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 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
- loop mediated isothermal amplification
- high throughput
- label free
- real time pcr
- acute heart failure
- mechanical ventilation
- atrial fibrillation
- human health
- type diabetes
- risk assessment
- glycemic control
- single cell
- skeletal muscle