Risk factors for severity of COVID-19: a rapid review to inform vaccine prioritisation in Canada

Abstract

ObjectivesRapid review to determine the magnitude of association between potential risk factors and severity of COVID-19, to inform vaccine prioritisation in Canada.SettingOvid MEDLINE(R) ALL, Epistemonikos COVID-19 in L·OVE Platform, McMaster COVID-19 Evidence Alerts and websites were searched to 15 June 2020. Eligible studies were conducted in high-income countries and used multivariate analyses.ParticipantsAfter piloting, screening, data extraction and quality appraisal were performed by a single experienced reviewer. Of 3740 unique records identified, 34 were included that reported on median 596 (range 44–418 794) participants, aged 42–84 years. 19/34 (56%) were good quality.OutcomesHospitalisation, intensive care unit admission, length of stay in hospital or intensive care unit, mechanical ventilation, severe disease, mortality.ResultsAuthors synthesised findings narratively and appraised the certainty of the evidence for each risk factor–outcome association. There was low or moderate certainty evidence for a large (≥2-fold) magnitude of association between hospitalisation in people with COVID-19, and: obesity class III, heart failure, diabetes, chronic kidney disease, dementia, age >45 years, male gender, black race/ethnicity (vs non-Hispanic white), homelessness and low income. Age >60 and >70 years may be associated with large increases in mechanical ventilation and severe disease, respectively. For mortality, a large magnitude of association may exist with liver disease, Bangladeshi ethnicity (vs British white), age >45 years, age >80 years (vs 65–69 years) and male gender among 20–64 years (but not older). Associations with hospitalisation and mortality may be very large (≥5-fold) for those aged ≥60 years.ConclusionsIncreasing age (especially >60 years) may be the most important risk factor for severe outcomes. High-quality primary research accounting for multiple confounders is needed to better understand the magnitude of associations for severity of COVID-19 with several other factors.PROSPERO registration numberCRD42020198001.

Effectiveness of Covid-19 Vaccines in Ambulatory and Inpatient Care Settings

“…This finding is reassuring, given that these groups can have impaired immune responses to other vaccines 28-30 and are most at risk for severe and prolonged manifestations of Covid-19 and death. 8 , 9 , 13 , 14 Second, in Black adults and Hispanic adults, who have been disproportionately affected by Covid-19, mRNA-based vaccines were similarly effective with respect to Covid-19–associated hospitalization and an emergency department or urgent care clinic visit. 9-11 , 14 , 31 Third, the effectiveness of full mRNA-based vaccination remained consistently high at least until 112 days after the second dose, which was the longest interval since vaccination during our study period.…”

“… 8 , 9 , 13 , 14 Second, in Black adults and Hispanic adults, who have been disproportionately affected by Covid-19, mRNA-based vaccines were similarly effective with respect to Covid-19–associated hospitalization and an emergency department or urgent care clinic visit. 9-11 , 14 , 31 Third, the effectiveness of full mRNA-based vaccination remained consistently high at least until 112 days after the second dose, which was the longest interval since vaccination during our study period. Fourth, we examined the effectiveness of all three authorized Covid-19 vaccines in the United States.…”

Uncovering Clinical Risk Factors and Predicting Severe COVID-19 Cases Using UK Biobank Data: Machine Learning Approach (Preprint)

“…Another large-scale British primary care study of more than 17 million individuals revealed similar risk factors as above [60]. There is also a relatively large literature on the study of risk factors associated with severe or fatal disease [15][16][17][18][61][62][63][64]. Some commonly reported risk factors included age, sex, obesity, T2DM, HT, renal, cardiometabolic, and respiratory disorders.…”

“…While predictive performance is the main concern in most previous studies, we argue that ML models can also provide important insights into individual contributing factors and the pattern of complex relationships between risk factors and the outcome. While many have studied risk factors of COVID-19 susceptibility or severity in the UKBB [12][13][14] or other cohorts (eg, [8,[15][16][17][18]), most relied on conventional linear models. As such, nonlinear effects and interactions between variables may be missed.…”

Uncertainty, Anxiety and Isolation: Experiencing the COVID-19 Pandemic and Lockdown as a Woman with Polycystic Ovary Syndrome (PCOS)

“…Due to this risk of severe and even fatal COVID-19, governments and relevant public health authorities worldwide enforced nationwide lockdown/quarantine measures, aiming to decrease the transmission of SARS-CoV-2 among the general population, and hence protect the health of vulnerable individuals [4][5][6][7]. Based on robust clinical and epidemiological evidence, it is now clear that, in addition to older age and male sex, susceptibility to severe COVID-19 is directly associated with a number of chronic cardio-metabolic diseases, such as obesity, diabetes, hypertension and metabolic syndrome [8][9][10][11][12][13][14]. Of note, with the exception of advanced age and male sex, the same cardio-metabolic risk factors which predispose to severe COVID-19 are also highly prevalent among women with polycystic ovary syndrome (PCOS) [15,16], placing this female patient population at potentially increased risk during the COVID-19 pandemic [17].…”