), chronic kidney disease (3.25 [1.13 to 9.28)], n = 9) and cancer (1.47 [1.01 to 2.14), n = 10) were associated with a significantly greater risk of mortality from COVID-19.
CONCLUSIONS: Patients with COVID-19 with cardiovascular disease, hypertension, diabetes, congestive heart failure, chronic kidney disease and cancer have a greater risk of mortality compared to patients with COVID-19 without these comorbidities. Tailored infection prevention and treatment strategies targeting this high-risk population might improve survival.

DOI: https://doi.org/10.1371/journal.pone.0238215
SN Compr Clin Med. 2020 Jun 25. 1-8

Comorbidity and its Impact on Patients with COVID-19.

Adekunle Sanyaolu, Chuku Okorie, Aleksandra Marinkovic, Risha Patidar, Kokab Younis, Priyank Desai, Zaheeda Hosein, Inderbir Padda, Jasmine Mangat, Mohsin Altaf.

  A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in Wuhan, China, in December 2019. Since then, the virus has made its way across the globe to affect over 180 countries. SARS-CoV-2 has infected humans in all age groups, of all ethnicities, both males and females while spreading through communities at an alarming rate. Given the nature of this virus, there is much still to be learned; however, we know that the clinical manifestations range from a common cold to more severe diseases such as bronchitis, pneumonia, severe acute respiratory distress syndrome (ARDS), multi-organ failure, and even death. It is believed that COVID-19, in those with underlying health conditions or comorbidities, has an increasingly rapid and severe progression, often leading to death. This paper examined the comorbid conditions, the progression of the disease, and mortality rates in patients of all ages, infected with the ongoing COVID-19 disease. An electronic literature review search was performed, and applicable data was then collected from peer-reviewed articles published from January to April 20, 2020. From what is known at the moment, patients with COVID-19 disease who have comorbidities, such as hypertension or diabetes mellitus, are more likely to develop a more severe course and progression of the disease. Furthermore, older patients, especially those 65 years old and above who have comorbidities and are infected, have an increased admission rate into the intensive care unit (ICU) and mortality from the COVID-19 disease. Patients with comorbidities should take all necessary precautions to avoid getting infected with SARS CoV-2, as they usually have the worst prognosis.

Keywords:  COVID-19; Clinical features; Comorbidity; Coronavirus; Diabetes; Hypertension; SARS-CoV-2

DOI:  https://doi.org/10.1007/s42399-020-00363-4
J Infect. 2020 Aug 25. pii: S0163-4453(20)30564-8. [Epub ahead of print]

Disparities in the excess risk of mortality in the first wave of COVID-19: cross sectional study of the English sentinel network.

Simon de Lusignan, Mark Joy, Jason Oke, Dylan McGagh, Brian Nicholson, James Sheppard, Oluwafunmi Akinyemi, Gayatri Amirthalingam, Kevin Brown, Rachel Byford, Gavin Dabrera, Else Krajenbrink, Harshana Liyanage, Jamie LopezBernal, Cecilia Okusi, Mary Ramsay, Julian Sherlock, Mary Sinnathamby, Ruby S M Tsang, Victoria Tzortziou Brown, John Williams, Maria Zambon, Filipa Ferreira, Gary Howsam, Richard Hobbs.

  OBJECTIVES: Few studies report contributors to the excess mortality in England during the first wave of coronavirus disease 2019 (COVID-19) infection. We report the absolute excess risk (AER) of mortality and excess mortality rate (EMR) from a nationally representative COVID-19 sentinel surveillance network including known COVID-19 risk factors in people aged 45 years and above.METHODS: Pseudonymised, coded clinical data were uploaded from contributing primary care providers (N=1,970,314, ≥45years). We calculated the AER in mortality by comparing mortality for weeks 2 to 20 this year with mortality data from the Office for National Statistics (ONS) from 2018 for the same weeks. We conducted univariate and multivariate analysis including preselected variables. We report AER and EMR, with 95% confidence intervals (95% CI).
RESULTS: The AER of mortality was 197•8/10,000 person years (95%CI:194•30-201•40) . The EMR for male gender, compared with female, was 1.4 (95%CI:1•35-1•44, p<0•00); for our oldest age band (≥75 years) 10•09 (95%CI:9•46-10•75, p<0•00) compared to 45-64 year olds; Black ethnicity's EMR was 1.17 (95%CI: 1•03-1•33, p<0•02), reference white; and for dwellings with ≥9 occupants 8•01 (95%CI: 9•46-10•75, p<0•00). Presence of all included comorbidities significantly increased EMR. Ranked from lowest to highest these were: hypertension, chronic kidney disease, chronic respiratory and heart disease, and cancer or immunocompromised.
CONCLUSIONS: The absolute excess mortality was approximately 2 deaths per 100 person years in the first wave of COVID-19. More personalised shielding advice for any second wave should include ethnicity, comorbidity and household size as predictors of risk.

