bims-covirf 2021-05-23 papers

Issue of 2021–05–23
six papers selected by
Catherine Rycroft, BresMed

Lancet Reg Health Eur. 2021 Jul;6 100109

Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform.

Background: Mortality from COVID-19 shows a strong relationship with age and pre-existing medical conditions, as does mortality from other causes. We aimed to investigate how specific factors are differentially associated with COVID-19 mortality as compared to mortality from causes other than COVID-19.
Methods: Working on behalf of NHS England, we carried out a cohort study within the OpenSAFELY platform. Primary care data from England were linked to national death registrations. We included all adults (aged ≥18 years) in the database on 1st February 2020 and with >1 year of continuous prior registration; the cut-off date for deaths was 9th November 2020. Associations between individual-level characteristics and COVID-19 and non-COVID deaths, classified according to the presence of a COVID-19 code as the underlying cause of death on the death certificate, were estimated by fitting age- and sex-adjusted logistic models for these two outcomes.
Findings: 17,456,515 individuals were included. 17,063 died from COVID-19 and 134,316 from other causes. Most factors associated with COVID-19 death were similarly associated with non-COVID death, but the magnitudes of association differed. Older age was more strongly associated with COVID-19 death than non-COVID death (e.g. ORs 40.7 [95% CI 37.7-43.8] and 29.6 [28.9-30.3] respectively for ≥80 vs 50-59 years), as was male sex, deprivation, obesity, and some comorbidities. Smoking, history of cancer and chronic liver disease had stronger associations with non-COVID than COVID-19 death. All non-white ethnic groups had higher odds than white of COVID-19 death (OR for Black: 2.20 [1.96-2.47], South Asian: 2.33 [2.16-2.52]), but lower odds than white of non-COVID death (Black: 0.88 [0.83-0.94], South Asian: 0.78 [0.75-0.81]).
Interpretation: Similar associations of most individual-level factors with COVID-19 and non-COVID death suggest that COVID-19 largely multiplies existing risks faced by patients, with some notable exceptions. Identifying the unique factors contributing to the excess COVID-19 mortality risk among non-white groups is a priority to inform efforts to reduce deaths from COVID-19.
Funding: Wellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, Health Data Research UK.

Keywords: COVID-19; Epidemiology; Mortality

DOI: https://doi.org/10.1016/j.lanepe.2021.100109

BMC Geriatr. 2021 05 19. 21(1): 321

Clinical features and outcomes of COVID-19 in older adults: a systematic review and meta-analysis.

Sunny Singhal, Pramod Kumar, Sumitabh Singh, Srishti Saha, Aparajit Ballav Dey.

BACKGROUND: Few studies have focused on exploring the clinical characteristics and outcomes of COVID-19 in older patients. We conducted this systematic review and meta-analysis to have a better understanding of the clinical characteristics of older COVID-19 patients.
METHODS: A systematic search of PubMed and Scopus was performed from December 2019 to May 3rd, 2020. Observational studies including older adults (age ≥ 60 years) with COVID-19 infection and reporting clinical characteristics or outcome were included. Primary outcome was assessing weighted pooled prevalence (WPP) of severity and outcomes. Secondary outcomes were clinical features including comorbidities and need of respiratory support.
RESULT: Forty-six studies with 13,624 older patients were included. Severe infection was seen in 51% (95% CI- 36-65%, I2-95%) patients while 22% (95% CI- 16-28%, I2-88%) were critically ill. Overall, 11% (95% CI- 5-21%, I2-98%) patients died. The common comorbidities were hypertension (48, 95% CI- 36-60% I2-92%), diabetes mellitus (22, 95% CI- 13-32%, I2-86%) and cardiovascular disease (19, 95% CI - 11-28%, I2-85%). Common symptoms were fever (83, 95% CI- 66-97%, I2-91%), cough (60, 95% CI- 50-70%, I2-71%) and dyspnoea (42, 95% CI- 19-67%, I2-94%). Overall, 84% (95% CI- 60-100%, I2-81%) required oxygen support and 21% (95% CI- 0-49%, I2-91%) required mechanical ventilation. Majority of studies had medium to high risk of bias and overall quality of evidence was low for all outcomes.
CONCLUSION: Approximately half of older patients with COVID-19 have severe infection, one in five are critically ill and one in ten die. More high-quality evidence is needed to study outcomes in this vulnerable patient population and factors affecting these outcomes.

Keywords: Comorbidities; Coronavirus; Mortality; Severe illness; Symptoms

DOI: https://doi.org/10.1186/s12877-021-02261-3

J Clin Med Res. 2021 Apr;13(4): 237-244

A Simplified Comorbidity Evaluation Predicting Clinical Outcomes Among Patients With Coronavirus Disease 2019.

Jessica J Kirby, Sajid Shaikh, David P Bryant, Amy F Ho, James P d'Etienne, Chet D Schrader, Hao Wang.

