bims-covirf Biomed News
on COVID19 risk factors
Issue of 2020‒10‒18
eight papers selected by
Catherine Rycroft

  1. Cureus. 2020 Sep 10. 12(9): e10350
    Hanif M, Haider MA, Xi Q, Ali MJ, Ahmed MU.
      The global pandemic of coronavirus disease 2019 (COVID-19) and its rapid spread throughout the globe is of much concern. With little known about the peculiar virus and the changing mortality and morbidity, we attempt to review the risk factors associated with significant outcome.  We conducted a review of the information available in medical journals published on COVID-19 risk factors associated with poor outcomes using PubMed®, Google Scholar, and material published online. The risk factors associated with poor outcome were kept in particular consideration. A total of 96 articles were thoroughly reviewed and analyzed so as to highlight the risk factors and the subsequent disease presentation that were present in patients with COVID-19. With little data available in this regard, emphasis and consideration of risk factors might help health care workers preclude the worst outcome. From the aforementioned search we can conclude that the most prevalent risk factors were reported to be hypertension followed by diabetes. In terms of mortality, age greater than 65 was the most significant risk factor. Among non-survivors, coagulation profile including d-dimers, prothrombin time, and inflammatory markers like erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and serum ferritin levels were very deranged. Much emphasis and consideration in relation to risk factors must be deliberated by health care workers so as to prevent severe outcomes and mitigate appropriate treatment modalities.
    Keywords:  co-morbidities; covid-19; diabetes mellitus; hypertension; predictors; risk factors; sars-cov-2
  2. Aging (Albany NY). 2020 Oct 13. 12
    Su W, Qiu Z, Zhou L, Hou J, Wang Y, Huang F, Zhang Y, Jia Y, Zhou J, Liu D, Xia Z, Xia ZY, Lei S.
      The coronavirus disease 2019 (COVID-19) became a global pandemic. Males, compared to females, seem to be more susceptible to COVID-19, but related evidence is scarce, especially in severe patients. We explored sex differences in clinical characteristics and potential risk factors for mortality in severe COVID-19 patients. In this retrospective cohort study, we included all severe COVID-19 patients admitted to Eastern Renmin Hospital of Wuhan University, Wuhan, China, with a definitive clinical outcome as of Apr 10, 2020. Of the included 651 patients, 332 were male, and 319 were female. Males and females did not differ in age and underlying comorbidities. Males were more likely than females to report fever and develop serious complications, including acute respiratory distress syndrome, secondary infection, acute cardiac injury, coagulopathy, acute kidney injury and arrhythmia. Further, males had much higher mortality relative to females. Multivariable regression showed neutrophilia (odds ratio 6.845, 95% CI 1.227-38.192, p=0.028), thrombocytopenia (19.488, 3.030-25.335, p=0.002), hypersensitive troponin I greater than 0.04 pg/mL (6.058, 1.545-23.755, p=0.010), and procalcitonin greater than 0.1 ng/mL (6.350, 1.396-28.882, p=0.017) on admission were associated with in-hospital death. With either of these risk factors, the cumulative survival rate was relatively lower in males than in females. In conclusion, males are more likely than females to develop serious complications and progress to death. The potential risk factors of neutrophilia, thrombocytopenia, hypersensitive troponin I greater than 0.04 pg/mL and procalcitonin more than 0.1 ng/mL may help clinicians to identify patients with poor outcomes at an early stage, especially in males.
    Keywords:  COVID-19; mortality; risk factors; sex difference
  3. Expert Rev Anticancer Ther. 2020 Oct 14.
    Liu Y, Lu H, Wang W, Liu Q, Zhu C.
      INTRODUCTION: Patients with cancer are more vulnerable to COVID-19 than the general population. Accordingly, it is necessary to identify the risk factors for death in patients with cancer and COVID-19.METHODS: PubMed, Cochrane Library, and Embase Ovid databases were searched for relevant articles published before July 31st, 2020. Studies that explored the risk factors for mortality were included. The effect size was relative risk (RR) and 95% confidence interval (CI).
