Development and external validation of a dynamic risk score for early prediction of cardiogenic shock in cardiac intensive care units using machine learning.
Yuxuan HuAlbert LuiMark GoldsteinMukund SudarshanAndrea TinsayCindy TsuiSamuel D MaidmanJohn MedamanaNeil JethaniAahlad PuliVuthy NguyYindalon AphinyanaphongsNicholas KieferNathaniel R SmilowitzJames HorowitzTania AhujaGlenn I FishmanJudith HochmanStuart KatzSamuel BernardRajesh RanganathPublished in: European heart journal. Acute cardiovascular care (2024)
The novel CShock score has the potential to provide automated detection and early warning for cardiogenic shock and improve the outcomes for the millions of patients who suffer from myocardial infarction and heart failure.
Keyphrases
- heart failure
- left ventricular
- intensive care unit
- cardiac resynchronization therapy
- machine learning
- deep learning
- high throughput
- loop mediated isothermal amplification
- label free
- real time pcr
- atrial fibrillation
- acute heart failure
- human health
- type diabetes
- adipose tissue
- metabolic syndrome
- acute respiratory distress syndrome
- climate change
- clinical evaluation