Background: Patients with coronavirus disease 2019 (COVID-19) have shown a range of clinical outcomes. Previous studies have reported that patient comorbidities are predictive of worse clinical outcomes, especially when patients have multiple chronic diseases. We aim to: 1) derive a simplified comorbidity evaluation and determine its accuracy of predicting clinical outcomes (i.e., hospital admission, intensive care unit (ICU) admission, ventilation, and in-hospital mortality); and 2) determine its performance accuracy in comparison to well-established comorbidity indexes.
Methods: This was a single-center retrospective observational study. We enrolled all emergency department (ED) patients with COVID-19 from March 1, 2020, to December 31, 2020. A simplified comorbidity evaluation (COVID-related high-risk chronic condition (CCC)) was derived to predict different clinical outcomes using multivariate logistic regressions. In addition, chronic diseases included in the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI) were scored, and its accuracy of predicting COVID-19 clinical outcomes was also compared with the CCC.
Results: Data were retrieved from 90,549 ED patient visits during the study period, among which 3,864 patients were COVID-19 positive. Forty-seven point nine percent (1,851/3,864) were admitted to the hospital, 9.4% (364) patients were admitted to the ICU, 6.2% (238) received invasive mechanical ventilation, and 4.6% (177) patients died in the hospital. The CCC evaluation correlated well with the four studied clinical outcomes. The adjusted odds ratios of predicting in-hospital death from CCC was 2.84 (95% confidence interval (CI): 1.81 - 4.45, P < 0.001). C-statistics of CCC predicting in-hospital all-cause mortality was 0.73 (0.69 - 0.76), similar to those of the CCI's (0.72) and ECI's (0.71, P = 0.0513).
Conclusions: CCC can accurately predict clinical outcomes among patients with COVID-19. Its performance accuracies for such predictions are not inferior to those of the CCI or ECI's.

Keywords: COVID-19; Clinical outcome; Comorbidity

DOI: https://doi.org/10.14740/jocmr4476

Euro Surveill. 2021 May;26(20):

Epidemiological characteristics and outcomes of COVID-19 cases: mortality inequalities by socio-economic status, Barcelona, Spain, 24 February to 4 May 2020.

COVID-19 Surveillance Working Group of Barcelona

BackgroundPopulation-based studies characterising outcomes of COVID-19 in European settings are limited, and effects of socio-economic status (SES) on outcomes have not been widely investigated. AimWe describe the epidemiological characteristics of COVID-19 cases, highlighting incidence and mortality rate differences across SES during the first wave in Barcelona, Catalonia, Spain.MethodsThis population-based study reports individual-level data of laboratory-confirmed COVID-19 cases diagnosed from 24 February to 4 May 2020, notified to the Public Health Agency of Barcelona and followed until 15 June 2020. We analysed end-of-study vital status and the effects of chronic conditions on mortality using logistic regression. Geocoded addresses were linked to basic health area SES data, estimated using the composed socio-economic index. We estimated age-standardised incidence, hospitalisation, and mortality rates by SES.ResultsOf 15,554 COVID-19-confirmed cases, the majority were women (n = 9,028; 58%), median age was 63 years (interquartile range: 46-83), 8,046 (54%) required hospitalisation, and 2,287 (15%) cases died. Prevalence of chronic conditions varied across SES, and multiple chronic conditions increased risk of death (≥ 3, adjusted odds ratio: 2.3). Age-standardised rates (incidence, hospitalisation, mortality) were highest in the most deprived SES quartile (incidence: 1,011 (95% confidence interval (CI): 975-1,047); hospitalisation: 619 (95% CI: 591-648); mortality: 150 (95% CI: 136-165)) and lowest in the most affluent (incidence: 784 (95% CI: 759-809); hospitalisation: 400 (95% CI: 382-418); mortality: 121 (95% CI: 112-131)).ConclusionsCOVID-19 outcomes varied markedly across SES, underscoring the need to implement effective preventive strategies for vulnerable populations.

Keywords: SARS-CoV-2; epidemiology; health inequalities; mortality; socio-economic status; surveillance

DOI: https://doi.org/10.2807/1560-7917.ES.2021.26.20.2001138

medRxiv. 2020 Nov 30. pii: 2020.11.27.20239616. [Epub ahead of print]

Obesity as a predictor for adverse outcomes among COVID-19 patients: A meta-analysis.

Pranta Das, Nandeeta Samad, Abdul-Aziz Seidu, Richard Gyan Aboagye, Justice Kanor Tetteh, Bright Opoku Ahinkorah.

Background: This meta-analysis sought to determine the estimated association between obesity and adverse outcomes among COVID-19 patients.
Methods: We followed the recommended PRISMA guidelines. A systematic literature search was conducted in PubMed, Google Scholar, and ScienceDirect for published literature between December 1, 2019, and October 2, 2020. The data for the study were pooled from studies that contained the search terms "Obesity" AND (COVID-19 or 2019-nCoV or Coronavirus or SARS-CoV-2) AND ("ICU admission" OR "Hospitalization" OR "Disease severity" OR "Invasive mechanical ventilator" OR "Death" OR "Mortality"). All the online searches were supplemented by reference screening of retrieved studies for additional literature. The pooled odds ratio (OR) and confidence intervals (CI) from the retrieved studies were calculated using the random effect model (Inverse-Variance method).
Findings: Five studies with a combined sample size of 335,192 patients were included in the meta-analysis. The pooled OR from the final analysis showed that patients who are severely obese were more likely to experience adverse outcome (death or ICU admission or needing IMV or hospitalization) compared to the normal patients [OR = 2.81, 95% CI = 2.33 - 3.40, I 2 = 29%].
Conclusion: Severe obesity is a risk factor in developing adverse outcomes among COVID-19 patients. The finding of the study signifies promotive, preventive, and curative attention to be accorded patients diagnosed with severe obesity and COVID-19.

DOI: https://doi.org/10.1101/2020.11.27.20239616