Association of cardiovascular disease and 10 other pre-existing comorbidities with COVID-19 mortality: A systematic review and meta-analysis
Background Estimating the risk of pre-existing comorbidities on coronavirus disease 2019
(COVID-19) mortality may promote the importance of targeting populations at risk to improve …
(COVID-19) mortality may promote the importance of targeting populations at risk to improve …
Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations
Abstract Background Directed acyclic graphs (DAGs) are an increasingly popular approach
for identifying confounding variables that require conditioning when estimating causal …
for identifying confounding variables that require conditioning when estimating causal …
Causal inference and counterfactual prediction in machine learning for actionable healthcare
Big data, high-performance computing, and (deep) machine learning are increasingly
becoming key to precision medicine—from identifying disease risks and taking preventive …
becoming key to precision medicine—from identifying disease risks and taking preventive …
Humidity's role in heat-related health outcomes: a heated debate
Background: As atmospheric greenhouse gas concentrations continue to rise, temperature
and humidity will increase further, causing potentially dire increases in human heat stress …
and humidity will increase further, causing potentially dire increases in human heat stress …
Control of confounding and reporting of results in causal inference studies. Guidance for authors from editors of respiratory, sleep, and critical care journals
The views and recommendations made in this document do not represent the official
position of any publisher or professional medical society. This document has not been …
position of any publisher or professional medical society. This document has not been …
The effects of COVID-19 on cognitive performance in a community-based cohort: a COVID symptom study biobank prospective cohort study
Background Cognitive impairment has been reported after many types of infection, including
SARS-CoV-2. Whether deficits following SARS-CoV-2 improve over time is unclear. Studies …
SARS-CoV-2. Whether deficits following SARS-CoV-2 improve over time is unclear. Studies …
Long-term exposure to multiple ambient air pollutants and association with incident depression and anxiety
Importance Air pollution is increasingly recognized as an important environmental risk factor
for mental health. However, epidemiologic evidence on long-term exposure to low levels of …
for mental health. However, epidemiologic evidence on long-term exposure to low levels of …
[HTML][HTML] Smoking and COVID-19 outcomes: an observational and Mendelian randomisation study using the UK Biobank cohort
Background Conflicting evidence has emerged regarding the relevance of smoking on risk
of COVID-19 and its severity. Methods We undertook large-scale observational and …
of COVID-19 and its severity. Methods We undertook large-scale observational and …
Tutorial on directed acyclic graphs
Directed acyclic graphs (DAGs) are an intuitive yet rigorous tool to communicate about
causal questions in clinical and epidemiologic research and inform study design and …
causal questions in clinical and epidemiologic research and inform study design and …
The C-word: scientific euphemisms do not improve causal inference from observational data
MA Hernán - American journal of public health, 2018 - ajph.aphapublications.org
Causal inference is a core task of science. However, authors and editors often refrain from
explicitly acknowledging the causal goal of research projects; they refer to causal effect …
explicitly acknowledging the causal goal of research projects; they refer to causal effect …