How to derive and validate clinical prediction models for use in intensive care medicine
Published 2014 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
How to derive and validate clinical prediction models for use in intensive care medicine
Authors
Keywords
Clinical prediction models, Clinical decision rule, Prognosis, Severity of illness index, Intensive care
Journal
INTENSIVE CARE MEDICINE
Volume 40, Issue 4, Pages 513-527
Publisher
Springer Nature
Online
2014-02-25
DOI
10.1007/s00134-014-3227-6
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Prognosis Research Strategy (PROGRESS) 3: Prognostic Model Research
- (2013) Ewout W. Steyerberg et al. PLOS MEDICINE
- Validation of a Clinical Prediction Model for Early Admission to the Intensive Care Unit of Patients With Pneumonia
- (2012) José Labarère et al. ACADEMIC EMERGENCY MEDICINE
- Re: "Dealing With Missing Outcome Data in Randomized Trials and Observational Studies"
- (2012) V. Liublinska et al. AMERICAN JOURNAL OF EPIDEMIOLOGY
- Missing covariate data in clinical research: when and when not to use the missing-indicator method for analysis
- (2012) R. H. H. Groenwold et al. CANADIAN MEDICAL ASSOCIATION JOURNAL
- Risk prediction models: II. External validation, model updating, and impact assessment
- (2012) Karel G M Moons et al. HEART
- Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker
- (2012) Karel G M Moons et al. HEART
- Comparing risk prediction models
- (2012) G. S. Collins et al. BMJ-British Medical Journal
- Consort 2010 statement: extension to cluster randomised trials
- (2012) M. K. Campbell et al. BMJ-British Medical Journal
- Dealing With Missing Outcome Data in Randomized Trials and Observational Studies
- (2011) Rolf H. H. Groenwold et al. AMERICAN JOURNAL OF EPIDEMIOLOGY
- Severity assessment tools to guide ICU admission in community-acquired pneumonia: systematic review and meta-analysis
- (2011) James D. Chalmers et al. INTENSIVE CARE MEDICINE
- Logistic regression modeling and the number of events per variable: selection bias dominates
- (2011) Ewout W. Steyerberg et al. JOURNAL OF CLINICAL EPIDEMIOLOGY
- Performance of logistic regression modeling: beyond the number of events per variable, the role of data structure
- (2011) Delphine S. Courvoisier et al. JOURNAL OF CLINICAL EPIDEMIOLOGY
- Towards a sensible comprehension of severe community-acquired pneumonia
- (2010) Santiago Ewig et al. INTENSIVE CARE MEDICINE
- Use of Brier score to assess binary predictions
- (2010) Kaspar Rufibach JOURNAL OF CLINICAL EPIDEMIOLOGY
- Missing covariate data in medical research: To impute is better than to ignore
- (2010) Kristel J.M. Janssen et al. JOURNAL OF CLINICAL EPIDEMIOLOGY
- Prognostic Models: A Methodological Framework and Review of Models for Breast Cancer
- (2009) Douglas G. Altman CANCER INVESTIGATION
- Association between timing of intensive care unit admission and outcomes for emergency department patients with community-acquired pneumonia*
- (2009) Bertrand Renaud et al. CRITICAL CARE MEDICINE
- Assessing the Performance of Prediction Models
- (2009) Ewout W. Steyerberg et al. EPIDEMIOLOGY
- Development and validation of a prediction model with missing predictor data: a practical approach
- (2009) Yvonne Vergouwe et al. JOURNAL OF CLINICAL EPIDEMIOLOGY
- Validation, updating and impact of clinical prediction rules: A review
- (2008) D.B. Toll et al. JOURNAL OF CLINICAL EPIDEMIOLOGY
- Updating methods improved the performance of a clinical prediction model in new patients
- (2007) K.J.M. Janssen et al. JOURNAL OF CLINICAL EPIDEMIOLOGY
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started