bims-covirf Biomed News
on COVID19 risk factors
Issue of 2021‒04‒25
seven papers selected by
Catherine Rycroft

  1. Z Gesundh Wiss. 2021 Apr 11. 1-10
      Aim: International health authorities suggest that individuals aged 65 years and above and people with underlying comorbidities such as hypertension, chronic lung disease, cardiovascular disease, cancer, diabetes, and obesity are at increased risk of severe Coronavirus Disease 2019 (COVID-19); however, the prevalence of risk factors is unknown in many countries. Therefore, we aimed to describe the distribution of these risk factors across Europe.Subject and methods: Prevalence of risk factors for severe COVID-19 was identified based on interviews from 73,274 Europeans aged 50+ participating in the Survey of Health, Ageing and Retirement in Europe (SHARE) in 2017. Burden of disease was estimated using population data from Eurostat.
    Results: A total of 75.3% of the study population (corresponding to approx. 60 million European men and 71 million women) had at least one risk factor for severe COVID-19, 45.9% (approx. 36 million men and 43 million women) had at least two factors, and 21.2% (approx. 17 million men and 20 million women) had at least three risk factors. The prevalence of underlying medical conditions ranged from 4.5% for cancer to 41.4% for hypertension, and the region-specific prevalence of having at least three risk factors ranged from 18.9% in Northern Europe to 24.6% in Eastern Europe.
    Conclusions: Information about the prevalence of risk factors might help authorities to identify the most vulnerable subpopulations with multiple risk factors of severe COVID-19 and thus to decide appropriate strategies to mitigate the pandemic.
    Supplementary Information: The online version contains supplementary material available at 10.1007/s10389-021-01537-7.
    Keywords:  Burden of disease; COVID-19; Europe; Prevalence; Risk factors; SARS-CoV-2
  2. PLoS One. 2021 ;16(4): e0250400
      IMPORTANCE: The ongoing pandemic of the novel Corona Virus Disease 2019 (COVID-19) is an unprecedented challenge to global health, never experienced before.OBJECTIVE: This study aims to describe the clinical characteristics and outcomes of patients with COVID-19 admitted to Mercy Hospitals.
    DESIGN AND METHODS: Retrospective, observational cohort study designed to include every COVID-19 subject aged 18 years or older admitted to Mercy Saint (St) Vincent, Mercy St Charles, and Mercy St Anne's hospital in Toledo, Ohio from January 1, 2020 through June 15th, 2020. Primary Outcome Measure was mortality in the emergency department or as an in-patient.
    RESULTS: 470 subjects including 224 males and 246 females met the inclusion criteria for the study. Subjects with the following characteristics had higher odds (OR) of death: Older age [OR 8.3 (95% CI 1.1-63.1, p = 0.04)] for subjects age 70 or more compared to subjects age 18-29); Hypertension [OR 3.6 (95% CI 1.6-7.8, p = 0.001)]; Diabetes [OR 3.1 (95% CI 1.7-5.6, p<0.001)]; COPD [OR 3.4 (95% CI 1.8-6.3, p<0.001)] and CKD stage 2 or greater [OR 2.5 (95% CI 1.3-4.9, p = 0.006)]. Combining all age groups, subjects with hypertension had significantly greater odds of the following adverse outcomes: requiring hospital admission (OR 2.2, 95% CI 1.4-3.4, p<0.001); needing respiratory support in 24 hours (OR 2.5, 95% CI: 1.7-3.7, p<0.001); ICU admission (OR 2.7, 95% CI 1.7-4.4, p<0.001); and death (OR 3.6, 95% CI 1.6-7.8, p = 0.001). Hypertension was not associated with needing vent in 24 hours (p = 0.07).
    CONCLUSION: Age and hypertension were associated with significant comorbidity and mortality in Covid-19 Positive patients. Furthermore, people who were older than 70, and had hypertension, diabetes, COPD, or CKD had higher odds of dying from the disease as compared to patients who hadn't. Subjects with hypertension also had significantly greater odds of other adverse outcomes.
  3. Epidemiol Prev. 2021 Jan-Apr;45(1-2):45(1-2): 100-109
      OBJECTIVES: to develop a risk prediction model for 30-day mortality from COVID‑19 in an Italian cohort aged 40 years or older.DESIGN: a population-based retrospective cohort study on prospectively collected data was conducted.
    SETTING AND PARTICIPANTS: the cohort included all swab positive cases aged 40 years older (No. 18,286) among residents in the territory of the Milan's Agency for Health Protection (ATS-MI) up to 27.04.2020. Data on comorbidities were obtained from the ATS administrative database of chronic conditions.
    MAIN OUTCOME MEASURES: to predict 30-day mortality risk, a multivariable logistic regression model, including age, gender, and the selected conditions, was developed following the TRIPOD guidelines. Discrimination and calibration of the model were assessed.
    RESULTS: after age and gender, the most important predictors of 30-day mortality were diabetes, tumour in first-line treatment, chronic heart failure, and complicated diabetes. The bootstrap-validated c-index was 0.78, which suggests that this model is useful in predicting death after COVID-19 infection in swab positive cases. The model had good discrimination (Brier score 0.13) and was well calibrated (Index of prediction accuracy of 14.8%).
