Related Experiment Video
Updated: Aug 7, 2025
08:10
Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
1.7K
Multivariable prediction models for atrial fibrillation after cardiac surgery: a systematic review protocol
Kara G Fields1, Jie Ma2, Tatjana Petrinic3
1Department of Anesthesiology, Perioperative and Pain Medicine, Harvard Medical School, Boston, Massachusetts, USA.
BMJ Open
|March 13, 2023
Summary
This systematic review critically appraises prediction models for atrial fibrillation after cardiac surgery (AFACS). It identifies methodological weaknesses to improve future clinical risk estimation tools.
Area of Science:
- Cardiology
- Medical Informatics
- Clinical Epidemiology
Background:
- Numerous multivariable prediction models for atrial fibrillation after cardiac surgery (AFACS) exist.
- Lack of clinical adoption stems from poor model performance and methodological weaknesses.
- Limited external validation hinders reproducibility and transportability of existing AFACS models.
Purpose of the Study:
- To critically appraise the methodology and risk of bias in studies developing or validating AFACS prediction models.
- To identify common weaknesses in the development and validation of AFACS prediction models.
- To guide future research toward creating clinically useful AFACS risk estimation tools.
Main Methods:
- Systematic review of studies published up to December 31, 2021, identified via PubMed, Embase, and Web of Science.
- Independent data extraction by two reviewers using adapted checklists (CCDC-PREDICT and PROBAST).
- Assessment of methodological quality and risk of bias, with findings reported via narrative synthesis and descriptive statistics.
Main Results:
- (Results will be populated upon study completion)
Conclusions:
- (Conclusions will be populated upon study completion)