    RESULTS: We included 17 observational studies involving 3268 patients. The pooled mortality was 24.8%. Male gender, age above 65 years, and comorbidities (especially hypertension and COPD) were risk factors for death (RR 1.16, 1.27, 1.12; 95% CI 0.7-1.95, 1.08-1.49, 1.04-1.2; P=0.006, 0.004 and 0.002, respectively). Recent anti-cancer treatments did not increase mortality (P> 0.05). Dyspnea, cough, and sputum were associated with an elevated risk of death (P< 0.05). Antibiotics, glucocorticoids, interferons, invasive ventilation, and complications were associated with a high probability of death (P< 0.05).
    CONCLUSIONS: Various demographic and clinical characteristics, such as male gender, advanced age, comorbidities, and symptoms, were identified as risk factors for mortality in patients with cancer and COVID-19. Our findings suggest recent anti-cancer treatments do not increase mortality.
    TRIAL REGISTRATION: Registration in PROSPERO (CRD42020201514).
    Keywords:  COVID-19; cancer; meta-analysis; mortality; risk factors
  4. Am J Emerg Med. 2020 Aug 20. pii: S0735-6757(20)30711-7. [Epub ahead of print]
    Cheruiyot I, Kipkorir V, Ngure B, Misiani M, Munguti J.
      BACKGROUND: Coronavirus disease 2019 (COVID-19) is a rapidly escalating pandemic that has spread to many parts of the world. As such, there is urgent need to identify predictors of clinical severity in COVID-19 patients. This may be useful for early identification of patients who may require life-saving interventions. In this meta-analysis, we evaluated whether malignancies are associated with a significantly enhanced odds of COVID-19 severity and mortality.METHOD: A systematic search of literature was conducted between November 1, 2019, to May 26th, 2020 on PubMed and China National Knowledge Infrastructure (CNKI) to identify studies reporting data on cancers in patients with or without severe COVID-19 were included. The primary outcome of interest was the association between malignancies and COVID-19 severity, while the secondary outcome was the association between malignancies and COVID-19 mortality. Data were pooled into a meta-analysis to estimate pooled odds ratio (OR) with 95% confidence interval (95% CI) for either outcome.
    RESULTS: A total of 20 studies (n = 4549 patients) were included. Overall, malignancies were found to be associated with significantly increased odds of COVID-19 severity (OR = 2.17; 95% CI 1.47-3.196; p < 0.001) and mortality (OR = 2.39; 95% CI 1.18-4.85; p = 0.016). No heterogeneity was observed for both outcomes (Cochran's Q = 6.558, p = 0.922, I2 = 0% and Cochran's Q = 2.91, p = 0.71, I2 = 0% respectively).
    CONCLUSION: Malignancies were significantly associated with a 2-fold increase in the odds of developing severe COVID-19 disease, as well as mortality. Larger studies are needed to corroborate these findings. These patients should be closely monitored for any signs of unfavorable disease progression.
    Keywords:  COVID-19; Cancer; Mortality; Severity
  5. Blood Adv. 2020 Oct 27. 4(20): 4981-4989
    Hoiland RL, Fergusson NA, Mitra AR, Griesdale DEG, Devine DV, Stukas S, Cooper J, Thiara S, Foster D, Chen LYC, Lee AYY, Conway EM, Wellington CL, Sekhon MS.
      Studies on severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) suggest a protective effect of anti-A antibodies against viral cell entry that may hold relevance for SARS-CoV-2 infection. Therefore, we aimed to determine whether ABO blood groups are associated with different severities of COVID-19. We conducted a multicenter retrospective analysis and nested prospective observational substudy of critically ill patients with COVID-19. We collected data pertaining to age, sex, comorbidities, dates of symptom onset, hospital admission, intensive care unit (ICU) admission, mechanical ventilation, continuous renal replacement therapy (CRRT), standard laboratory parameters, and serum inflammatory cytokines. National (N = 398 671; P = .38) and provincial (n = 62 246; P = .60) ABO blood group distributions did not differ from our cohort (n = 95). A higher proportion of COVID-19 patients with blood group A or AB required mechanical ventilation (P = .02) and CRRT (P = .004) and had a longer ICU stay (P = .03) compared with patients with blood group O or B. Blood group A or AB also had an increased probability of requiring mechanical ventilation and CRRT after adjusting for age, sex, and presence of ≥1 comorbidity. Inflammatory cytokines did not differ between patients with blood group A or AB (n = 11) vs O or B (n = 14; P > .10 for all cytokines). Collectively, our data indicate that critically ill COVID-19 patients with blood group A or AB are at increased risk for requiring mechanical ventilation, CRRT, and prolonged ICU admission compared with patients with blood group O or B. Further work is needed to understand the underlying mechanisms.
