Population risk factors for severe disease and mortality in COVID-19: A global systematic review and meta-analysis
Aim COVID-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 …
cases. While there are a number of early publications relating to risk factors for COVID-19 …
Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review
Objective To assess the methodological quality of studies on prediction models developed
using machine learning techniques across all medical specialties. Design Systematic …
using machine learning techniques across all medical specialties. Design Systematic …
Metabolomic profiles predict individual multidisease outcomes
Risk stratification is critical for the early identification of high-risk individuals and disease
prevention. Here we explored the potential of nuclear magnetic resonance (NMR) …
prevention. Here we explored the potential of nuclear magnetic resonance (NMR) …
Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on …
Introduction The Transparent Reporting of a multivariable prediction model of Individual
Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias …
Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias …
Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C …
Objective To develop and validate a pragmatic risk score to predict mortality in patients
admitted to hospital with coronavirus disease 2019 (covid-19). Design Prospective …
admitted to hospital with coronavirus disease 2019 (covid-19). Design Prospective …
External validation of prognostic models: what, why, how, when and where?
Prognostic models that aim to improve the prediction of clinical events, individualized
treatment and decision-making are increasingly being developed and published. However …
treatment and decision-making are increasingly being developed and published. However …
Cross-sectional studies: strengths, weaknesses, and recommendations
X Wang, Z Cheng - Chest, 2020 - Elsevier
Cross-sectional studies are observational studies that analyze data from a population at a
single point in time. They are often used to measure the prevalence of health outcomes …
single point in time. They are often used to measure the prevalence of health outcomes …
There is no such thing as a validated prediction model
Background Clinical prediction models should be validated before implementation in clinical
practice. But is favorable performance at internal validation or one external validation …
practice. But is favorable performance at internal validation or one external validation …
Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal
Objective To review and appraise the validity and usefulness of published and preprint
reports of prediction models for prognosis of patients with covid-19, and for detecting people …
reports of prediction models for prognosis of patients with covid-19, and for detecting people …
Calibration: the Achilles heel of predictive analytics
Background The assessment of calibration performance of risk prediction models based on
regression or more flexible machine learning algorithms receives little attention. Main text …
regression or more flexible machine learning algorithms receives little attention. Main text …