    CONCLUSIONS: a risk prediction model for 30-day mortality in a large COVID-19 cohort aged 40 years or older was developed. In a new epidemic wave, it would help to define groups at different risk and to identify high-risk subjects to target for specific prevention and therapeutic strategies.
  4. Sci Rep. 2021 Apr 20. 11(1): 8562
      Several comorbidities have been shown to be associated with coronavirus disease 2019 (COVID-19) related severity and mortality. However, considerable variation in the prevalence estimates of comorbidities and their effects on COVID-19 morbidity and mortality have been observed in prior studies. This systematic review and meta-analysis aimed to determine geographical, age, and gender related differences in the prevalence of comorbidities and associated severity and mortality rates among COVID-19 patients. We conducted a search using PubMed, Scopus, and EMBASE to include all COVID-19 studies published between January 1st, 2020 to July 24th, 2020 reporting comorbidities with severity or mortality. We included studies reporting the confirmed diagnosis of COVID-19 on human patients that also provided information on comorbidities or disease outcomes. We used DerSimonian and Laird random effects method for calculating estimates. Of 120 studies with 125,446 patients, the most prevalent comorbidity was hypertension (32%), obesity (25%), diabetes (18%), and cardiovascular disease (16%) while chronic kidney or other renal diseases (51%, 44%), cerebrovascular accident (43%, 44%), and cardiovascular disease (44%, 40%) patients had more COVID-19 severity and mortality respectively. Considerable variation in the prevalence of comorbidities and associated disease severity and mortality in different geographic regions was observed. The highest mortality was observed in studies with Latin American and European patients with any medical condition, mostly older adults (≥ 65 years), and predominantly male patients. Although the US studies observed the highest prevalence of comorbidities in COVID-19 patients, the severity of COVID-19 among each comorbid condition was highest in Asian studies whereas the mortality was highest in the European and Latin American countries. Risk stratification and effective control strategies for the COVID-19 should be done according to comorbidities, age, and gender differences specific to geographical location.
  5. Lancet Reg Health Eur. 2021 Jun;5 100097
      Background: To date, over 2 million people worldwide have died with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. To describe the experience in Ireland, this study examined associations between underlying conditions and the following outcomes: mortality, admission to hospital or admission to the intensive care unit (ICU) among those infected with COVID-19.Methods: This study used data from the Health Protection Surveillance Centre in Ireland and included confirmed cases of COVID-19 from the first wave of the pandemic between March and July 2020. Two cohorts were included: all cases (community and hospital) and hospital admissions only. For all cases, health outcome data included mortality and hospitalisation. For hospitalised cases, outcome data included mortality and ICU admission. Logistic regression was used to examine associations between underlying conditions and outcomes across both cohorts. Results are presented as adjusted odds ratios (OR) and 95% confidence intervals (CIs).
    Findings: There were 19,789 cases included in analysis, which encompassed 1,476 (7.5%) deaths, 2,811 (14.2%) hospitalisations, and 438 (2.2%) ICU admissions of whom 90 (20.5%) died. Significantly higher risk of mortality, hospitalisation and ICU admission was associated with having chronic heart disease, a BMI ≥40kg/m2 and male sex. Additionally, diagnosis of a chronic neurological condition (OR 1.41; 95%CI:1.17, 1.69), chronic kidney disease (OR 1.74; 95%CI:1.35, 2.24) and cancer (OR 2.77; 95%CI:2.21, 3.47) were significantly associated with higher risk of mortality among all cases, with similar patterns of association observed for mortality among hospitalised cases.
    Interpretation: The identification of underlying conditions among COVID-19 cases may help identify those at highest risk of the worst health outcomes and inform preventive strategies to improve outcomes.
    Funding: This study was supported by the Health Service Executive, Health Protection Surveillance Centre. KEB and MM are funded by the Health Research Board (RL-15-1579 and EIA-2019-012 respectively).
    Keywords:  COVID-19; Hospitalisation; ICU admission; Mortality; Underlying conditions
  6. Obes Med. 2021 Apr 15. 100340
      Introduction: Obesity and higher BMI is one of the leading comorbidities to increase the risk of COVID-19 severity. This paper presents a systematic review and meta-analysis estimating the effects of overweight and obesity on COVID-19 disease severity.Method: ology: Two electronic databases (Medline and Cochrane library) and one grey literature database (Grey Literature Report) were searched. The risks of bias of the selected studies were assessed by using the Navigation Guide method for human data. Both random and fixed effect meta-analyses were determined using Review Manager (RevMan) software version 5.4.
    Results: After initial screening, 12 studies were fulfilled the eligibility criteria, comprising a total of 405359 patients, and included in the systematic review. The pooled risk of COVID-19 severity was 1.31 times higher based on both fixed and random effect model among those overweight patients, I 2 0% and 2.09 and 2.41 times higher based on fixed and random effect respectively among obese patients, I 2 42% compared to healthy individuals.
    Conclusion: Overweight and obesity are found to be risk factors for disease severity of COVID-19 patients. However, further assessment of metabolic parameters is required to estimate the risk factors of COVID-19 patients and understanding the mechanism between COVID-19 and body mass index.
    Keywords:  BMI; COVID-19; obesity; overweight