The use of echocardiographic and clinical data recorded on admission to simplify decision making for elective percutaneous coronary intervention: a prospective cohort study.
Rabah M Al AbdiHussam AlshraidehHeba H HijaziMohamad JarrahMohammad S AlyahyaPublished in: BMC medical informatics and decision making (2019)
The prediction of HRQoL scores 6 months after an ePCI is possible based on data acquired on admission. The models developed here can be used as decision-making tools to guide physicians in identifying the efficacy of ePCIs for individual patients, hence decreasing the rate of inappropriate ePCIs and reducing costs and complications.
Keyphrases
- decision making
- percutaneous coronary intervention
- ejection fraction
- emergency department
- end stage renal disease
- electronic health record
- big data
- primary care
- acute myocardial infarction
- chronic kidney disease
- coronary artery disease
- st segment elevation myocardial infarction
- acute coronary syndrome
- patients undergoing
- prognostic factors
- heart failure
- pulmonary hypertension
- st elevation myocardial infarction
- deep learning
- artificial intelligence
- coronary artery bypass