  6. J Stroke Cerebrovasc Dis. 2020 Nov;pii: S1052-3057(20)30701-1. [Epub ahead of print]29(11): 105283
    Xu J, Xiao W, Liang X, Zhang P, Shi L, Wang Y, Wang Y, Yang H.
      OBJECTIVE: The aim of this study was to address the association between cerebrovascular disease and adverse outcomes in coronavirus disease 2019 (COVID-19) patients by using a quantitative meta-analysis based on adjusted effect estimates.METHOD: A systematic search was performed in PubMed, Web of Science, and EMBASE up to August 10th, 2020. The adjusted effect estimates were extracted and pooled to evaluate the risk of the unfavorable outcomes in COVID-19 patients with cerebrovascular disease. Subgroup analysis and meta-regression were also carried out.
    RESULTS: There were 12 studies with 10,304 patients included in our meta-analysis. A significant trend was observed when evaluating the association between cerebrovascular disease and adverse outcomes (pooled effect = 2.05, 95% confidence interval (CI): 1.34-3.16). In addition, the pooled effects showed that patients with a history of cerebrovascular disease had more likelihood to progress fatal outcomes than patients without a history of cerebrovascular disease (pooled effect = 1.78, 95% CI: 1.04-3.07).
    CONCLUSION: This study for the first time indicated that cerebrovascular disease was an independent risk factor for predicting the adverse outcomes, particularly fatal outcomes, in COVID-19 patients on the basis of adjusted effect estimates. Well-designed studies with larger sample size are needed for further verification.
    Keywords:  Adjusted effect estimate; Adverse outcomes; COVID-19; Cerebrovascular disease; Meta-analysis
  7. PLoS One. 2020 ;15(10): e0240346
    Wollenstein-Betech S, Silva AAB, Fleck JL, Cassandras CG, Paschalidis IC.
      BACKGROUND: Given the severity and scope of the current COVID-19 pandemic, it is critical to determine predictive features of COVID-19 mortality and medical resource usage to effectively inform health, risk-based physical distancing, and work accommodation policies. Non-clinical sociodemographic features are important explanatory variables of COVID-19 outcomes, revealing existing disparities in large health care systems.METHODS AND FINDINGS: We use nation-wide multicenter data of COVID-19 patients in Brazil to predict mortality and ventilator usage. The dataset contains hospitalized patients who tested positive for COVID-19 and had either recovered or were deceased between March 1 and June 30, 2020. A total of 113,214 patients with 50,387 deceased, were included. Both interpretable (sparse versions of Logistic Regression and Support Vector Machines) and state-of-the-art non-interpretable (Gradient Boosted Decision Trees and Random Forest) classification methods are employed. Death from COVID-19 was strongly associated with demographics, socioeconomic factors, and comorbidities. Variables highly predictive of mortality included geographic location of the hospital (OR = 2.2 for Northeast region, OR = 2.1 for North region); renal (OR = 2.0) and liver (OR = 1.7) chronic disease; immunosuppression (OR = 1.7); obesity (OR = 1.7); neurological (OR = 1.6), cardiovascular (OR = 1.5), and hematologic (OR = 1.2) disease; diabetes (OR = 1.4); chronic pneumopathy (OR = 1.4); immunosuppression (OR = 1.3); respiratory symptoms, ranging from respiratory discomfort (OR = 1.4) and dyspnea (OR = 1.3) to oxygen saturation less than 95% (OR = 1.7); hospitalization in a public hospital (OR = 1.2); and self-reported patient illiteracy (OR = 1.1). Validation accuracies (AUC) for predicting mortality and ventilation need reach 79% and 70%, respectively, when using only pre-admission variables. Models that use post-admission disease progression information reach accuracies (AUC) of 86% and 87% for predicting mortality and ventilation use, respectively.
    CONCLUSIONS: The results highlight the predictive power of socioeconomic information in assessing COVID-19 mortality and medical resource allocation, and shed light on existing disparities in the Brazilian health care system during the COVID-19 pandemic.