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Predicting Shunt Dependency from the Effect of Cerebrospinal Fluid Drainage on Ventricular Size.

Clio RubinosSoon Bin KwonMurad MegjhaniKalijah TerilliBrenda WongLizbeth CespedesJenna FordRenz ReyesHannah KirschAyham AlkhachroumAngela VelazquezDavid RohSachin AgarwalJan ClaassenE Sander ConnollySoojin Park
Published in: Neurocritical care (2022)
The correlation of ΔBCI and CSF output is a reliable intraindividual biometric for VPS dependency after SAH as early as days four to six after EVD placement. Our machine learning model leverages this relationship between ΔBCI and cumulative CSF output to predict VPS dependency. Early knowledge of VPS dependency could be studied to reduce EVD duration in many centers (intensive care unit length of stay).
Keyphrases
  • cerebrospinal fluid
  • intensive care unit
  • machine learning
  • healthcare
  • heart failure
  • ultrasound guided
  • left ventricular
  • big data
  • atrial fibrillation
  • catheter ablation
  • pulmonary arterial hypertension