Additional predictors of stroke and transient ischaemic attack in BEFAST positive patients in out-of-hours emergency primary care.

Introduction: In patients suspected of stroke or transient ischemic attack (TIA), rapid triaging is imperative to improve clinical outcomes. For this purpose, balance-eye-face-arm-speech-time (BEFAST) items are used in out-of-hours primary care (OHS-PC). We explored the risk of stroke and TIA among BEFAST positive patients calling to the OHS-PC, and assessed whether additional predictors could improve risk stratification.

Don't be misled: 3 misconceptions about external validation of clinical prediction models.

Clinical prediction models provide risks of health outcomes that can inform patients and support medical decisions. However, most models never make it to actual implementation in practice. A commonly heard reason for this lack of implementation is that prediction models are often not externally validated.

Predictive factors of clot propagation in patients with superficial venous thrombosis towards deep venous thrombosis and pulmonary embolism: a systematic review and meta-analysis.

Objective: A subset of patients with superficial venous thrombosis (SVT) experiences clot propagation towards deep venous thrombosis (DVT) and/or pulmonary embolism (PE). The aim of this systematic review is to identify all clinically relevant cross-sectional and prognostic factors for predicting thrombotic complications in patients with SVT.

Design: Systematic review.

Five critical quality criteria for artificial intelligence-based prediction models.

To raise the quality of clinical artificial intelligence (AI) prediction modelling studies in the cardiovascular health domain and thereby improve their impact and relevancy, the editors for digital health, innovation, and quality standards of the European Heart Journal propose five minimal quality criteria for AI-based prediction model development and validation studies: complete reporting, carefully defined intended use of the model, rigorous validation, large enough sample size, and openness of code and software.

Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis.

Objective: To externally validate various prognostic models and scoring rules for predicting short term mortality in patients admitted to hospital for covid-19.

Design: Two stage individual participant data meta-analysis.

Setting: Secondary and tertiary care.

Cardiovascular vulnerability predicts hospitalisation in primary care clinically suspected and confirmed COVID-19 patients: A model development and validation study.

Objectives: Cardiovascular conditions were shown to be predictive of clinical deterioration in hospitalised patients with coronavirus disease 2019 (COVID-19). Whether this also holds for outpatients managed in primary care is yet unknown. The aim of this study was to determine the incremental value of cardiovascular vulnerability in predicting the risk of hospital referral in primary care COVID-19 outpatients.

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 diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease.

Design: Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group.

Data Sources: PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020.

Automated CT quantification methods for the assessment of interstitial lung disease in collagen vascular diseases: A systematic review.

Interstitial lung disease (ILD) is highly prevalent in collagen vascular diseases and reduction of ILD is an important therapeutic target. To that end, reliable quantification of pulmonary disease severity is of great significance. This study systematically reviewed the literature on automated computed tomography (CT) quantification methods for assessing ILD in collagen vascular diseases.