Validation of prognostic models predicting mortality or ICU admission in patients with COVID-19 in low- and middle-income countries: a global individual participant data meta-analysis.

Background: We evaluated the performance of prognostic models for predicting mortality or ICU admission in hospitalized patients with COVID-19 in the World Health Organization (WHO) Global Clinical Platform, a repository of individual-level clinical data of patients hospitalized with COVID-19, including in low- and middle-income countries (LMICs).

Methods: We identified eligible multivariable prognostic models for predicting overall mortality and ICU admission during hospital stay in patients with confirmed or suspected COVID-19 from a living review of COVID-19 prediction models. These models were evaluated using data contributed to the WHO Global Clinical Platform for COVID-19 from nine LMICs (Burkina Faso, Cameroon, Democratic Republic of Congo, Guinea, India, Niger, Nigeria, Zambia, and Zimbabwe).

The definition of predictor and outcome variables in mortality prediction models: a scoping review and quality of reporting study.

Background And Objectives: Mortality prediction models are promising tools for guiding clinical decision-making and resource allocation in intensive care units (ICUs). Clearly specified predictor and outcome variables are necessary to enable external validation and safe clinical application of prediction models. The objective of this study was to identify the predictor and outcome variables used in different mortality prediction models in the ICU and investigate their reporting.

Boosting the accuracy of existing models by updating and extending: using a multicenter COVID-19 ICU cohort as a proxy.

Most published prediction models for Coronavirus Disease 2019 (COVID-19) were poorly reported, at high risk of bias, and heterogeneous in model performance. To tackle methodological challenges faced in previous prediction studies, we investigated whether model updating and extending improves mortality prediction, using the Intensive Care Unit (ICU) as a proxy. All COVID-19 patients admitted to seven ICUs in the Euregio-Meuse Rhine during the first pandemic wave were included.

Effectiveness of safety netting approaches for acutely ill children: a network meta-analysis.

Background: Safety netting advice (SNA) can help in the management of acutely ill children.

Aim: Assess the effectiveness of different SNA methods for acutely ill children on antibiotic prescription and consumption.

Design And Setting: Systematic review and network meta-analysis of randomised controlled trials, non-randomised trials of interventions, and controlled before-after studies in ambulatory care.