Keywords:  General Practice; Medical record systems, computerized; Mortality; Sentinel Surveillance

DOI:  https://doi.org/10.1016/j.jinf.2020.08.037
Clin Infect Dis. 2020 Aug 28. pii: ciaa1268. [Epub ahead of print]

Patient Characteristics and Outcomes of 11,721 Patients with COVID19 Hospitalized Across the United States.

Michael W Fried, Julie M Crawford, Andrea R Mospan, Stephanie E Watkins, Breda Munoz Hernandez, Richard C Zink, Sherry Elliott, Kyle Burleson, Charles Landis, K Rajender Reddy, Robert S Brown.

  BACKGROUND: As COVID-19 disseminates throughout the US, a better understanding of patient characteristics associated with hospitalization, morbidity and mortality in diverse geographic regions is essential.METHODS: Hospital chargemaster data on adult patients with COVID-19 admitted to 245 hospitals across 38 states between February 15 and April 20, 2020 were assessed. Clinical course from admission through hospitalization to discharge or death was analyzed.
RESULTS: A total of 11,721 patients were included (majority were >60 years of age [59.9%] and male [53.4%]). Comorbidities included hypertension (46.7%), diabetes (27.8%), cardiovascular disease (18.6%), obesity (16.1%), and chronic kidney disease (12.2%). Mechanical ventilation was required by 1,967 patients (16.8%). Mortality among hospitalized patients was 21.4% and increased to 70.5% among those on mechanical ventilation. Male sex, older age, obesity, geographic region, and the presence of chronic kidney disease or preexisting cardiovascular disease were associated with an increased odds of mechanical ventilation. All aforementioned risk factors, with the exception of obesity, were associated with an increased odds of death (all p& 0.001). Many patients received investigational medications for treatment of COVID-19, including 48 patients on remdesivir and 4,232 on hydroxychloroquine.
CONCLUSION: This large observational cohort describes the clinical course and identifies factors associated with outcomes of hospitalized patients with COVID-19 across the US. These data can inform strategies to prioritize prevention and treatment for this disease.

Keywords:  COVID-19; SARS-CoV-2; hydroxychloroquine; observational study; remdesivir

DOI:  https://doi.org/10.1093/cid/ciaa1268
SN Compr Clin Med. 2020 Aug 09. 1-4

Sex Differences in Age and Comorbidities for COVID-19 Mortality in Urban New York City.

Eyal Klang, Shelly Soffer, Girish Nadkarni, Ben Glicksberg, Robert Freeman, Carol Horowitz, David L Reich, Matthew A Levin.

  Previous studies demonstrated a higher COVID-19 fatality rate in men. The aim of this study was to compare age and comorbidities between women and men who died from COVID-19. We retrospectively analyzed data of COVID-19 patients hospitalized to a large academic hospital system in New York City between March 1 and May 9, 2020. We used a multivariable logistic regression model to identify independently significant variables associated with gender in patients who died from COVID-19. The model was adjusted for age and comorbidities known to be associated with COVID-19 mortality. We identified 6760 patients diagnosed with COVID-19. Of these patients, 3018/6760 (44.6%) were women. The mortality rate was higher for men (women 18.2% vs. men 20.6%, p = 0.039). Of the patients who died, women were on average 5 years older than men (woman 77.4 ± 12.7 vs. men 72.4 ± 13.0, p < 0.001). In the multivariable model, cardiovascular comorbidities were not significantly different between women and men. Chronic kidney disease (aOR for women 0.7, 95% CI 0.5-0.9) and smoking (aOR for women 0.7, 95% CI 0.5-0.9) were more common in men. Age decile (aOR for women 1.4, 95% CI 1.3-1.6) and obesity (aOR for women 2.3, 95% CI 1.8-3.0) were higher in women. This study demonstrates that women who died of COVID-19 showed a similar cardiovascular disease profile as men. Yet, they are 5 years older than men. Investigating the gender impacts of COVID-19 is an important part of understanding the disease behavior.

Keywords:  COVID-19; Comorbidities; Coronavirus; Mortality; Sex

DOI:  https://doi.org/10.1007/s42399-020-00430-w
EClinicalMedicine. 2020 Jul 15. 100455

The association of race and COVID-19 mortality.

Ladan Golestaneh, Joel Neugarten, Molly Fisher, Henny H Billett, Morayma Reyes Gil, Tanya Johns, Milagros Yunes, Michele H Mokrzycki, Maria Coco, Keith C Norris, Hector R Perez, Shani Scott, Ryung S Kim, Eran Bellin.

