Population risk factors for severe disease and mortality in COVID-19: A global systematic review and meta-analysis

Abstract

AimCOVID-19 clinical presentation is heterogeneous, ranging from asymptomatic to severe cases. While there are a number of early publications relating to risk factors for COVID-19 infection, low sample size and heterogeneity in study design impacted consolidation of early findings. There is a pressing need to identify the factors which predispose patients to severe cases of COVID-19. For rapid and widespread risk stratification, these factors should be easily obtainable, inexpensive, and avoid invasive clinical procedures. The aim of our study is to fill this knowledge gap by systematically mapping all the available evidence on the association of various clinical, demographic, and lifestyle variables with the risk of specific adverse outcomes in patients with COVID-19.MethodsThe systematic review was conducted using standardized methodology, searching three electronic databases (PubMed, Embase, and Web of Science) for relevant literature published between 1st January 2020 and 9th July 2020. Included studies reported characteristics of patients with COVID-19 while reporting outcomes relating to disease severity. In the case of sufficient comparable data, meta-analyses were conducted to estimate risk of each variable.ResultsSeventy-six studies were identified, with a total of 17,860,001 patients across 14 countries. The studies were highly heterogeneous in terms of the sample under study, outcomes, and risk measures reported. A large number of risk factors were presented for COVID-19. Commonly reported variables for adverse outcome from COVID-19 comprised patient characteristics, including age >75 (OR = 2.65 (1.81–3.90)), male sex (OR = 2.05(1.39–3.04)) and severe obesity (OR = 2.57 (1.31–5.05)). Active cancer (OR = 1.46 (1.04–2.04)) was associated with increased risk of severe outcome. A number of common symptoms and vital measures (respiratory rate and SpO2) also suggested elevated risk profiles.ConclusionsBased on the findings of this study, a range of easily assessed parameters are valuable to predict elevated risk of severe illness and mortality as a result of COVID-19, including patient characteristics and detailed comorbidities, alongside the novel inclusion of real-time symptoms and vital measurements.

Machine learning approach to dynamic risk modeling of mortality in COVID-19: a UK Biobank study

“…While research on COVID-19 is rapidly evolving, it is well established that age 23 and obesity 24 are significant variables. In the data-driven model, we found that age was the most critical factor in determining outcome, in line with meta-analyses on outcomes in COVID-19 patients 10,23 . Obesity is also well reflected in our model, with body mass index (BMI) and related measures featuring dominantly in the data-driven ranking.…”

“…While both conditions are linked to obesity, diabetes has been reported to confer significant independent mortality risk 27 . Evidence for the role of hypertension as an independent risk factor, however, is not fully established, with meta-analyses finding hypertension non-significant after adjusting for other risk factors 10,28,29 .…”

“…Decision-making at all levels requires an understanding of individuals’ risk of severe disease. Various patient characteristics, comorbidities, and lifestyle factors have been linked to greater risk of death and/or severe illness following infection 5–7 . Once patients are infected with SARS-CoV-2, additional physiological parameters, such as symptoms and vital signs, can inform real-time prognostication 8 .…”

Perceptions and acceptance of COVID-19 vaccine among pregnant and lactating women in Singapore: A cross-sectional study

“…Pregnant women are a vulnerable group in this pandemic, with an increased risk for severe disease and adverse outcomes if infected, including preterm birth, venous thromboembolism, severe respiratory complications requiring invasive ventilation. (9)(10)(11)(12) Lactating mothers could also potentially infect the infant postnatally via droplet infection. (13,14) Despite the benefits of vaccination to prevent maternal and fetal complications, studies have demonstrated varying rates of vaccine acceptance in pregnant and lactating women.…”

Children develop robust and sustained cross-reactive spike-specific immune responses following SARS-CoV-2 infection

“…The SARS-CoV-2 pandemic has resulted in over 2.8 million deaths to date and the most significant determinant of outcome is age at the time of primary infection (Booth, Reed et al 2021). In children, SARS-CoV-2 infection is generally asymptomatic or mild and contrasts with high rates of hospitalisations and deaths among older adults (Viner, Mytton et al 2021).…”