  Background: COVID-19 mortality disproportionately affects the Black population in the United States (US). To explore this association a cohort study was undertaken.Methods: We assembled a cohort of 505,992 patients receiving ambulatory care at Bronx Montefiore Health System (BMHS) between 1/1/18 and 1/1/20 to evaluate the relative risk of hospitalization and death in two time-periods, the pre-COVID time-period (1/1/20-2/15/20) and COVID time-period (3/1/20-4/15/20). COVID testing, hospitalization and mortality were determined with the Black and Hispanic patient population compared separately to the White population using logistic modeling. Evaluation of the interaction of pre-COVID and COVID time periods and race, with respect to mortality was completed.
Findings: A total of 9,286/505,992 (1.8%) patients were hospitalized during either or both pre-COVID or COVID periods. Compared to Whites the relative risk of hospitalization of Black patients did not increase in the COVID period (p for interaction=0.12). In the pre- COVID period, compared to Whites, the odds of death for Blacks and Hispanics adjusted for comorbidity was statistically equivalent. In the COVID period compared to Whites the adjusted odds of death for Blacks was 1.6 (95% CI 1.2-2.0, p = 0.001). There was a significant increase in Black mortality risk from pre-COVID to COVID periods (p for interaction=0.02). Adjustment for relevant clinical and social indices attenuated but did not fully explain the observed difference in Black mortality.
Interpretation: The BMHS COVID experience demonstrates that Blacks do have a higher mortality with COVID incompletely explained by age, multiple reported comorbidities and available metrics of sociodemographic disparity.
Funding: N/A.

Keywords:  Covid; Disparity; Hospitalization; Mortality; Race

DOI:  https://doi.org/10.1016/j.eclinm.2020.100455
Lancet Oncol. 2020 Aug 24. pii: S1470-2045(20)30442-3. [Epub ahead of print]

COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: a prospective cohort study.

Lennard Y W Lee, Jean-Baptiste Cazier, Thomas Starkey, Sarah E W Briggs, Roland Arnold, Vartika Bisht, Stephen Booth, Naomi A Campton, Vinton W T Cheng, Graham Collins, Helen M Curley, Philip Earwaker, Matthew W Fittall, Spyridon Gennatas, Anshita Goel, Simon Hartley, Daniel J Hughes, David Kerr, Alvin J X Lee, Rebecca J Lee, Siow Ming Lee, Hayley Mckenzie, Chris P Middleton, Nirupa Murugaesu, Tom Newsom-Davis, Anna C Olsson-Brown, Claire Palles, Thomas Powles, Emily A Protheroe, Karin Purshouse, Archana Sharma-Oates, Shivan Sivakumar, Ashley J Smith, Oliver Topping, Chris D Turnbull, Csilla Várnai, Adam D M Briggs, Gary Middleton, Rachel Kerr, .

BACKGROUND: Patients with cancer are purported to have poor COVID-19 outcomes. However, cancer is a heterogeneous group of diseases, encompassing a spectrum of tumour subtypes. The aim of this study was to investigate COVID-19 risk according to tumour subtype and patient demographics in patients with cancer in the UK.METHODS: We compared adult patients with cancer enrolled in the UK Coronavirus Cancer Monitoring Project (UKCCMP) cohort between March 18 and May 8, 2020, with a parallel non-COVID-19 UK cancer control population from the UK Office for National Statistics (2017 data). The primary outcome of the study was the effect of primary tumour subtype, age, and sex and on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prevalence and the case-fatality rate during hospital admission. We analysed the effect of tumour subtype and patient demographics (age and sex) on prevalence and mortality from COVID-19 using univariable and multivariable models.
FINDINGS: 319 (30·6%) of 1044 patients in the UKCCMP cohort died, 295 (92·5%) of whom had a cause of death recorded as due to COVID-19. The all-cause case-fatality rate in patients with cancer after SARS-CoV-2 infection was significantly associated with increasing age, rising from 0·10 in patients aged 40-49 years to 0·48 in those aged 80 years and older. Patients with haematological malignancies (leukaemia, lymphoma, and myeloma) had a more severe COVID-19 trajectory compared with patients with solid organ tumours (odds ratio [OR] 1·57, 95% CI 1·15-2·15; p<0·0043). Compared with the rest of the UKCCMP cohort, patients with leukaemia showed a significantly increased case-fatality rate (2·25, 1·13-4·57; p=0·023). After correction for age and sex, patients with haematological malignancies who had recent chemotherapy had an increased risk of death during COVID-19-associated hospital admission (OR 2·09, 95% CI 1·09-4·08; p=0·028).
INTERPRETATION: Patients with cancer with different tumour types have differing susceptibility to SARS-CoV-2 infection and COVID-19 phenotypes. We generated individualised risk tables for patients with cancer, considering age, sex, and tumour subtype. Our results could be useful to assist physicians in informed risk-benefit discussions to explain COVID-19 risk and enable an evidenced-based approach to national social isolation policies.
FUNDING: University of Birmingham and University of Oxford.

DOI: https://doi.org/10.1016/S1470-2045(20)30442-3